{"hits":{"hits":[{"id":"1620205","created":"2017-08-29T00:00:00+00:00","links":{"bibtex":"https://inspirehep.net/api/literature/1620205?format=bibtex","latex-eu":"https://inspirehep.net/api/literature/1620205?format=latex-eu","latex-us":"https://inspirehep.net/api/literature/1620205?format=latex-us","json":"https://inspirehep.net/api/literature/1620205?format=json","json-expanded":"https://inspirehep.net/api/literature/1620205?format=json-expanded","cv":"https://inspirehep.net/api/literature/1620205?format=cv","citations":"https://inspirehep.net/api/literature/?q=refersto%3Arecid%3A1620205"},"metadata":{"citation_count":77,"report_numbers":[{"value":"CMS-EXO-17-006"},{"value":"CERN-EP-2017-194"}],"publication_info":[{"journal_volume":"119","artid":"221802","year":2017,"journal_record":{"$ref":"https://inspirehep.net/api/journals/1214495"},"journal_issue":"22","journal_title":"Phys.Rev.Lett."}],"documents":[{"filename":"10.1103_PhysRevLett.119.221802.pdf","attachment":{"content":"Search for Evidence of the Type-III Seesaw Mechanism in Multilepton Final States\nin Proton-Proton Collisions at\n\nffiffi\ns\n\np\n= 13 TeV\n\nA.M. Sirunyan et al.\n*\n\n(CMS Collaboration)\n(Received 26 August 2017; published 1 December 2017)\n\nA search for a signal consistent with the type-III seesaw mechanism in events with three or more\nelectrons or muons is presented. The data sample consists of proton-proton collisions at\n\nffiffiffi\ns\n\np ¼ 13 TeV\ncollected by the CMS experiment at the LHC in 2016 and corresponds to an integrated luminosity of\n35.9 fb−1. Selection criteria based on the number of leptons and the invariant mass of oppositely charged\nlepton pairs are used to distinguish the signal from the standard model background. The observations are\nconsistent with the expectations from standard model processes. The results are used to place limits on the\nproduction of heavy fermions of the type-III seesaw model as a function of the branching ratio to each\nlepton flavor. In the scenario of equal branching fractions to each lepton flavor, heavy fermions with masses\nbelow 840 GeV are excluded. This is the most sensitive probe to date of the type-III seesaw mechanism.\n\nDOI: 10.1103/PhysRevLett.119.221802\n\nThe discovery of neutrino oscillations established that\nneutrinos have mass [1]. Among proposed extensions of the\nstandard model (SM) that explain neutrino mass, models\nbased on the seesaw mechanism are an appealing possibil-\nity [2–10]. The seesaw mechanism introduces new heavy\nparticles that couple to leptons and to a Higgs boson (H)\ndoublet, and accounts for the smallness of neutrino masses\n[11–13]. Within the type-III seesaw model [8], the neutrino\nis considered a Majorana particle whose mass arises from\nthe mediation of new massive fermions that form an SU(2)\ntriplet of heavy Dirac charged leptons Σ� and a heavy\nMajorana neutral lepton Σ0. In proton-proton (pp) colli-\nsions, these massive fermions may be pair-produced\nthrough leading order electroweak interactions, in both\ncharged-charged and charged-neutral pairs. The renewed\ninterest in the type-III seesaw models [14–19] emphasizes\nthe importance of exploring such signatures at the CERN\nLHC.\nWe conduct a search for these new massive fermions by\n\nexamining final states with at least three electrons and\nmuons (including those that come from the decays of tau\nleptons) [20,21]. Such final states arise from these decays:\nΣ� → W�νl, Σ� → Zl�, Σ� → Hl�, Σ0 → W�l∓,\nΣ0 → Zνl, and Σ0 → Hνl, where l ¼ e, μ, or τ. The\nbranching fractions are mass dependent. A complete\ndecay chain example would be Σ�Σ0 → W�νW�l∓ →\nl�ννl�νl∓. In this search, we consider all 27 different\n\nproduction and decay processes resulting from the decays\nof each of the Σ0Σþ, Σ0Σ−, and ΣþΣ− pairs to the nine\ndifferent pairs of W, Z, and H bosons.\nIn the model used in this analysis [22], the Σ� and Σ0\n\ndecays are prompt, and gauge invariance ensures that they\nare degenerate in mass at tree level. The branching fraction\n(Bl) of a heavy fermion to a lepton of flavor l is\nproportional to jVlj2=ðjVej2 þ jVμj2 þ jVτj2Þ, where Vl\n\nis the heavy-light fermion mixing angle. A prior CMS\nsearch using 7 TeV data excluded heavy fermions with\nmass (mΣ) below 179 GeV [23], probing a scenario where\nthe branching fractions to all lepton flavors are equal\n(flavor-democratic scenario, Be¼Bμ¼Bτ). Using 8 TeV\ndata, the ATLAS Collaboration similarly excluded mΣ\nbelow 335 GeV, assuming that the Σ’s decay only to the\nfirst two generations of leptons [24]. In this Letter, we\nprobe all values of Bl for each flavor of l, subject to the\nconstraint Be þ Bμ þ Bτ ¼ 1.\nWe pursue a search in final states with at least three\n\ncharged leptons. The backgrounds can be classified as the\nirreducible ones due to the production and decay of\ndibosons (WZ and ZZ production), and the reducible ones\ndue to the leptonic decay of Z þ jets or tt̄þ jets accom-\npanied by leptons originating from heavy quark decay, or\nfrom misidentification of jets as leptons. In addition, small\nirreducible contributions to the background arise from other\nSM processes such as tt̄W, tt̄Z, triboson (ZZZ, WWZ,\netc.), and Higgs boson production.\nThe central feature of the CMS apparatus is a super-\n\nconducting solenoid of 6 m internal diameter, providing a\nmagnetic field of 3.8 T. Within the solenoid volume are a\nsilicon pixel and strip tracker, a lead tungstate crystal\nelectromagnetic calorimeter (ECAL), and a brass and\nscintillator hadron calorimeter, each composed of a barrel\nand two end cap sections. Forward calorimeters extend the\n\n*Full author list given at the end of the article.\n\nPublished by the American Physical Society under the terms of\nthe Creative Commons Attribution 4.0 International license.\nFurther distribution of this work must maintain attribution to\nthe author(s) and the published article’s title, journal citation,\nand DOI.\n\nPRL 119, 221802 (2017) P HY S I CA L R EV I EW LE T T ER S\nweek ending\n\n1 DECEMBER 2017\n\n0031-9007=17=119(22)=221802(17) 221802-1 © 2017 CERN, for the CMS Collaboration\n\nhttps://doi.org/10.1103/PhysRevLett.119.221802\nhttps://doi.org/10.1103/PhysRevLett.119.221802\nhttps://doi.org/10.1103/PhysRevLett.119.221802\nhttps://doi.org/10.1103/PhysRevLett.119.221802\nhttps://creativecommons.org/licenses/by/4.0/\nhttps://creativecommons.org/licenses/by/4.0/\n\n\npseudorapidity (η) coverage provided by the barrel and end\ncap detectors. Muons are detected in gas-ionization cham-\nbers embedded in the steel flux-return yoke outside the\nsolenoid. A detailed description of the CMS detector can be\nfound in Ref. [25].\nThe data sample consists of pp collisions at\n\nffiffiffi\ns\n\np ¼\n13 TeV collected by the CMS experiment at the LHC in\n2016, corresponding to an integrated luminosity of\n35.9 fb−1. The data for this search are collected using\nseveral dilepton triggers based on a two-level trigger\nsystem [26]. The double-electron (double-muon) trigger\nrequires two loosely isolated electrons (muons). The trans-\nverse momentum (pT) thresholds on the leading (sublead-\ning) lepton are 23 (12) GeV for the double electron, and 17\n(8) GeV for the double-muon trigger, respectively. We also\nuse two muon-electron cross-trigger combinations that\nrequire a pT > 23 GeV loosely isolated muon (electron)\nand a pT > 8 GeV loosely isolated electron (muon).\nThe signal is simulated using MADGRAPH5_aMC@NLO\n\nv2.2.2 [27] at leading order precision using the NNPDF30_\nlo_as_0130_nf_4 [28] parton distribution functions (PDFs).\nThe signal cross section is calculated at next-to-leading\norder (NLO) plus next-to-leading logarithmic accuracy,\nassuming that the heavy leptons, Σ�;0, are SU(2) triplet\nfermions [29,30]. The diboson backgrounds are generated at\nNLO with POWHEG 2.0 [31–33]. Backgrounds from Higgs\nboson production are generated using the POWHEG and\nJHUGEN 6.2.8 [34–37] generators. Triboson backgrounds are\ngenerated using MADGRAPH5_aMC@NLO. Bosonic decays,\nparton showering, fragmentation, and hadronization are\nsimulated for all samples using PYTHIA 8.212 [38,39].\nThe response of the CMS detector is simulated using\n\ndedicated software based on the GEANT4 toolkit [40]. The\npresence of multiple pp interactions in the same or adjacent\nbunch crossing (pileup) [41] is incorporated by simulating\nadditional interactions that are both in time and out of time\nwith the collision.\nEvents satisfying the trigger are required to pass addi-\n\ntional off-line selections. Electrons and muons must satisfy\npT > 10 GeV and jηj < 2.5 (jηj < 2.4 for muons). Ele-\nctrons are reconstructed using Gaussian sum filter tracks\nmatched to ECAL superclusters [42]. Muons are recon-\nstructed using the particle-flow (PF) algorithm [43] that\nutilizes measurements from the tracker, calorimeter, and\nmuon systems to reconstruct candidate muons, photons,\nand hadrons. Tracks of candidate electrons and muons must\nsatisfy quality requirements and should match geometri-\ncally with either energy deposits in the ECAL (for\nelectrons) or tracks in the muon detectors (for muons).\nJets are reconstructed from the PF candidates and\n\nelectrons using the anti-kT algorithm [44] with distance\nparameter R ¼ 0.4. Jets are required to have pT ≥ 30 GeV\nand jηj ≤ 3.0 and satisfy quality criteria that remove\ncontributions from pileup. The missing transverse momen-\ntum vector p⃗miss\n\nT is defined as the projection onto the plane\n\nperpendicular to the beam axis of the negative vector sum\nof the momenta of all reconstructed PF objects in an event\n[45]. Its magnitude is referred to as pmiss\n\nT . Jet energy\ncorrections are applied to all jets and also propagated to\nthe calculation of p⃗miss\n\nT .\nThe reducible backgrounds include leptons inside or near\n\njets and leptons from heavy quark decays. In addition,\nhadrons that reach the muon detectors, or hadronic showers\nwith large electromagnetic energy fractions can be mis-\nidentified as leptons. Henceforth, we refer to all leptons not\narising from vector boson decay (either directly or via\nan intermediate tau lepton) as misidentified leptons. Back-\ngrounds from misidentified leptons are significantly\nreduced by an isolation requirement comparing the pT\nof a lepton to the summed pT of particles in its neighbor-\nhood. We utilize relative isolation, which is defined as the\nscalar pT sum, normalized to the lepton pT , of photon and\nhadron PF candidates within a cone around the lepton. This\nrelative isolation is required to be less than 25% within a\ncone of size R ¼\n\nffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi\nðΔηÞ2 þ ðΔϕÞ2\n\np\n¼ 0.4 for muons,\n\nwhere ϕ is azimuthal angle in radians. For electrons, the\nrelative isolation within a cone of R ¼ 0.3must be less than\n7% (8%) for the reconstructed energy deposits situated in\nthe ECAL barrel [jηj < 1.479] (ECAL end cap\n[jηj > 1.479]). Charged tracks returned by a jet finding\nalgorithm [44,46] and the corresponding pmiss\n\nT are asso-\nciated with each reconstructed vertex. The vertex with the\nlargest value of Σp2\n\nT over the charged tracks and the p\nmiss\nT is\n\ntaken to be the primary pp interaction vertex. All isolation\nquantities are corrected for contributions from particles\noriginating from pileup vertices. Electrons and muons must\nsatisfy jdzj < 0.1 and jdxyj < 0.05 cm, where dz and dxy\nare the longitudinal and transverse impact parameters of\nleptons with respect to the primary vertex, respectively. For\nelectrons in the ECAL end cap, we relax these requirements\nto jdzj < 0.2 and jdxyj < 0.1 cm.\nFor the two leading leptons we apply off-line pT\n\nthresholds of 25 and 15 GeV. Additional leptons must\nsatisfy pT > 10 GeV. With these thresholds, the trigger\nefficiency for trilepton events is close to 100%. Events\ncontaining an opposite-sign same-flavor (OSSF) lepton\npair with mass below 12 GeV are vetoed to reduce back-\nground from low-mass resonances. We reject trilepton\nevents containing an OSSF pair with mass below\n81 GeV when the trilepton mass is within a Z boson mass\nwindow (91� 10 GeV). This suppresses events from the\nZ → ll� → llγ background process, where the photon\nconverts into two additional leptons, one of which is lost.\nWe classify the selected multilepton events into sta-\n\ntistically independent search channels using the number of\nleptons and OSSF pairs, and other kinematic quantities as\ndescribed below. The number of OSSF pairs is counted\nusing each lepton once. For example, μþμþe− is tagged as\nOSSF0, while μþμ−eþe− is tagged as OSSF2. We further\nclassify events as “on Z,” “below Z,” and “above Z,” based\n\nPRL 119, 221802 (2017) P HY S I CA L R EV I EW LE T T ER S\nweek ending\n\n1 DECEMBER 2017\n\n221802-2\n\n\n\non the presence andmass of at least oneOSSFpair relative to\na Z boson mass window, defined as the range 81–101 GeV.\nIn cases of ambiguity (such as μþμ−μ−), the OSSF pair with\nits mass closest to that of the Z boson takes precedence. We\ndefine LT as the scalar sum of all charged lepton pT’s, and\nwe use LT þ pmiss\n\nT as the main discriminating variable. This\nchoice allows us tomaintain sensitivity to decaymodes such\nas Σ� → l�Z → l�l�l∓ with large charged-lepton\nmomenta, as well as Σ0 → Hν → WWν, where charged\nlepton pT’s are lower but the neutrinos contribute to pmiss\n\nT .\nFor events with OSSF1 and on Z, the sensitivity is improved\nby considering the transverse mass, MT ¼ f2pmiss\n\nT pl\nT ½1 −\n\ncosðp⃗miss\nT ; p⃗l\n\nTÞ�g1=2 using the lepton that is not part of the\nOSSFpair. Events are grouped in eight bins ofwidth 150 and\n100 GeV for LT þ pmiss\n\nT andMT , respectively. In each case\nthe highest bin includes overflow events.\nAltogether, six event categories are considered with eight\n\nbins of LT þ pmiss\nT in (i) three leptons, OSSF1, above Z;\n\n(ii) three leptons, OSSF1, below Z; (iii) three leptons,\nOSSF0; (iv) four or more leptons, OSSF1; (v) four or more\nleptons, OSSF2; and eight bins of MT in (vi) three leptons,\nOSSF1, on Z. The 48 mutually exclusive signal regions are\nsummarized in Table I.\nThe irreducible backgrounds are estimated using simu-\n\nlation samples. The dominant processes are WZ and ZZ\nproduction and are normalized to data using dedicated\ncontrol regions. The WZ control sample consists of events\nwith exactly three leptons, tagged as OSSF1 onZ, satisfying\n50 < pmiss\n\nT < 100 and MT > 30 GeV. The ratio of the\npredictedWZ rate to data (after correcting for backgrounds\nother than WZ) is 1.15� 0.08, where the uncertainty\nincludes statistical and systematic contributions. The ZZ\ncontrol sample consists of events with exactly four leptons,\nOSSF2, on Z for both pairs, and with pmiss\n\nT < 50 GeV. The\nratio of the predicted ZZ rate to data is 1.25� 0.06. These\nfactors are used to normalize the WZ and ZZ background\nestimates. We also use these control regions to verify the\nmodeling of kinematic distributions such as LT þ pmiss\n\nT and\nMT . The “rare” irreducible backgrounds from triboson, tt̄W,\n\ntt̄Z, and Higgs boson processes are estimated from simu-\nlated samples using the theoretical cross sections.\nThe misidentified lepton background is estimated from\n\nobservations using a three-dimensional implementation of\na matrix method [47] in which probabilities (rates) of\nprompt and misidentified leptons satisfying a loose lepton\nselection to also pass a tight lepton selection are measured\nin data using a dilepton selection for prompt leptons,\nand a trilepton signal-depleted selection (OSSF1, on Z,\npmiss\nT < 50 GeV) for misidentified leptons. The rates are\n\nparametrized as a function of lepton pT , η and the number\nof PF candidates around the lepton. The rate measurements\nare dominated by Z þ jets events, and are corrected using\nsimulation to an average of Z þ jets and tt̄þ jets events.\nA residual “conversion” background is also estimated\n\nusing the data. When a final-state radiation photon from a\nlepton converts asymmetrically, oftenonlyoneof the resultant\nleptons is reconstructed in the detector. To estimate this\nbackground, we count trilepton events where the trilepton\nmass is on Z, but the dilepton mass is below Z. These events\nare compared with dileptonþ photon events where the\ndilepton invariantmass is belowZ, but the combined invariant\nmass of the two leptons and the photon is on Z. Photons\nsuitable for modeling conversions are selected by ignoring\nphotons that are far away from a lepton or are close to a jet.\nThe photon conversion rates are 3% to 5% depending upon\nthe lepton typeandpT . The conversionbackground in a signal\nregion is estimated by scaling the observed number of\ndileptonþ photon events with these rates.\nAs an example of the complete background estimation,\n\nFig. 1 shows the background predictions and the observed\nevents with three leptons, OSSF1, above Z, and for events\nwith four or more leptons, OSSF1, along with systematic\nuncertainties. The WZ (ZZ) background has a systematic\nuncertainty of 7% (5%) arising from the normalization factor\nmeasurement. The rare backgrounds have an uncertainty of\n50% in the theoretical cross section and 2.5% due to the\nintegrated luminosity measurement. The misidentified back-\ngroundhas anuncertaintyof 30%,which is derivedbyvarying\nthe measured rates up and down for each lepton flavor within\ntheir respective uncertainties. This uncertainty is dominated\nby the differences in rates inZ þ jets and tt̄þ jets events. The\nconversion background has an uncertainty of 30% arising\nfrom contamination by nonconversion backgrounds in the\ncontrol sample used to measure the conversion rate.\nCorrections are applied to the simulated backgroundevents\n\nto account for differences from data in lepton identification\nand isolation efficiencies, dilepton trigger efficiencies, as well\nas in the overall scale and resolutionof energy andmomentum\nmeasurements for electrons, muons, and jets. The minor\nuncertainties due to these corrections are considered sepa-\nrately and result in a 1%–10% variation of the simulation-\nbased background yields across all signal regions.\nThe uncertainties in the signal acceptance due to the PDF\n\nuncertainties are estimated by utilizing the replica weights\n\nTABLE I. The signal regions summarized in terms of the\nnumber of leptons, the presence of an OSSF pair, and the\nkinematic variable used for signal discrimination. Each region\nis divided into eight bins in the kinematic variable, leading to 48\nindependent signal regions. Additional criteria based on pmiss\n\nT\nensure that signal and control regions do not overlap.\n\nNleptons OSSF and mass Variable pmiss\nT requirement\n\n3 OSSF1, on Z MT pmiss\nT > 100 GeV\n\nOSSF1, above Z LT þ pmiss\nT no requirement\n\n3 OSSF1, below Z LT þ pmiss\nT pmiss\n\nT > 50 GeV\nOSSF0 LT þ pmiss\n\nT no requirement\n\n≥ 4\nOSSF1 LT þ pmiss\n\nT no requirement\nOSSF2 LT þ pmiss\n\nT pmiss\nT >50GeV if on Z\n\nPRL 119, 221802 (2017) P HY S I CA L R EV I EW LE T T ER S\nweek ending\n\n1 DECEMBER 2017\n\n221802-3\n\n\n\nof the NNPDF30_lo_as_0130_nf_4 PDF set [48], and are\nfound to be less than 3% in all signal bins. The signal yields\nalso have uncertainties due to the integrated luminosity\nmeasurement (2.5%) and the corrections applied to the\nsimulation samples mentioned in the previous paragraph.\nWe observe no statistically significant excess in the\n\nvarious signal regions that we probe. We calculate a\n95% confidence level (CL) upper limit on the sum of\ncross sections for the production of heavy fermion pairs\n(Σ0Σþ, Σ0Σ−, and ΣþΣ−) using the CLs criterion [49–52].\nWe consider all sources of systematic and statistical\nuncertainties as nuisance parameters, with log-normal\nand gamma prior distributions, respectively, and perform\na simultaneous fit across all search regions. Figure 2 shows\nthe upper limits on the cross section in the flavor-\ndemocratic scenario where the observed (expected) limit\n\non masses of heavy fermions is 840 (780) GeV. The signal\ncross section has an uncertainty of approximately 5%–15%\ndue to choices of PDFs, and factorization and renormal-\nization scales in the mass range we consider. Figure 3\nshows the expected and observed excluded mass limits in\nthe Be-Bτ plane [note that Bμ ¼ 1 − ðBe þ BτÞ]. The limits\nare the most restrictive when the Σ branching fraction to\neither electron or muon flavor is maximal, and become less\nrestrictive as the branching fraction to τ flavor increases.\n\n (GeV)miss\nT\n\n+pTL\n\nE\nve\n\nnt\ns \n\n/ 1\n50\n\n G\neV\n\n1−10\n\n1\n\n10\n\n210\n\n310\n\n410\n\n510\nData\nMisidentified\nWZ\nConversion\nZZ\nRare\nUncertainty\n\n380Σ\n700Σ\n\nCMS\n\n (13 TeV)-135.9 fb\n\n (GeV)miss\nT\n\n+pTL\n0 200 400 600 800 1000 1200\n\nO\nbs\n\n/E\nxp\n\n0\n0.5\n\n1\n1.5\n\n2\n\n (GeV)miss\nT\n\n+pTL\n\nE\nve\n\nnt\ns \n\n/ 1\n50\n\n G\neV\n\n1−10\n\n1\n\n10\n\n210\n\n310\n\n410\n\n510\nData\nZZ\nRare\nMisidentified\nConversion\nUncertainty\n\n380Σ\n700Σ\n\nCMS\n\n (13 TeV)-135.9 fb\n\n (GeV)miss\nT\n\n+pTL\n0 200 400 600 800 1000 1200\n\nO\nbs\n\n/E\nxp\n\n0\n0.5\n\n1\n1.5\n\n2\n\nFIG. 1. TheLT þ pmiss\nT distribution for events with three leptons\n\nand one OSSF pair with mass above Z (upper) and the LT þ pmiss\nT\n\ndistribution for events with four or more leptons and one OSSF\npair (lower). The total SM background is shown as a stacked\nhistogram of all contributing processes. The predictions for signal\nmodels (sum of all production and decay modes) with mΣ ¼ 700\n(solid line) andmΣ ¼ 380 GeV (dashed line) are also shown. The\nlower panels show the ratio of observed to expected events. The\nhatched gray band in the upper panel, and the dark and light gray\nbands in the lower panel represent the total, statistical, and\nsystematic uncertainties in the expected background, respectively.\n\n Mass (GeV)Σ\n200 300 400 500 600 700 800 900 1000\n\n (\npb\n\n)\nσ\n\n-310\n\n-210\n\n-110\n\n1\n\n10\n) with unc.ΣΣ→(ppσ\n\n95% CL upper limits\n\nObserved\n\nExpected\n\n 1 s.d.±Expected\n\n 2 s.d.±Expected\n\nCMS\n\n (13 TeV)-135.9 fb\n\nFIG. 2. The 95% confidence level upper limits on the cross\nsection for production of heavy fermion pairs (Σ0Σþ, Σ0Σ−, and\nΣþΣ−). Also shown is the theoretical prediction for the cross\nsection of the Σ pair production via the type-III seesaw mecha-\nnism, with its uncertainty. In the flavor-democratic scenario\n(Be ¼ Bμ ¼ Bτ), heavy fermion pair production is excluded\nfor masses below 840 GeV.\n\neB\n0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1\n\nτ\nB\n\n0\n\n0.1\n\n0.2\n\n0.3\n\n0.4\n\n0.5\n\n0.6\n\n0.7\n\n0.8\n\n0.9\n\n1\n\nM\nas\n\ns \nlim\n\nit \n(G\n\neV\n)\n\n300\n\n400\n\n500\n\n600\n\n700\n\n800\n\n900\n\n1000\n\n880 880 880 880 870 870 870 860 860 850 840\n\n860 860 860 850 850 850 840 830 830 820\n\n830 830 830 820 820 810 810 800 790\n\n800 800 800 780 790 780 770 760\n\n770 760 760 760 750 740 730\n\n730 730 720 710 710 700\n\n680 680 670 660 650\n\n630 620 610 600\n\n560 550 540\n\n480 470\n\n370\nCMS\n\n (13 TeV)-135.9 fb\n\nExpected\n95% CL exclusion limits\n\nM\nas\n\ns \nlim\n\nit \n(G\n\neV\n)\n\n300\n\n400\n\n500\n\n600\n\n700\n\n800\n\n900\n\n1000\n\neB\n0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1\n\nτ\nB\n\n0\n\n0.1\n\n0.2\n\n0.3\n\n0.4\n\n0.5\n\n0.6\n\n0.7\n\n0.8\n\n0.9\n\n1\n\n930 930 930 930 930 930 930 920 920 910 900\n\n910 910 910 910 910 910 900 900 890 880\n\n880 880 880 880 880 880 870 860 850\n\n850 860 860 840 850 850 840 820\n\n820 820 820 820 820 810 790\n\n790 790 790 780 770 760\n\n750 750 740 730 720\n\n700 700 690 680\n\n640 630 610\n\n550 530\n\n390\nCMS\n\n (13 TeV)-135.9 fb\n\nObserved\n95% CL exclusion limits\n\nFIG. 3. The 95% confidence level expected (upper) and ob-\nserved (lower) limits on the heavy fermionmassmΣ (GeV) for each\ncombination of branching fractions to the individual lepton\nflavors. The color scale represents the mass exclusion limit\nobtained at each point. The branching fraction to μ can be obtained\nfrom Bμ ¼ 1 − ½Be þ Bτ�. The highlighted box indicates the limit\non mΣ for the flavor-democratic scenario (Be ¼ Bμ ¼ Bτ).\n\nPRL 119, 221802 (2017) P HY S I CA L R EV I EW LE T T ER S\nweek ending\n\n1 DECEMBER 2017\n\n221802-4\n\n\n\nIn summary, a search has been performed for type-III\nseesaw heavy fermions in multilepton final states using\n35.9 fb−1 of pp collision data at\n\nffiffiffi\ns\n\np ¼ 13 TeV, collected\nusing the CMS detector. No significant discrepancies are\nobserved between the data and the standard model predic-\ntion. Assuming degenerate heavy fermion masses, previ-\nously unexplored regions of the signal model as a function\nof the branching ratio of heavy fermions to each lepton\nflavor are excluded. In the lepton-flavor democratic\nscenario (Be ¼ Bμ ¼ Bτ), heavy fermions with mass below\n840 GeV are excluded at 95% confidence level. In the\nτ-phobic case (Bτ ¼ 0, Be þ Bμ ¼ 1) the mass limits range\nfrom900GeVin the pure electron scenario to 930GeVin the\npure muon scenario. In the electron- or muon-phobic case\n(Bτ ¼ 1,Be þ Bμ ¼ 0) the mass limit is 390 GeV. These are\nthe strongest constraints to date on the mass of heavy\nfermions associated with the type-III seesaw mechanism.\n\nWe congratulate our colleagues in the CERN accelerator\ndepartments for the excellent performance of the LHC and\nthank the technical and administrative staffs at CERN and\nat other CMS institutes for their contributions to the success\nof the CMS effort. In addition, we gratefully acknowledge\nthe computing centers and personnel of the Worldwide\nLHC Computing Grid for delivering so effectively the\ncomputing infrastructure essential to our analyses. Finally,\nwe acknowledge the enduring support for the construction\nand operation of the LHC and the CMS detector provided\nby the following funding agencies: BMWFW and FWF\n(Austria); FNRS and FWO (Belgium); CNPq, CAPES,\nFAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN;\nCAS, MoST, and NSFC (China); COLCIENCIAS\n(Colombia); MSES and CSF (Croatia); RPF (Cyprus);\nSENESCYT (Ecuador); MoER, ERC IUT, and ERDF\n(Estonia); Academy of Finland, MEC, and HIP\n(Finland); CEA and CNRS/IN2P3 (France); BMBF,\nDFG, and HGF (Germany); GSRT (Greece); OTKA and\nNIH (Hungary); DAE and DST (India); IPM (Iran); SFI\n(Ireland); INFN (Italy); MSIP and NRF (Republic of\nKorea); LAS (Lithuania); MOE and UM (Malaysia);\nBUAP, CINVESTAV, CONACYT, LNS, SEP, and\nUASLP-FAI (Mexico); MBIE (New Zealand); PAEC\n(Pakistan); MSHE and NSC (Poland); FCT (Portugal);\nJINR (Dubna); MON, RosAtom, RAS, RFBR and RAEP\n(Russia); MESTD (Serbia); SEIDI, CPAN, PCTI and\nFEDER (Spain); Swiss Funding Agencies (Switzerland);\nMST (Taipei); ThEPCenter, IPST, STAR, and NSTDA\n(Thailand); TUBITAK and TAEK (Turkey); NASU and\nSFFR (Ukraine); STFC (United Kingdom); DOE and\nNSF (USA).\n\n[1] F. 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Tao,16 C. Wang,16\n\nZ. Wang,16 E. Yazgan,16 H. Zhang,16 J. Zhao,16 Y. Ban,17 G. Chen,17 Q. Li,17 S. Liu,17 Y. Mao,17 S. J. Qian,17 D. Wang,17\n\nZ. Xu,17 C. Avila,18 A. Cabrera,18 L. F. Chaparro Sierra,18 C. Florez,18 C. F. González Hernández,18 J. D. Ruiz Alvarez,18\n\nB. Courbon,19 N. Godinovic,19 D. Lelas,19 I. Puljak,19 P. M. Ribeiro Cipriano,19 T. Sculac,19 Z. Antunovic,20 M. Kovac,20\n\nV. Brigljevic,21 D. Ferencek,21 K. Kadija,21 B. Mesic,21 A. Starodumov,21,g T. Susa,21 M.W. Ather,22 A. Attikis,22\n\nG. Mavromanolakis,22 J. Mousa,22 C. Nicolaou,22 F. Ptochos,22 P. A. Razis,22 H. Rykaczewski,22 M. Finger,23,h\n\nM. Finger Jr.,23,h E. Carrera Jarrin,24 E. El-khateeb,25,i S. Elgammal,25,j A. Ellithi Kamel,25,k R. K. Dewanjee,26\n\nM. Kadastik,26 L. Perrini,26 M. Raidal,26 A. Tiko,26 C. Veelken,26 P. Eerola,27 J. Pekkanen,27 M. Voutilainen,27\n\nJ. Härkönen,28 T. Järvinen,28 V. Karimäki,28 R. Kinnunen,28 T. Lampén,28 K. Lassila-Perini,28 S. Lehti,28 T. Lindén,28\n\nP. Luukka,28 E. Tuominen,28 J. Tuominiemi,28 E. Tuovinen,28 J. Talvitie,29 T. Tuuva,29 M. Besancon,30 F. Couderc,30\n\nM. Dejardin,30 D. Denegri,30 J. L. Faure,30 F. Ferri,30 S. Ganjour,30 S. Ghosh,30 A. Givernaud,30 P. Gras,30\n\nG. Hamel de Monchenault,30 P. Jarry,30 I. Kucher,30 E. Locci,30 M. Machet,30 J. Malcles,30 G. Negro,30 J. Rander,30\n\nA. Rosowsky,30 M. Ö. Sahin,30 M. Titov,30 A. Abdulsalam,31 I. Antropov,31 S. Baffioni,31 F. Beaudette,31 P. Busson,31\n\nL. Cadamuro,31 C. Charlot,31 R. Granier de Cassagnac,31 M. Jo,31 S. Lisniak,31 A. Lobanov,31 J. Martin Blanco,31\n\nM. Nguyen,31 C. Ochando,31 G. Ortona,31 P. Paganini,31 P. Pigard,31 S. Regnard,31 R. Salerno,31 J. B. Sauvan,31 Y. Sirois,31\n\nA. G. Stahl Leiton,31 T. Strebler,31 Y. Yilmaz,31 A. Zabi,31 A. Zghiche,31 J.-L. Agram,32,l J. Andrea,32 D. Bloch,32\n\nJ.-M. Brom,32 M. Buttignol,32 E. C. Chabert,32 N. Chanon,32 C. Collard,32 E. Conte,32,l X. Coubez,32 J.-C. Fontaine,32,l\n\nD. Gelé,32 U. Goerlach,32 M. Jansová,32 A.-C. Le Bihan,32 N. Tonon,32 P. Van Hove,32 S. Gadrat,33 S. Beauceron,34\n\nC. Bernet,34 G. Boudoul,34 R. Chierici,34 D. Contardo,34 P. Depasse,34 H. El Mamouni,34 J. Fay,34 L. Finco,34 S. Gascon,34\n\nM. Gouzevitch,34 G. Grenier,34 B. Ille,34 F. Lagarde,34 I. B. Laktineh,34 M. Lethuillier,34 L. Mirabito,34 A. L. Pequegnot,34\n\nS. Perries,34 A. Popov,34,m V. Sordini,34 M. Vander Donckt,34 S. Viret,34 T. Toriashvili,35,n D. Lomidze,36 C. Autermann,37\n\nS. Beranek,37 L. Feld,37 M. K. Kiesel,37 K. Klein,37 M. Lipinski,37 M. Preuten,37 C. Schomakers,37 J. Schulz,37 T. Verlage,37\n\nA. Albert,38 E. Dietz-Laursonn,38 D. Duchardt,38 M. Endres,38 M. Erdmann,38 S. Erdweg,38 T. Esch,38 R. Fischer,38\n\nA. Güth,38 M. Hamer,38 T. Hebbeker,38 C. Heidemann,38 K. Hoepfner,38 S. Knutzen,38 M. Merschmeyer,38 A. Meyer,38\n\nP. Millet,38 S. Mukherjee,38 M. Olschewski,38 K. Padeken,38 T. Pook,38 M. Radziej,38 H. Reithler,38 M. Rieger,38\n\nF. Scheuch,38 D. Teyssier,38 S. Thüer,38 G. Flügge,39 B. Kargoll,39 T. Kress,39 A. Künsken,39 J. Lingemann,39 T. Müller,39\n\nA. Nehrkorn,39 A. Nowack,39 C. Pistone,39 O. Pooth,39 A. Stahl,39,o M. Aldaya Martin,40 T. Arndt,40\n\nC. Asawatangtrakuldee,40 K. Beernaert,40 O. Behnke,40 U. Behrens,40 A. Bermúdez Martínez,40 A. A. Bin Anuar,40\n\nK. Borras,40,p V. Botta,40 A. Campbell,40 P. Connor,40 C. Contreras-Campana,40 F. Costanza,40 C. Diez Pardos,40\n\nG. Eckerlin,40 D. Eckstein,40 T. Eichhorn,40 E. Eren,40 E. Gallo,40,q J. Garay Garcia,40 A. Geiser,40 A. Gizhko,40\n\nJ. M. Grados Luyando,40 A. Grohsjean,40 P. Gunnellini,40 A. Harb,40 J. Hauk,40 M. Hempel,40,r H. Jung,40\n\nA. Kalogeropoulos,40 M. Kasemann,40 J. Keaveney,40 C. Kleinwort,40 I. Korol,40 D. Krücker,40 W. Lange,40 A. Lelek,40\n\nT. Lenz,40 J. Leonard,40 K. Lipka,40 W. Lohmann,40,r R. Mankel,40 I.-A. Melzer-Pellmann,40 A. B. Meyer,40 G. Mittag,40\n\nPRL 119, 221802 (2017) P HY S I CA L R EV I EW LE T T ER S\nweek ending\n\n1 DECEMBER 2017\n\n221802-7\n\n\n\nJ. Mnich,40 A. Mussgiller,40 E. Ntomari,40 D. Pitzl,40 A. Raspereza,40 B. Roland,40 M. Savitskyi,40 P. Saxena,40\n\nR. Shevchenko,40 S. Spannagel,40 N. Stefaniuk,40 G. P. Van Onsem,40 R. Walsh,40 Y. Wen,40 K. Wichmann,40 C. Wissing,40\n\nO. Zenaiev,40 S. Bein,41 V. Blobel,41 M. Centis Vignali,41 T. Dreyer,41 E. Garutti,41 D. Gonzalez,41 J. Haller,41\n\nA. Hinzmann,41 M. Hoffmann,41 A. Karavdina,41 R. Klanner,41 R. Kogler,41 N. Kovalchuk,41 S. Kurz,41 T. Lapsien,41\n\nI. Marchesini,41 D. Marconi,41 M. Meyer,41 M. Niedziela,41 D. Nowatschin,41 F. Pantaleo,41,o T. Peiffer,41 A. Perieanu,41\n\nC. Scharf,41 P. Schleper,41 A. Schmidt,41 S. Schumann,41 J. Schwandt,41 J. Sonneveld,41 H. Stadie,41 G. Steinbrück,41\n\nF. M. Stober,41 M. Stöver,41 H. Tholen,41 D. Troendle,41 E. Usai,41 L. Vanelderen,41 A. Vanhoefer,41 B. Vormwald,41\n\nM. Akbiyik,42 C. Barth,42 S. Baur,42 E. Butz,42 R. Caspart,42 T. Chwalek,42 F. Colombo,42 W. De Boer,42 A. Dierlamm,42\n\nB. Freund,42 R. Friese,42 M. Giffels,42 A. Gilbert,42 D. Haitz,42 F. Hartmann,42,o S. M. Heindl,42 U. Husemann,42\n\nF. Kassel,42,o S. Kudella,42 H. Mildner,42 M. U. Mozer,42 Th. Müller,42 M. Plagge,42 G. Quast,42 K. Rabbertz,42\n\nM. Schröder,42 I. Shvetsov,42 G. Sieber,42 H. J. Simonis,42 R. Ulrich,42 S. Wayand,42 M. Weber,42 T. Weiler,42\n\nS. Williamson,42 C. Wöhrmann,42 R. Wolf,42 G. Anagnostou,43 G. Daskalakis,43 T. Geralis,43 V. A. Giakoumopoulou,43\n\nA. Kyriakis,43 D. Loukas,43 I. Topsis-Giotis,43 G. Karathanasis,44 S. Kesisoglou,44 A. Panagiotou,44 N. Saoulidou,44\n\nI. Evangelou,45 C. Foudas,45 P. Kokkas,45 S. Mallios,45 N. Manthos,45 I. Papadopoulos,45 E. Paradas,45 J. Strologas,45\n\nF. A. Triantis,45 M. Csanad,46 N. Filipovic,46 G. Pasztor,46 G. Bencze,47 C. Hajdu,47 D. Horvath,47,s Á. Hunyadi,47 F. Sikler,47\n\nV. Veszpremi,47 G. Vesztergombi,47,t A. J. Zsigmond,47 N. Beni,48 S. Czellar,48 J. Karancsi,48,u A. Makovec,48 J. Molnar,48\n\nZ. Szillasi,48 M. Bartók,49,t P. Raics,49 Z. L. Trocsanyi,49 B. Ujvari,49 S. Choudhury,50 J. R. Komaragiri,50 S. Bahinipati,51,v\n\nS. Bhowmik,51 P. Mal,51 K. Mandal,51 A. Nayak,51,w D. K. Sahoo,51,v N. Sahoo,51 S. K. Swain,51 S. Bansal,52 S. B. Beri,52\n\nV. Bhatnagar,52 R. Chawla,52 N. Dhingra,52 A. K. Kalsi,52 A. Kaur,52 M. Kaur,52 R. Kumar,52 P. Kumari,52 A. Mehta,52\n\nJ. B. Singh,52 G. Walia,52 Ashok Kumar,53 Aashaq Shah,53 A. Bhardwaj,53 S. Chauhan,53 B. C. Choudhary,53 R. B. Garg,53\n\nS. Keshri,53 A. Kumar,53 S. Malhotra,53 M. Naimuddin,53 K. Ranjan,53 R. Sharma,53 V. Sharma,53 R. Bhardwaj,54\n\nR. Bhattacharya,54 S. Bhattacharya,54 U. Bhawandeep,54 S. Dey,54 S. Dutt,54 S. Dutta,54 S. Ghosh,54 N. Majumdar,54\n\nA. Modak,54 K. Mondal,54 S. Mukhopadhyay,54 S. Nandan,54 A. Purohit,54 A. Roy,54 D. Roy,54 S. Roy Chowdhury,54\n\nS. Sarkar,54 M. Sharan,54 S. Thakur,54 P. K. Behera,55 R. Chudasama,56 D. Dutta,56 V. Jha,56 V. Kumar,56 A. K. Mohanty,56,o\n\nP. K. Netrakanti,56 L. M. Pant,56 P. Shukla,56 A. Topkar,56 T. Aziz,57 S. Dugad,57 B. Mahakud,57 S. Mitra,57 G. B. Mohanty,57\n\nN. Sur,57 B. Sutar,57 S. Banerjee,58 S. Bhattacharya,58 S. Chatterjee,58 P. Das,58 M. Guchait,58 Sa. Jain,58 S. Kumar,58\n\nM. Maity,58,x G. Majumder,58 K. Mazumdar,58 T. Sarkar,58,x N. Wickramage,58,y S. Chauhan,59 S. Dube,59 V. Hegde,59\n\nA. Kapoor,59 K. Kothekar,59 S. Pandey,59 A. Rane,59 S. Sharma,59 S. Chenarani,60,z E. Eskandari Tadavani,60\n\nS. M. Etesami,60,z M. Khakzad,60 M. Mohammadi Najafabadi,60 M. Naseri,60 S. Paktinat Mehdiabadi,60,aa\n\nF. Rezaei Hosseinabadi,60 B. Safarzadeh,60,bb M. Zeinali,60 M. Felcini,61 M. Grunewald,61 M. Abbrescia,62a,62b\n\nC. Calabria,62a,62b C. Caputo,62a,62b A. Colaleo,62a D. Creanza,62a,62c L. Cristella,62a,62b N. De Filippis,62a,62c\n\nM. De Palma,62a,62b F. Errico,62a,62b L. Fiore,62a G. Iaselli,62a,62c S. Lezki,62a,62b G. Maggi,62a,62c M. Maggi,62a\n\nG. Miniello,62a,62b S. My,62a,62b S. Nuzzo,62a,62b A. Pompili,62a,62b G. Pugliese,62a,62c R. Radogna,62a,62b A. Ranieri,62a\n\nG. Selvaggi,62a,62b A. Sharma,62a L. Silvestris,62a,o R. Venditti,62a P. Verwilligen,62a G. Abbiendi,63a C. Battilana,63a,63b\n\nD. Bonacorsi,63a,63b S. Braibant-Giacomelli,63a,63b R. Campanini,63a,63b P. Capiluppi,63a,63b A. Castro,63a,63b F. R. Cavallo,63a\n\nS. S. Chhibra,63a G. Codispoti,63a,63b M. Cuffiani,63a,63b G. M. Dallavalle,63a F. Fabbri,63a A. Fanfani,63a,63b D. Fasanella,63a,63b\n\nP. Giacomelli,63a C. Grandi,63a L. Guiducci,63a,63b S. Marcellini,63a G. Masetti,63a A. Montanari,63a F. L. Navarria,63a,63b\n\nA. Perrotta,63a A. M. Rossi,63a,63b T. Rovelli,63a,63b G. P. Siroli,63a,63b N. Tosi,63a S. Albergo,64a,64b S. Costa,64a,64b\n\nA. Di Mattia,64a F. Giordano,64a,64b R. Potenza,64a,64b A. Tricomi,64a,64b C. Tuve,64a,64b G. Barbagli,65a K. Chatterjee,65a,65b\n\nV. Ciulli,65a,65b C. Civinini,65a R. D’Alessandro,65a,65b E. Focardi,65a,65b P. Lenzi,65a,65b M. Meschini,65a S. Paoletti,65a\n\nL. Russo,65a,cc G. Sguazzoni,65a D. Strom,65a L. Viliani,65a,65b,o L. Benussi,66 S. Bianco,66 F. Fabbri,66 D. Piccolo,66\n\nF. Primavera,66,o C. Biggio,67a V. Calvelli,67a,67b F. Ferro,67a E. Robutti,67a S. Tosi,67a,67b L. Brianza,68a,68b F. Brivio,68a,68b\n\nV. Ciriolo,68a,68b M. E. Dinardo,68a,68b S. Fiorendi,68a,68b S. Gennai,68a A. Ghezzi,68a,68b P. Govoni,68a,68b M. Malberti,68a,68b\n\nS. Malvezzi,68a R. A. Manzoni,68a,68b D. Menasce,68a L. Moroni,68a M. Paganoni,68a,68b K. Pauwels,68a,68b D. Pedrini,68a\n\nS. Pigazzini,68a,68b,dd S. Ragazzi,68a,68b T. Tabarelli de Fatis,68a,68b S. Buontempo,69a N. Cavallo,69a,69c S. Di Guida,69a,69d,o\n\nF. Fabozzi,69a,69c F. Fienga,69a,69b A. O. M. Iorio,69a,69b W. A. Khan,69a L. Lista,69a S. Meola,69a,69d,o P. Paolucci,69a,o\n\nC. Sciacca,69a,69b F. Thyssen,69a P. Azzi,70a,o N. Bacchetta,70a L. Benato,70a,70b D. Bisello,70a,70b A. Boletti,70a,70b\n\nR. Carlin,70a,70b A. Carvalho Antunes De Oliveira,70a,70b P. Checchia,70a P. De Castro Manzano,70a T. Dorigo,70a\n\nF. Gasparini,70a,70b U. Gasparini,70a,70b A. Gozzelino,70a S. Lacaprara,70a P. Lujan,70a M. Margoni,70a,70b\n\nPRL 119, 221802 (2017) P HY S I CA L R EV I EW LE T T ER S\nweek ending\n\n1 DECEMBER 2017\n\n221802-8\n\n\n\nA. T. Meneguzzo,70a,70b N. Pozzobon,70a,70b P. Ronchese,70a,70b R. Rossin,70a,70b F. Simonetto,70a,70b E. Torassa,70a\n\nM. Zanetti,70a,70b P. Zotto,70a,70b G. Zumerle,70a,70b A. Braghieri,71a F. Fallavollita,71a,71b A. Magnani,71a,71b P. Montagna,71a,71b\n\nS. P. Ratti,71a,71b V. Re,71a M. Ressegotti,71a C. Riccardi,71a,71b P. Salvini,71a I. Vai,71a,71b P. Vitulo,71a,71b\n\nL. Alunni Solestizi,72a,72b M. Biasini,72a,72b G. M. Bilei,72a C. Cecchi,72a,72b D. Ciangottini,72a,72b L. Fanò,72a,72b\n\nP. Lariccia,72a,72b R. Leonardi,72a,72b E. Manoni,72a G. Mantovani,72a,72b V. Mariani,72a,72b M. Menichelli,72a A. Rossi,72a,72b\n\nA. Santocchia,72a,72b D. Spiga,72a K. Androsov,73a P. Azzurri,73a,o G. Bagliesi,73a J. Bernardini,73a T. Boccali,73a\n\nL. Borrello,73a R. Castaldi,73a M. A. Ciocci,73a,73b R. Dell’Orso,73a G. Fedi,73a L. Giannini,73a,73c A. Giassi,73a\n\nM. T. Grippo,73a,cc F. Ligabue,73a,73c T. Lomtadze,73a E. Manca,73a,73c G. Mandorli,73a,73c L. Martini,73a,73b A. Messineo,73a,73b\n\nF. Palla,73a A. Rizzi,73a,73b A. Savoy-Navarro,73a,ee P. Spagnolo,73a R. Tenchini,73a G. Tonelli,73a,73b A. Venturi,73a\n\nP. G. Verdini,73a L. Barone,74a,74b F. Cavallari,74a M. Cipriani,74a,74b N. Daci,74a D. Del Re,74a,74b,o M. Diemoz,74a\n\nS. Gelli,74a,74b E. Longo,74a,74b F. Margaroli,74a,74b B. Marzocchi,74a,74b P. Meridiani,74a G. Organtini,74a,74b R. Paramatti,74a,74b\n\nF. Preiato,74a,74b S. Rahatlou,74a,74b C. Rovelli,74a F. Santanastasio,74a,74b N. Amapane,75a,75b R. Arcidiacono,75a,75c\n\nS. Argiro,75a,75b M. Arneodo,75a,75c N. Bartosik,75a R. Bellan,75a,75b C. Biino,75a N. Cartiglia,75a F. Cenna,75a,75b\n\nM. Costa,75a,75b R. Covarelli,75a,75b A. Degano,75a,75b N. Demaria,75a B. Kiani,75a,75b C. Mariotti,75a S. Maselli,75a\n\nE. Migliore,75a,75b V. Monaco,75a,75b E. Monteil,75a,75b M. Monteno,75a M.M. Obertino,75a,75b L. Pacher,75a,75b N. Pastrone,75a\n\nM. Pelliccioni,75a G. L. Pinna Angioni,75a,75b F. Ravera,75a,75b A. Romero,75a,75b M. Ruspa,75a,75c R. Sacchi,75a,75b\n\nK. Shchelina,75a,75b V. Sola,75a A. Solano,75a,75b A. Staiano,75a P. Traczyk,75a,75b S. Belforte,76a M. Casarsa,76a F. Cossutti,76a\n\nG. Della Ricca,76a,76b A. Zanetti,76a D. H. Kim,77 G. N. Kim,77 M. S. Kim,77 J. Lee,77 S. Lee,77 S.W. Lee,77 C. S. Moon,77\n\nY. D. Oh,77 S. Sekmen,77 D. C. Son,77 Y. C. Yang,77 A. Lee,78 H. Kim,79 D. H. Moon,79 G. Oh,79 J. A. Brochero Cifuentes,80\n\nJ. Goh,80 T. J. Kim,80 S. Cho,81 S. Choi,81 Y. Go,81 D. Gyun,81 S. Ha,81 B. Hong,81 Y. Jo,81 Y. Kim,81 K. Lee,81 K. S. Lee,81\n\nS. Lee,81 J. Lim,81 S. K. Park,81 Y. Roh,81 J. Almond,82 J. Kim,82 J. S. Kim,82 H. Lee,82 K. Lee,82 K. Nam,82 S. B. Oh,82\n\nB. C. Radburn-Smith,82 S. h. Seo,82 U. K. Yang,82 H. D. Yoo,82 G. B. Yu,82 M. Choi,83 H. Kim,83 J. H. Kim,83 J. S. H. Lee,83\n\nI. C. Park,83 G. Ryu,83 Y. Choi,84 C. Hwang,84 J. Lee,84 I. Yu,84 V. Dudenas,85 A. Juodagalvis,85 J. Vaitkus,85 I. Ahmed,86\n\nZ. A. Ibrahim,86 M. A. B. Md Ali,86,ff F. Mohamad Idris,86,gg W. A. T. Wan Abdullah,86 M. N. Yusli,86 Z. Zolkapli,86\n\nR. Reyes-Almanza,87 G. Ramirez-Sanchez,87 M. C. Duran-Osuna,87 H. Castilla-Valdez,87 E. De La Cruz-Burelo,87\n\nI. Heredia-De La Cruz,87,hh R. I. Rabadan-Trejo,87 R. Lopez-Fernandez,87 J. Mejia Guisao,87 A. Sanchez-Hernandez,87\n\nS. Carrillo Moreno,88 C. Oropeza Barrera,88 F. Vazquez Valencia,88 I. Pedraza,89 H. A. Salazar Ibarguen,89\n\nC. Uribe Estrada,89 A. Morelos Pineda,90 D. Krofcheck,91 P. H. Butler,92 A. Ahmad,93 M. Ahmad,93 Q. Hassan,93\n\nH. R. Hoorani,93 A. Saddique,93 M. A. Shah,93 M. Shoaib,93 M. Waqas,93 H. Bialkowska,94 M. Bluj,94 B. Boimska,94\n\nT. Frueboes,94 M. Górski,94 M. Kazana,94 K. Nawrocki,94 K. Romanowska-Rybinska,94 M. Szleper,94 P. Zalewski,94\n\nK. Bunkowski,95 A. Byszuk,95,ii K. Doroba,95 A. Kalinowski,95 M. Konecki,95 J. Krolikowski,95 M. Misiura,95\n\nM. Olszewski,95 A. Pyskir,95 M. Walczak,95 P. Bargassa,96 C. Beirão Da Cruz E Silva,96 B. Calpas,96,jj A. Di Francesco,96\n\nP. Faccioli,96 M. Gallinaro,96 J. Hollar,96 N. Leonardo,96 L. Lloret Iglesias,96 M. V. Nemallapudi,96 J. Seixas,96 O. Toldaiev,96\n\nD. Vadruccio,96 J. Varela,96 S. Afanasiev,97 P. Bunin,97 M. Gavrilenko,97 I. Golutvin,97 I. Gorbunov,97 A. Kamenev,97\n\nV. Karjavin,97 A. Lanev,97 A. Malakhov,97 V. Matveev,97,kk,ll V. Palichik,97 V. Perelygin,97 S. Shmatov,97 S. Shulha,97\n\nN. Skatchkov,97 V. Smirnov,97 N. Voytishin,97 A. Zarubin,97 Y. Ivanov,98 V. Kim,98,mm E. Kuznetsova,98,nn P. Levchenko,98\n\nV. Murzin,98 V. Oreshkin,98 I. Smirnov,98 V. Sulimov,98 L. Uvarov,98 S. Vavilov,98 A. Vorobyev,98 Yu. Andreev,99\n\nA. Dermenev,99 S. Gninenko,99 N. Golubev,99 A. Karneyeu,99 M. Kirsanov,99 N. Krasnikov,99 A. Pashenkov,99 D. Tlisov,99\n\nA. Toropin,99 V. Epshteyn,100 V. Gavrilov,100 N. Lychkovskaya,100 V. Popov,100 I. Pozdnyakov,100 G. Safronov,100\n\nA. Spiridonov,100 A. Stepennov,100 M. Toms,100 E. Vlasov,100 A. Zhokin,100 T. Aushev,101 A. Bylinkin,101,ll R. Chistov,102,oo\n\nM. Danilov,102,oo P. Parygin,102 D. Philippov,102 S. Polikarpov,102 E. Tarkovskii,102 V. Andreev,103 M. Azarkin,103,ll\n\nI. Dremin,103,ll M. Kirakosyan,103,ll A. Terkulov,103 A. Baskakov,104 A. Belyaev,104 E. Boos,104 M. Dubinin,104,pp\n\nL. Dudko,104 A. Ershov,104 A. Gribushin,104 V. Klyukhin,104 O. Kodolova,104 I. Lokhtin,104 I. Miagkov,104 S. Obraztsov,104\n\nS. Petrushanko,104 V. Savrin,104 A. Snigirev,104 V. Blinov,105,qq Y. Skovpen,105,qq D. Shtol,105,qq I. Azhgirey,106 I. Bayshev,106\n\nS. Bitioukov,106 D. Elumakhov,106 V. Kachanov,106 A. Kalinin,106 D. Konstantinov,106 V. Krychkine,106 V. Petrov,106\n\nR. Ryutin,106 A. Sobol,106 S. Troshin,106 N. Tyurin,106 A. Uzunian,106 A. Volkov,106 P. Adzic,107,rr P. Cirkovic,107\n\nD. Devetak,107 M. Dordevic,107 J. Milosevic,107 V. Rekovic,107 J. Alcaraz Maestre,108 M. Barrio Luna,108 M. Cerrada,108\n\nN. Colino,108 B. De La Cruz,108 A. Delgado Peris,108 A. Escalante Del Valle,108 C. Fernandez Bedoya,108\n\nJ. P. Fernández Ramos,108 J. Flix,108 M. C. Fouz,108 P. Garcia-Abia,108 O. Gonzalez Lopez,108 S. Goy Lopez,108\n\nPRL 119, 221802 (2017) P HY S I CA L R EV I EW LE T T ER S\nweek ending\n\n1 DECEMBER 2017\n\n221802-9\n\n\n\nJ. M. Hernandez,108 M. I. Josa,108 A. Pérez-Calero Yzquierdo,108 J. Puerta Pelayo,108 A. Quintario Olmeda,108\n\nI. Redondo,108 L. Romero,108 M. S. Soares,108 A. Álvarez Fernández,108 J. F. de Trocóniz,109 M. Missiroli,109 D. Moran,109\n\nJ. Cuevas,110 C. Erice,110 J. Fernandez Menendez,110 I. Gonzalez Caballero,110 J. R. González Fernández,110\n\nE. Palencia Cortezon,110 S. Sanchez Cruz,110 I. Suárez Andrés,110 P. Vischia,110 J. M. Vizan Garcia,110 I. J. Cabrillo,111\n\nA. Calderon,111 B. Chazin Quero,111 E. Curras,111 J. Duarte Campderros,111 M. Fernandez,111 J. Garcia-Ferrero,111\n\nG. Gomez,111 A. Lopez Virto,111 J. Marco,111 C. Martinez Rivero,111 P. Martinez Ruiz del Arbol,111 F. Matorras,111\n\nJ. Piedra Gomez,111 T. Rodrigo,111 A. Ruiz-Jimeno,111 L. Scodellaro,111 N. Trevisani,111 I. Vila,111 R. Vilar Cortabitarte,111\n\nD. Abbaneo,112 E. Auffray,112 P. Baillon,112 A. H. Ball,112 D. Barney,112 M. Bianco,112 P. Bloch,112 A. Bocci,112 C. Botta,112\n\nT. Camporesi,112 R. Castello,112 M. Cepeda,112 G. Cerminara,112 E. Chapon,112 Y. Chen,112 D. d’Enterria,112\n\nA. Dabrowski,112 V. Daponte,112 A. David,112 M. De Gruttola,112 A. De Roeck,112 E. Di Marco,112,ss M. Dobson,112\n\nB. Dorney,112 T. du Pree,112 M. Dünser,112 N. Dupont,112 A. Elliott-Peisert,112 P. Everaerts,112 G. Franzoni,112 J. Fulcher,112\n\nW. Funk,112 D. Gigi,112 K. Gill,112 F. Glege,112 D. Gulhan,112 S. Gundacker,112 M. Guthoff,112 P. Harris,112 J. Hegeman,112\n\nV. Innocente,112 P. Janot,112 O. Karacheban,112,r J. Kieseler,112 H. Kirschenmann,112 V. Knünz,112 A. Kornmayer,112,o\n\nM. J. Kortelainen,112 M. Krammer,112,b C. Lange,112 P. Lecoq,112 C. Lourenço,112 M. T. Lucchini,112 L. Malgeri,112\n\nM. Mannelli,112 A. Martelli,112 F. Meijers,112 J. A. Merlin,112 S. Mersi,112 E. Meschi,112 P. Milenovic,112,tt F. Moortgat,112\n\nM. Mulders,112 H. Neugebauer,112 S. Orfanelli,112 L. Orsini,112 L. Pape,112 E. Perez,112 M. Peruzzi,112 A. Petrilli,112\n\nG. Petrucciani,112 A. Pfeiffer,112 M. Pierini,112 A. Racz,112 T. Reis,112 G. Rolandi,112,uu M. Rovere,112 H. Sakulin,112\n\nC. Schäfer,112 C. Schwick,112 M. Seidel,112 M. Selvaggi,112 A. Sharma,112 P. Silva,112 P. Sphicas,112,vv A. Stakia,112\n\nJ. Steggemann,112 M. Stoye,112 M. Tosi,112 D. Treille,112 A. Triossi,112 A. Tsirou,112 V. Veckalns,112,ww G. I. Veres,112,t\n\nM. Verweij,112 N. Wardle,112 W. D. Zeuner,112 W. Bertl,113,a L. Caminada,113,xx K. Deiters,113 W. Erdmann,113\n\nR. Horisberger,113 Q. Ingram,113 H. C. Kaestli,113 D. Kotlinski,113 U. Langenegger,113 T. Rohe,113 S. A. Wiederkehr,113\n\nF. Bachmair,114 L. Bäni,114 P. Berger,114 L. Bianchini,114 B. Casal,114 G. Dissertori,114 M. Dittmar,114 M. Donegà,114\n\nC. Grab,114 C. Heidegger,114 D. Hits,114 J. Hoss,114 G. Kasieczka,114 T. Klijnsma,114 W. Lustermann,114 B. Mangano,114\n\nM. Marionneau,114 M. T. Meinhard,114 D. Meister,114 F. Micheli,114 P. Musella,114 F. Nessi-Tedaldi,114 F. Pandolfi,114\n\nJ. Pata,114 F. Pauss,114 G. Perrin,114 L. Perrozzi,114 M. Quittnat,114 M. Reichmann,114 M. Schönenberger,114 L. Shchutska,114\n\nV. R. Tavolaro,114 K. Theofilatos,114 M. L. Vesterbacka Olsson,114 R. Wallny,114 D. H. Zhu,114 T. K. Aarrestad,115\n\nC. Amsler,115,yy M. F. Canelli,115 A. De Cosa,115 R. Del Burgo,115 S. Donato,115 C. Galloni,115 T. Hreus,115 B. Kilminster,115\n\nJ. Ngadiuba,115 D. Pinna,115 G. Rauco,115 P. Robmann,115 D. Salerno,115 C. Seitz,115 Y. Takahashi,115 A. Zucchetta,115\n\nV. Candelise,116 T. H. Doan,116 Sh. Jain,116 R. Khurana,116 C. M. Kuo,116 W. Lin,116 A. Pozdnyakov,116 S. S. Yu,116\n\nArun Kumar,117 P. Chang,117 Y. Chao,117 K. F. Chen,117 P. H. Chen,117 F. Fiori,117 W.-S. Hou,117 Y. Hsiung,117 Y. F. Liu,117\n\nR.-S. Lu,117 E. Paganis,117 A. Psallidas,117 A. Steen,117 J. f. Tsai,117 B. Asavapibhop,118 K. Kovitanggoon,118 G. Singh,118\n\nN. Srimanobhas,118 A. Adiguzel,119,zz F. Boran,119 S. Cerci,119,aaa S. Damarseckin,119 Z. S. Demiroglu,119 C. Dozen,119\n\nI. Dumanoglu,119 S. Girgis,119 G. Gokbulut,119 Y. Guler,119 I. Hos,119,bbb E. E. Kangal,119,ccc O. Kara,119 A. Kayis Topaksu,119\n\nU. Kiminsu,119 M. Oglakci,119 G. Onengut,119,ddd K. Ozdemir,119,eee D. Sunar Cerci,119,aaa B. Tali,119,aaa S. Turkcapar,119\n\nI. S. Zorbakir,119 C. Zorbilmez,119 B. Bilin,120 G. Karapinar,120,fff K. Ocalan,120,ggg M. Yalvac,120 M. Zeyrek,120\n\nE. Gülmez,121 M. Kaya,121,hhh O. Kaya,121,iii S. Tekten,121 E. A. Yetkin,121,jjj M. N. Agaras,122 S. Atay,122 A. Cakir,122\n\nK. Cankocak,122 B. Grynyov,123 L. Levchuk,124 P. Sorokin,124 R. Aggleton,125 F. Ball,125 L. Beck,125 J. J. Brooke,125\n\nD. Burns,125 E. Clement,125 D. Cussans,125 O. Davignon,125 H. Flacher,125 J. Goldstein,125 M. Grimes,125 G. P. Heath,125\n\nH. F. Heath,125 J. Jacob,125 L. Kreczko,125 C. Lucas,125 D. M. Newbold,125,kkk S. Paramesvaran,125 A. Poll,125 T. Sakuma,125\n\nS. Seif El Nasr-storey,125 D. Smith,125 V. J. Smith,125 K.W. Bell,126 A. Belyaev,126,lll C. Brew,126 R. M. Brown,126\n\nL. Calligaris,126 D. Cieri,126 D. J. A. Cockerill,126 J. A. Coughlan,126 K. Harder,126 S. Harper,126 E. Olaiya,126 D. Petyt,126\n\nC. H. Shepherd-Themistocleous,126 A. Thea,126 I. R. Tomalin,126 T. Williams,126 G. Auzinger,127 R. Bainbridge,127\n\nS. Breeze,127 O. Buchmuller,127 A. Bundock,127 S. Casasso,127 M. Citron,127 D. Colling,127 L. Corpe,127 P. Dauncey,127\n\nG. Davies,127 A. De Wit,127 M. Della Negra,127 R. Di Maria,127 A. Elwood,127 Y. Haddad,127 G. Hall,127 G. Iles,127\n\nT. James,127 R. Lane,127 C. Laner,127 L. Lyons,127 A.-M. Magnan,127 S. Malik,127 L. Mastrolorenzo,127 T. Matsushita,127\n\nJ. Nash,127 A. Nikitenko,127,g V. Palladino,127 M. Pesaresi,127 D. M. Raymond,127 A. Richards,127 A. Rose,127 E. Scott,127\n\nC. Seez,127 A. Shtipliyski,127 S. Summers,127 A. Tapper,127 K. Uchida,127 M. Vazquez Acosta,127,mmm T. Virdee,127,o\n\nD. Winterbottom,127 J. Wright,127 S. C. Zenz,127 J. E. Cole,128 P. R. Hobson,128 A. Khan,128 P. Kyberd,128 I. D. Reid,128\n\nP. Symonds,128 L. Teodorescu,128 M. Turner,128 A. Borzou,129 K. Call,129 J. Dittmann,129 K. Hatakeyama,129 H. Liu,129\n\nPRL 119, 221802 (2017) P HY S I CA L R EV I EW LE T T ER S\nweek ending\n\n1 DECEMBER 2017\n\n221802-10\n\n\n\nN. Pastika,129 C. Smith,129 R. Bartek,130 A. Dominguez,130 A. Buccilli,131 S. I. Cooper,131 C. Henderson,131 P. Rumerio,131\n\nC. West,131 D. Arcaro,132 A. Avetisyan,132 T. Bose,132 D. Gastler,132 D. Rankin,132 C. Richardson,132 J. Rohlf,132 L. Sulak,132\n\nD. Zou,132 G. Benelli,133 D. Cutts,133 A. Garabedian,133 J. Hakala,133 U. Heintz,133 J. M. Hogan,133 K. H. M. Kwok,133\n\nE. Laird,133 G. Landsberg,133 Z. Mao,133 M. Narain,133 J. Pazzini,133 S. Piperov,133 S. Sagir,133 R. Syarif,133 D. Yu,133\n\nR. Band,134 C. Brainerd,134 D. Burns,134 M. Calderon De La Barca Sanchez,134 M. Chertok,134 J. Conway,134 R. Conway,134\n\nP. T. Cox,134 R. Erbacher,134 C. Flores,134 G. Funk,134 M. Gardner,134 W. Ko,134 R. Lander,134 C. Mclean,134 M. Mulhearn,134\n\nD. Pellett,134 J. Pilot,134 S. Shalhout,134 M. Shi,134 J. Smith,134 M. Squires,134 D. Stolp,134 K. Tos,134 M. Tripathi,134\n\nZ. Wang,134 M. Bachtis,135 C. Bravo,135 R. Cousins,135 A. Dasgupta,135 A. Florent,135 J. Hauser,135 M. Ignatenko,135\n\nN. Mccoll,135 D. Saltzberg,135 C. Schnaible,135 V. Valuev,135 E. Bouvier,136 K. Burt,136 R. Clare,136 J. Ellison,136\n\nJ. W. Gary,136 S. M. A. Ghiasi Shirazi,136 G. Hanson,136 J. Heilman,136 P. Jandir,136 E. Kennedy,136 F. Lacroix,136\n\nO. R. Long,136 M. Olmedo Negrete,136 M. I. Paneva,136 A. Shrinivas,136 W. Si,136 L. Wang,136 H. Wei,136 S. Wimpenny,136\n\nB. R. Yates,136 J. G. Branson,137 S. Cittolin,137 M. Derdzinski,137 R. Gerosa,137 B. Hashemi,137 A. Holzner,137 D. Klein,137\n\nG. Kole,137 V. Krutelyov,137 J. Letts,137 I. Macneill,137 M. Masciovecchio,137 D. Olivito,137 S. Padhi,137 M. Pieri,137\n\nM. Sani,137 V. Sharma,137 S. Simon,137 M. Tadel,137 A. Vartak,137 S. Wasserbaech,137,nnn J. Wood,137 F. Würthwein,137\n\nA. Yagil,137 G. Zevi Della Porta,137 N. Amin,138 R. Bhandari,138 J. Bradmiller-Feld,138 C. Campagnari,138 A. Dishaw,138\n\nV. Dutta,138 M. Franco Sevilla,138 C. George,138 F. Golf,138 L. Gouskos,138 J. Gran,138 R. Heller,138 J. Incandela,138\n\nS. D. Mullin,138 A. Ovcharova,138 H. Qu,138 J. Richman,138 D. Stuart,138 I. Suarez,138 J. Yoo,138 D. Anderson,139\n\nJ. Bendavid,139 A. Bornheim,139 J. M. Lawhorn,139 H. B. Newman,139 T. Nguyen,139 C. Pena,139 M. Spiropulu,139\n\nJ. R. Vlimant,139 S. Xie,139 Z. Zhang,139 R. Y. Zhu,139 M. B. Andrews,140 T. Ferguson,140 T. Mudholkar,140 M. Paulini,140\n\nJ. Russ,140 M. Sun,140 H. Vogel,140 I. Vorobiev,140 M. Weinberg,140 J. P. Cumalat,141 W. T. Ford,141 F. Jensen,141\n\nA. Johnson,141 M. Krohn,141 S. Leontsinis,141 T. Mulholland,141 K. Stenson,141 S. R. Wagner,141 J. Alexander,142\n\nJ. Chaves,142 J. Chu,142 S. Dittmer,142 K. Mcdermott,142 N. Mirman,142 J. R. Patterson,142 A. Rinkevicius,142 A. Ryd,142\n\nL. Skinnari,142 L. Soffi,142 S. M. Tan,142 Z. Tao,142 J. Thom,142 J. Tucker,142 P. Wittich,142 M. Zientek,142 S. Abdullin,143\n\nM. Albrow,143 G. Apollinari,143 A. Apresyan,143 A. Apyan,143 S. Banerjee,143 L. A. T. Bauerdick,143 A. Beretvas,143\n\nJ. Berryhill,143 P. C. Bhat,143 G. Bolla,143 K. Burkett,143 J. N. Butler,143 A. Canepa,143 G. B. Cerati,143 H.W. K. Cheung,143\n\nF. Chlebana,143 M. Cremonesi,143 J. Duarte,143 V. D. Elvira,143 J. Freeman,143 Z. Gecse,143 E. Gottschalk,143 L. Gray,143\n\nD. Green,143 S. Grünendahl,143 O. Gutsche,143 R. M. Harris,143 S. Hasegawa,143 J. Hirschauer,143 Z. Hu,143 B. Jayatilaka,143\n\nS. Jindariani,143 M. Johnson,143 U. Joshi,143 B. Klima,143 B. Kreis,143 S. Lammel,143 D. Lincoln,143 R. Lipton,143 M. Liu,143\n\nT. Liu,143 R. Lopes De Sá,143 J. Lykken,143 K. Maeshima,143 N. Magini,143 J. M. Marraffino,143 S. Maruyama,143\n\nD. Mason,143 P. McBride,143 P. Merkel,143 S. Mrenna,143 S. Nahn,143 V. O’Dell,143 K. Pedro,143 O. Prokofyev,143\n\nG. Rakness,143 L. Ristori,143 B. Schneider,143 E. Sexton-Kennedy,143 A. Soha,143 W. J. Spalding,143 L. Spiegel,143\n\nS. Stoynev,143 J. Strait,143 N. Strobbe,143 L. Taylor,143 S. Tkaczyk,143 N. V. Tran,143 L. Uplegger,143 E. W. Vaandering,143\n\nC. Vernieri,143 M. Verzocchi,143 R. Vidal,143 M. Wang,143 H. A. Weber,143 A. Whitbeck,143 D. Acosta,144 P. Avery,144\n\nP. Bortignon,144 D. Bourilkov,144 A. Brinkerhoff,144 A. Carnes,144 M. Carver,144 D. Curry,144 R. D. Field,144 I. K. Furic,144\n\nJ. Konigsberg,144 A. Korytov,144 K. Kotov,144 P. Ma,144 K. Matchev,144 H. Mei,144 G. Mitselmakher,144 D. Rank,144\n\nD. Sperka,144 N. Terentyev,144 L. Thomas,144 J. Wang,144 S. Wang,144 J. Yelton,144 Y. R. Joshi,145 S. Linn,145 P. Markowitz,145\n\nJ. L. Rodriguez,145 A. Ackert,146 T. Adams,146 A. Askew,146 S. Hagopian,146 V. Hagopian,146 K. F. Johnson,146 T. Kolberg,146\n\nG. Martinez,146 T. Perry,146 H. Prosper,146 A. Saha,146 A. Santra,146 R. Yohay,146 M.M. Baarmand,147 V. Bhopatkar,147\n\nS. Colafranceschi,147 M. Hohlmann,147 D. Noonan,147 T. Roy,147 F. Yumiceva,147 M. R. Adams,148 L. Apanasevich,148\n\nD. Berry,148 R. R. Betts,148 R. Cavanaugh,148 X. Chen,148 O. Evdokimov,148 C. E. Gerber,148 D. A. Hangal,148\n\nD. J. Hofman,148 K. Jung,148 J. Kamin,148 I. D. Sandoval Gonzalez,148 M. B. Tonjes,148 H. Trauger,148 N. Varelas,148\n\nH. Wang,148 Z. Wu,148 J. Zhang,148 B. Bilki,149,ooo W. Clarida,149 K. Dilsiz,149,ppp S. Durgut,149 R. P. Gandrajula,149\n\nM. Haytmyradov,149 V. Khristenko,149 J.-P. Merlo,149 H. Mermerkaya,149,qqq A. Mestvirishvili,149 A. Moeller,149\n\nJ. Nachtman,149 H. Ogul,149,rrr Y. Onel,149 F. Ozok,149,sss A. Penzo,149 C. Snyder,149 E. Tiras,149 J. Wetzel,149 K. Yi,149\n\nB. Blumenfeld,150 A. Cocoros,150 N. Eminizer,150 D. Fehling,150 L. Feng,150 A. V. Gritsan,150 P. Maksimovic,150 J. Roskes,150\n\nU. Sarica,150 M. Swartz,150 M. Xiao,150 C. You,150 A. Al-bataineh,151 P. Baringer,151 A. Bean,151 S. Boren,151 J. Bowen,151\n\nJ. Castle,151 S. Khalil,151 A. Kropivnitskaya,151 D. Majumder,151 W. Mcbrayer,151 M. Murray,151 C. Royon,151 S. Sanders,151\n\nE. Schmitz,151 R. Stringer,151 J. D. Tapia Takaki,151 Q. Wang,151 A. Ivanov,152 K. Kaadze,152 Y. Maravin,152\n\nA. Mohammadi,152 L. K. Saini,152 N. Skhirtladze,152 S. Toda,152 F. Rebassoo,153 D. Wright,153 C. Anelli,154 A. Baden,154\n\nPRL 119, 221802 (2017) P HY S I CA L R EV I EW LE T T ER S\nweek ending\n\n1 DECEMBER 2017\n\n221802-11\n\n\n\nO. Baron,154 A. Belloni,154 B. Calvert,154 S. C. Eno,154 C. Ferraioli,154 N. J. Hadley,154 S. Jabeen,154 G. Y. Jeng,154\n\nR. G. Kellogg,154 J. Kunkle,154 A. C. Mignerey,154 F. Ricci-Tam,154 Y. H. Shin,154 A. Skuja,154 S. C. Tonwar,154\n\nD. Abercrombie,155 B. Allen,155 V. Azzolini,155 R. Barbieri,155 A. Baty,155 R. Bi,155 S. Brandt,155 W. Busza,155 I. A. Cali,155\n\nM. D’Alfonso,155 Z. Demiragli,155 G. Gomez Ceballos,155 M. Goncharov,155 D. Hsu,155 Y. Iiyama,155 G. M. Innocenti,155\n\nM. Klute,155 D. Kovalskyi,155 Y. S. Lai,155 Y.-J. Lee,155 A. Levin,155 P. D. Luckey,155 B. Maier,155 A. C. Marini,155\n\nC. Mcginn,155 C. Mironov,155 S. Narayanan,155 X. Niu,155 C. Paus,155 C. Roland,155 G. Roland,155 J. Salfeld-Nebgen,155\n\nG. S. F. Stephans,155 K. Tatar,155 D. Velicanu,155 J. Wang,155 T. W. Wang,155 B. Wyslouch,155 A. C. Benvenuti,156\n\nR. M. Chatterjee,156 A. Evans,156 P. Hansen,156 S. Kalafut,156 Y. Kubota,156 Z. Lesko,156 J. Mans,156 S. Nourbakhsh,156\n\nN. Ruckstuhl,156 R. Rusack,156 J. Turkewitz,156 J. G. Acosta,157 S. Oliveros,157 E. Avdeeva,158 K. Bloom,158 D. R. Claes,158\n\nC. Fangmeier,158 R. Gonzalez Suarez,158 R. Kamalieddin,158 I. Kravchenko,158 J. Monroy,158 J. E. Siado,158 G. R. Snow,158\n\nB. Stieger,158 M. Alyari,159 J. Dolen,159 A. Godshalk,159 C. Harrington,159 I. Iashvili,159 D. Nguyen,159 A. Parker,159\n\nS. Rappoccio,159 B. Roozbahani,159 G. Alverson,160 E. Barberis,160 A. Hortiangtham,160 A. Massironi,160 D. M. Morse,160\n\nD. Nash,160 T. Orimoto,160 R. Teixeira De Lima,160 D. Trocino,160 D. Wood,160 S. Bhattacharya,161 O. Charaf,161\n\nK. A. Hahn,161 N. Mucia,161 N. Odell,161 B. Pollack,161 M. H. Schmitt,161 K. Sung,161 M. Trovato,161 M. Velasco,161\n\nN. Dev,162 M. Hildreth,162 K. Hurtado Anampa,162 C. Jessop,162 D. J. Karmgard,162 N. Kellams,162 K. Lannon,162\n\nN. Loukas,162 N. Marinelli,162 F. Meng,162 C. Mueller,162 Y. Musienko,162,kk M. Planer,162 A. Reinsvold,162 R. Ruchti,162\n\nG. Smith,162 S. Taroni,162 M. Wayne,162 M. Wolf,162 A. Woodard,162 J. Alimena,163 L. Antonelli,163 B. Bylsma,163\n\nL. S. Durkin,163 S. Flowers,163 B. Francis,163 A. Hart,163 C. Hill,163 W. Ji,163 B. Liu,163 W. Luo,163 D. Puigh,163\n\nB. L. Winer,163 H.W. Wulsin,163 A. Benaglia,164 S. Cooperstein,164 O. Driga,164 P. Elmer,164 J. Hardenbrook,164 P. Hebda,164\n\nS. Higginbotham,164 D. Lange,164 J. Luo,164 D. Marlow,164 K. Mei,164 I. Ojalvo,164 J. Olsen,164 C. Palmer,164 P. Piroué,164\n\nD. Stickland,164 C. Tully,164 S. Malik,165 S. Norberg,165 A. Barker,166 V. E. Barnes,166 S. Das,166 S. Folgueras,166 L. Gutay,166\n\nM. K. Jha,166 M. Jones,166 A.W. Jung,166 A. Khatiwada,166 D. H. Miller,166 N. Neumeister,166 C. C. Peng,166 J. F. Schulte,166\n\nJ. Sun,166 F. Wang,166 W. Xie,166 T. Cheng,167 N. Parashar,167 J. Stupak,167 A. Adair,168 B. Akgun,168 Z. Chen,168\n\nK. M. Ecklund,168 F. J. M. Geurts,168 M. Guilbaud,168 W. Li,168 B. Michlin,168 M. Northup,168 B. P. Padley,168 J. Roberts,168\n\nJ. Rorie,168 Z. Tu,168 J. Zabel,168 A. Bodek,169 P. de Barbaro,169 R. Demina,169 Y. t. Duh,169 T. Ferbel,169 M. Galanti,169\n\nA. Garcia-Bellido,169 J. Han,169 O. Hindrichs,169 A. Khukhunaishvili,169 K. H. Lo,169 P. Tan,169 M. Verzetti,169\n\nR. Ciesielski,170 K. Goulianos,170 C. Mesropian,170 A. Agapitos,171 J. P. Chou,171 M. Christos,171 K. Feigelis,171\n\nY. Gershtein,171 T. A. Gómez Espinosa,171 E. Halkiadakis,171 M. Heindl,171 E. Hughes,171 S. Kaplan,171\n\nR. Kunnawalkam Elayavalli,171 S. Kyriacou,171 A. Lath,171 R. Montalvo,171 K. Nash,171 M. Osherson,171 H. Saka,171\n\nS. Salur,171 S. Schnetzer,171 D. Sheffield,171 S. Somalwar,171 R. Stone,171 S. Thomas,171 P. Thomassen,171 M. Walker,171\n\nB. Zhou,171 A. G. Delannoy,172 M. Foerster,172 J. Heideman,172 G. Riley,172 K. Rose,172 S. Spanier,172 K. Thapa,172\n\nO. Bouhali,173,ttt A. Castaneda Hernandez,173,ttt A. Celik,173 M. Dalchenko,173 M. De Mattia,173 A. Delgado,173 S. Dildick,173\n\nR. Eusebi,173 J. Gilmore,173 T. Huang,173 T. Kamon,173,uuu R. Mueller,173 Y. Pakhotin,173 R. Patel,173 A. Perloff,173\n\nL. Perniè,173 D. Rathjens,173 A. Safonov,173 A. Tatarinov,173 K. A. Ulmer,173 N. Akchurin,174 J. Damgov,174 F. De Guio,174\n\nP. R. Dudero,174 J. Faulkner,174 E. Gurpinar,174 S. Kunori,174 K. Lamichhane,174 S.W. Lee,174 T. Libeiro,174 T. Peltola,174\n\nS. Undleeb,174 I. Volobouev,174 Z. Wang,174 S. Greene,175 A. Gurrola,175 R. Janjam,175 W. Johns,175 C. Maguire,175\n\nA. Melo,175 H. Ni,175 P. Sheldon,175 S. Tuo,175 J. Velkovska,175 Q. Xu,175 M.W. Arenton,176 P. Barria,176 B. Cox,176\n\nR. Hirosky,176 A. Ledovskoy,176 H. Li,176 C. Neu,176 T. Sinthuprasith,176 X. Sun,176 Y. Wang,176 E. Wolfe,176 F. Xia,176\n\nR. Harr,177 P. E. Karchin,177 J. Sturdy,177 S. Zaleski,177 M. Brodski,178 J. Buchanan,178 C. Caillol,178 S. Dasu,178 L. Dodd,178\n\nS. Duric,178 B. Gomber,178 M. Grothe,178 M. Herndon,178 A. Hervé,178 U. Hussain,178 P. Klabbers,178 A. Lanaro,178\n\nA. Levine,178 K. Long,178 R. Loveless,178 G. A. Pierro,178 G. Polese,178 T. Ruggles,178 A. Savin,178 N. Smith,178\n\nW. H. Smith,178 D. Taylor,178 and N. Woods178\n\n(CMS Collaboration)\n\n1Yerevan Physics Institute, Yerevan, Armenia\n2Institut für Hochenergiephysik, Wien, Austria\n\n3Institute for Nuclear Problems, Minsk, Belarus\n4Universiteit Antwerpen, Antwerpen, Belgium\n\nPRL 119, 221802 (2017) P HY S I CA L R EV I EW LE T T ER S\nweek ending\n\n1 DECEMBER 2017\n\n221802-12\n\n\n\n5Vrije Universiteit Brussel, Brussel, Belgium\n6Université Libre de Bruxelles, Bruxelles, Belgium\n\n7Ghent University, Ghent, Belgium\n8Université Catholique de Louvain, Louvain-la-Neuve, Belgium\n\n9Université de Mons, Mons, Belgium\n10Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil\n\n11Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil\n12Universidade Estadual Paulista, Universidade Federal do ABC, São Paulo, Brazil\n\n12aUniversidade Estadual Paulista\n12bUniversidade Federal do ABC\n\n13Institute for Nuclear Research and Nuclear Energy of Bulgaria Academy of Sciences\n14University of Sofia, Sofia, Bulgaria\n15Beihang University, Beijing, China\n\n16Institute of High Energy Physics, Beijing, China\n17State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China\n\n18Universidad de Los Andes, Bogota, Colombia\n19University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, Croatia\n\n20University of Split, Faculty of Science, Split, Croatia\n21Institute Rudjer Boskovic, Zagreb, Croatia\n\n22University of Cyprus, Nicosia, Cyprus\n23Charles University, Prague, Czech Republic\n\n24Universidad San Francisco de Quito, Quito, Ecuador\n25Academy of Scientific Research and Technology of the Arab Republic of Egypt,\n\nEgyptian Network of High Energy Physics, Cairo, Egypt\n26National Institute of Chemical Physics and Biophysics, Tallinn, Estonia\n\n27Department of Physics, University of Helsinki, Helsinki, Finland\n28Helsinki Institute of Physics, Helsinki, Finland\n\n29Lappeenranta University of Technology, Lappeenranta, Finland\n30IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France\n\n31Laboratoire Leprince-Ringuet, Ecole polytechnique, CNRS/IN2P3, Université Paris-Saclay, Palaiseau, France\n32Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg, France\n\n33Centre de Calcul de l’Institut National de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne, France\n34Université de Lyon, Université Claude Bernard Lyon 1, CNRS-IN2P3, Institut de Physique Nucléaire de Lyon, Villeurbanne, France\n\n35Georgian Technical University, Tbilisi, Georgia\n36Tbilisi State University, Tbilisi, Georgia\n\n37RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany\n38RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany\n39RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany\n\n40Deutsches Elektronen-Synchrotron, Hamburg, Germany\n41University of Hamburg, Hamburg, Germany\n\n42Institut für Experimentelle Kernphysik, Karlsruhe, Germany\n43Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece\n\n44National and Kapodistrian University of Athens, Athens, Greece\n45University of Ioánnina, Ioánnina, Greece\n\n46MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University, Budapest, Hungary\n47Wigner Research Centre for Physics, Budapest, Hungary\n\n48Institute of Nuclear Research ATOMKI, Debrecen, Hungary\n49Institute of Physics, University of Debrecen, Debrecen, Hungary\n\n50Indian Institute of Science (IISc), Bangalore, India\n51National Institute of Science Education and Research, Bhubaneswar, India\n\n52Panjab University, Chandigarh, India\n53University of Delhi, Delhi, India\n\n54Saha Institute of Nuclear Physics, HBNI, Kolkata,India\n55Indian Institute of Technology Madras, Madras, India\n\n56Bhabha Atomic Research Centre, Mumbai, India\n57Tata Institute of Fundamental Research-A, Mumbai, India\n58Tata Institute of Fundamental Research-B, Mumbai, India\n\n59Indian Institute of Science Education and Research (IISER), Pune, India\n60Institute for Research in Fundamental Sciences (IPM), Tehran, Iran\n\n61University College Dublin, Dublin, Ireland\n\nPRL 119, 221802 (2017) P HY S I CA L R EV I EW LE T T ER S\nweek ending\n\n1 DECEMBER 2017\n\n221802-13\n\n\n\n62INFN Sezione di Bari, Università di Bari, Politecnico di Bari, Bari, Italy\n62aINFN Sezione di Bari\n\n62bUniversità di Bari\n62cPolitecnico di Bari\n\n63INFN Sezione di Bologna, Università di Bologna, Bologna, Italy\n63aINFN Sezione di Bologna\n\n63bUniversità di Bologna\n64INFN Sezione di Catania, Università di Catania, Catania, Italy\n\n64aINFN Sezione di Catania\n64bUniversità di Catania\n\n65INFN Sezione di Firenze, Università di Firenze, Firenze, Italy\n65aINFN Sezione di Firenze\n\n65bUniversità di Firenze\n66INFN Laboratori Nazionali di Frascati, Frascati, Italy\n\n67INFN Sezione di Genova, Università di Genova, Genova, Italy\n67aINFN Sezione di Genova\n\n67bUniversità di Genova\n68aINFN Sezione di Milano-Bicocca\n\n68bUniversità di Milano-Bicocca\n69INFN Sezione di Napoli, Università di Napoli ’Federico II’, Napoli, Italy, Università della Basilicata,\n\nPotenza, Italy, Università G. Marconi, Roma, Italy\n69aINFN Sezione di Napoli\n\n69bUniversità di Napoli ’Federico II’\n69cUniversità della Basilicata\n\n69dUniversità G. Marconi\n70INFN Sezione di Padova, Università di Padova, Padova, Italy, Università di Trento, Trento, Italy\n\n70aINFN Sezione di Padova\n70bUniversità di Padova\n70cUniversità di Trento\n\n71INFN Sezione di Pavia, Università di Pavia, Pavia, Italy\n71aINFN Sezione di Pavia\n\n71bUniversità di Pavia\n72INFN Sezione di Perugia, Università di Perugia, Perugia, Italy\n\n72aINFN Sezione di Perugia\n72bUniversità di Perugia\n\n73INFN Sezione di Pisa, Università di Pisa, Scuola Normale Superiore di Pisa, Pisa, Italy\n73aINFN Sezione di Pisa\n\n73bUniversità di Pisa\n73cScuola Normale Superiore di Pisa\n\n74aINFN Sezione di Roma\n74bSapienza Università di Roma\n\n75INFN Sezione di Torino, Università di Torino, Torino, Italy, Università del Piemonte Orientale, Novara, Italy\n75aINFN Sezione di Torino\n\n75bUniversità di Torino\n75cUniversità del Piemonte Orientale\n\n76INFN Sezione di Trieste, Università di Trieste, Trieste, Italy\n76aINFN Sezione di Trieste\n\n76bUniversità di Trieste\n77Kyungpook National University, Daegu, Korea\n78Chonbuk National University, Jeonju, Korea\n\n79Chonnam National University, Institute for Universe and Elementary Particles, Kwangju, Korea\n80Hanyang University, Seoul, Korea\n81Korea University, Seoul, Korea\n\n82Seoul National University, Seoul, Korea\n83University of Seoul, Seoul, Korea\n\n84Sungkyunkwan University, Suwon, Korea\n85Vilnius University, Vilnius, Lithuania\n\n86National Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia\n87Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico\n\n88Universidad Iberoamericana, Mexico City, Mexico\n\nPRL 119, 221802 (2017) P HY S I CA L R EV I EW LE T T ER S\nweek ending\n\n1 DECEMBER 2017\n\n221802-14\n\n\n\n89Benemerita Universidad Autonoma de Puebla, Puebla, Mexico\n90Universidad Autónoma de San Luis Potosí, San Luis Potosí, Mexico\n\n91University of Auckland, Auckland, New Zealand\n92University of Canterbury, Christchurch, New Zealand\n\n93National Centre for Physics, Quaid-I-Azam University, Islamabad, Pakistan\n94National Centre for Nuclear Research, Swierk, Poland\n\n95Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Warsaw, Poland\n96Laboratório de Instrumentação e Física Experimental de Partículas, Lisboa, Portugal\n\n97Joint Institute for Nuclear Research, Dubna, Russia\n98Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia\n\n99Institute for Nuclear Research, Moscow, Russia\n100Institute for Theoretical and Experimental Physics, Moscow, Russia\n\n101Moscow Institute of Physics and Technology, Moscow, Russia\n102National Research Nuclear University ’Moscow Engineering Physics Institute’ (MEPhI), Moscow, Russia\n\n103P.N. Lebedev Physical Institute, Moscow, Russia\n104Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia\n\n105Novosibirsk State University (NSU), Novosibirsk, Russia\n106State Research Center of Russian Federation, Institute for High Energy Physics, Protvino, Russia\n\n107University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia\n108Centro de Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain\n\n109Universidad Autónoma de Madrid, Madrid, Spain\n110Universidad de Oviedo, Oviedo, Spain\n\n111Instituto de Física de Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain\n112CERN, European Organization for Nuclear Research, Geneva, Switzerland\n\n113Paul Scherrer Institut, Villigen, Switzerland\n114Institute for Particle Physics, ETH Zurich, Zurich, Switzerland\n\n115Universität Zürich, Zurich, Switzerland\n116National Central University, Chung-Li, Taiwan\n\n117National Taiwan University (NTU), Taipei, Taiwan\n118Chulalongkorn University, Faculty of Science, Department of Physics, Bangkok, Thailand\n\n119Çukurova University, Physics Department, Science and Art Faculty, Adana, Turkey\n120Middle East Technical University, Physics Department, Ankara, Turkey\n\n121Bogazici University, Istanbul, Turkey\n122Istanbul Technical University, Istanbul, Turkey\n\n123Institute for Scintillation Materials of National Academy of Science of Ukraine, Kharkov, Ukraine\n124National Scientific Center, Kharkov Institute of Physics and Technology, Kharkov, Ukraine\n\n125University of Bristol, Bristol, United Kingdom\n126Rutherford Appleton Laboratory, Didcot, United Kingdom\n\n127Imperial College, London, United Kingdom\n128Brunel University, Uxbridge, United Kingdom\n\n129Baylor University, Waco, USA\n130Catholic University of America, Washington DC, USA\n\n131The University of Alabama, Tuscaloosa, USA\n132Boston University, Boston, USA\n\n133Brown University, Providence, USA\n134University of California, Davis, Davis, USA\n135University of California, Los Angeles, USA\n\n136University of California, Riverside, Riverside, USA\n137University of California, San Diego, La Jolla, USA\n\n138University of California, Santa Barbara—Department of Physics, Santa Barbara, USA\n139California Institute of Technology, Pasadena, USA\n\n140Carnegie Mellon University, Pittsburgh, USA\n141University of Colorado Boulder, Boulder, USA\n\n142Cornell University, Ithaca, USA\n143Fermi National Accelerator Laboratory, Batavia, USA\n\n144University of Florida, Gainesville, USA\n145Florida International University, Miami, USA\n146Florida State University, Tallahassee, USA\n\n147Florida Institute of Technology, Melbourne, USA\n148University of Illinois at Chicago (UIC), Chicago, USA\n\nPRL 119, 221802 (2017) P HY S I CA L R EV I EW LE T T ER S\nweek ending\n\n1 DECEMBER 2017\n\n221802-15\n\n\n\n149The University of Iowa, Iowa City, USA\n150Johns Hopkins University, Baltimore, USA\n151The University of Kansas, Lawrence, USA\n152Kansas State University, Manhattan, USA\n\n153Lawrence Livermore National Laboratory, Livermore, USA\n154University of Maryland, College Park, USA\n\n155Massachusetts Institute of Technology, Cambridge, USA\n156University of Minnesota, Minneapolis, USA\n\n157University of Mississippi, Oxford, USA\n158University of Nebraska-Lincoln, Lincoln, USA\n\n159State University of New York at Buffalo, Buffalo, USA\n160Northeastern University, Boston, USA\n\n161Northwestern University, Evanston, USA\n162University of Notre Dame, Notre Dame, USA\n163The Ohio State University, Columbus, USA\n\n164Princeton University, Princeton, USA\n165University of Puerto Rico, Mayaguez, USA\n166Purdue University, West Lafayette, USA\n\n167Purdue University Northwest, Hammond, USA\n168Rice University, Houston, USA\n\n169University of Rochester, Rochester, USA\n170The Rockefeller University, New York, USA\n\n171Rutgers, The State University of New Jersey, Piscataway, USA\n172University of Tennessee, Knoxville, USA\n\n173Texas A&M University, College Station, USA\n174Texas Tech University, Lubbock, USA\n175Vanderbilt University, Nashville, USA\n\n176University of Virginia, Charlottesville, USA\n177Wayne State University, Detroit, USA\n\n178University of Wisconsin—Madison, Madison, WI, USA\n\naDeceased.\nbAlso at Vienna University of Technology, Vienna, Austria\ncAlso at State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China\ndAlso at Universidade Estadual de Campinas, Campinas, Brazil\neAlso at Universidade Federal de Pelotas, Pelotas, Brazil\nfAlso at Université Libre de Bruxelles, Bruxelles, Belgium\ngAlso at Institute for Theoretical and Experimental Physics, Moscow, Russia\nhAlso at Joint Institute for Nuclear Research, Dubna, Russia\niAlso at Ain Shams University, Cairo, Egypt\njAlso at British University in Egypt, Cairo, Egypt\nkAlso at Cairo University, Cairo, Egypt\nlAlso at Université de Haute Alsace, Mulhouse, France\nmAlso at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia\nnAlso at Tbilisi State University, Tbilisi, Georgia\noAlso at CERN, European Organization for Nuclear Research, Geneva, Switzerland\npAlso at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany\nqAlso at University of Hamburg, Hamburg, Germany\nrAlso at Brandenburg University of Technology, Cottbus, Germany\nsAlso at Institute of Nuclear Research ATOMKI, Debrecen, Hungary\ntAlso at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University, Budapest, Hungary\nuAlso at Institute of Physics, University of Debrecen, Debrecen, Hungary\nvAlso at IIT Bhubaneswar, Bhubaneswar, India\nwAlso at Institute of Physics, Bhubaneswar, India\nxAlso at University of Visva-Bharati, Santiniketan, India\nyAlso at University of Ruhuna, Matara, Sri Lanka\nzAlso at Isfahan University of Technology, Isfahan, Iran\naaAlso at Yazd University, Yazd, Iran\nbbAlso at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran\nccAlso at Università degli Studi di Siena, Siena, Italy\n\nPRL 119, 221802 (2017) P HY S I CA L R EV I EW LE T T ER S\nweek ending\n\n1 DECEMBER 2017\n\n221802-16\n\n\n\nddAlso at INFN Sezione di Milano-Bicocca, Università di Milano-Bicocca, Milano, Italy\neeAlso at Purdue University, West Lafayette, USA\nffAlso at International Islamic University of Malaysia, Kuala Lumpur, Malaysia\nggAlso at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia\nhhAlso at Consejo Nacional de Ciencia y Tecnología, Mexico city, Mexico\niiAlso at Warsaw University of Technology, Institute of Electronic Systems, Warsaw, Poland\njjAlso at Czech Technical University, Praha, Czech Republic\nkkAlso at Institute for Nuclear Research, Moscow, Russia\nllAlso at National Research Nuclear University ’Moscow Engineering Physics Institute’ (MEPhI), Moscow, Russia\n\nmmAlso at St. Petersburg State Polytechnical University, St. Petersburg, Russia\nnnAlso at University of Florida, Gainesville, USA\nooAlso at P.N. Lebedev Physical Institute, Moscow, Russia\nppAlso at California Institute of Technology, Pasadena, USA\nqqAlso at Budker Institute of Nuclear Physics, Novosibirsk, Russia\nrrAlso at Faculty of Physics, University of Belgrade, Belgrade, Serbia\nssAlso at INFN Sezione di Roma, Sapienza Università di Roma, Rome, Italy\nttAlso at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia\nuuAlso at Scuola Normale e Sezione dell’INFN, Pisa, Italy\nvvAlso at National and Kapodistrian University of Athens, Athens, Greece\nwwAlso at Riga Technical University, Riga, Latvia\nxxAlso at Universität Zürich, Zurich, Switzerland\nyyAlso at Stefan Meyer Institute for Subatomic Physics\nzzAlso at Istanbul University, Faculty of Science, Istanbul, Turkey\naaaAlso at Adiyaman University, Adiyaman, Turkey\nbbbAlso at Istanbul Aydin University, Istanbul, Turkey\ncccAlso at Mersin University, Mersin, Turkey\ndddAlso at Cag University, Mersin, Turkey\neeeAlso at Piri Reis University, Istanbul, Turkey\nfffAlso at Izmir Institute of Technology, Izmir, Turkey\n\ngggAlso at Necmettin Erbakan University, Konya, Turkey\nhhhAlso at Marmara University, Istanbul, Turkey\niiiAlso at Kafkas University, Kars, Turkey\njjjAlso at Istanbul Bilgi University, Istanbul, Turkey\n\nkkkAlso at Rutherford Appleton Laboratory, Didcot, United Kingdom\nlllAlso at School of Physics and Astronomy, University of Southampton, Southampton, United Kingdom\n\nmmmAlso at Instituto de Astrofísica de Canarias, La Laguna, Spain\nnnnAlso at Utah Valley University, Orem, USA\noooAlso at Beykent University\npppAlso at Bingol University, Bingol, Turkey\nqqqAlso at Erzincan University, Erzincan, Turkey\nrrrAlso at Sinop University, Sinop, Turkey\nsssAlso at Mimar Sinan University, Istanbul, Istanbul, Turkey\ntttAlso at Texas A&M University at Qatar, Doha, Qatar\n\nuuuAlso at Kyungpook National University, Daegu, Korea\n\nPRL 119, 221802 (2017) P HY S I CA L R EV I EW LE T T ER S\nweek ending\n\n1 DECEMBER 2017\n\n221802-17"},"fulltext":true,"key":"f4fb13085d07491a4ed20dbf22bf4945","url":"https://inspirehep.net/files/f4fb13085d07491a4ed20dbf22bf4945"}],"authors":[{"raw_affiliations":[{"value":"Yerevan Physics Institute , Yerevan, Armenia"}],"full_name_unicode_normalized":"sirunyan, albert m","full_name":"Sirunyan, Albert M","record":{"$ref":"https://inspirehep.net/api/authors/1064002"},"last_name":"Sirunyan","ids":[{"schema":"INSPIRE ID","value":"INSPIRE-00312131"},{"schema":"INSPIRE BAI","value":"A.M.Sirunyan.1"}],"affiliations":[{"record":{"$ref":"https://inspirehep.net/api/institutions/903361"},"value":"Yerevan Phys. 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$\\LT+\\ptmiss$ distribution for events with three leptons and one OSSF pair with mass above-\\Z (\\cmsLeft) and the $\\LT+\\ptmiss$ distribution for events with four or more leptons and one OSSF pair (\\cmsRight). The total SM background is shown as a stacked histogram of all contributing processes. The predictions for signal models (sum of all production and decay modes) with $m_{\\PgS} = 700\\GeV$ (solid line) and $m_{\\PgS} = 380\\GeV$ (dashed line) are also shown. The lower panels show the ratio of observed to expected events. The hatched gray band in the upper panel, and the dark and light gray bands in the lower panel represent the total, statistical, and systematic uncertainties in the expected background, respectively.","source":"arxiv","key":"c416eade17f8eff925b7800c47e90107","url":"https://inspirehep.net/files/c416eade17f8eff925b7800c47e90107"},{"filename":"Figure_001-b.png","caption":"The $\\LT+\\ptmiss$ distribution for events with three leptons and one OSSF pair with mass above-\\Z (\\cmsLeft) and the $\\LT+\\ptmiss$ distribution for events with four or more leptons and one OSSF pair (\\cmsRight). The total SM background is shown as a stacked histogram of all contributing processes. The predictions for signal models (sum of all production and decay modes) with $m_{\\PgS} = 700\\GeV$ (solid line) and $m_{\\PgS} = 380\\GeV$ (dashed line) are also shown. The lower panels show the ratio of observed to expected events. The hatched gray band in the upper panel, and the dark and light gray bands in the lower panel represent the total, statistical, and systematic uncertainties in the expected background, respectively.","source":"arxiv","key":"8ec35c630a921cb7b4fc29d35d9c5875","url":"https://inspirehep.net/files/8ec35c630a921cb7b4fc29d35d9c5875"},{"filename":"Figure_002.png","caption":"The 95\\% confidence level upper limits on the cross section for production of heavy fermion pairs ($\\PgSz \\PgSp$, $\\PgSz \\PgSm$, and $\\PgSp \\PgSm$). Also shown is the theoretical prediction for the cross section of the \\PgS{} pair production via the type III seesaw mechanism, with its uncertainty. In the flavor-democratic scenario ($B_\\Pe=B_\\Pgm=B_\\Pgt$), heavy fermion pair production is excluded for masses below  840\\GeV.","source":"arxiv","key":"16c4ce585507520ff7f8a195f9cc62d7","url":"https://inspirehep.net/files/16c4ce585507520ff7f8a195f9cc62d7"},{"filename":"Figure_003-a.png","caption":"The 95\\% confidence level expected (\\cmsLeft) and observed (\\cmsRight) limits on the heavy fermion mass ${m_\\PgS}$ (\\GeV) for each combination of branching fractions to the individual lepton flavors. The color scale represents the mass exclusion limit obtained at each point. The branching fraction to $\\Pgm$ can be obtained from $B_{\\Pgm}=1-[B_{\\Pe} + B_{\\Pgt}]$. The highlighted box indicates the limit on $m_{\\PgS}$ for the flavor-democratic scenario ($B_\\Pe=B_\\Pgm=B_\\Pgt$).","source":"arxiv","key":"3e8becfafa0f071da0cf6e49a5782586","url":"https://inspirehep.net/files/3e8becfafa0f071da0cf6e49a5782586"},{"filename":"Figure_003-b.png","caption":"The 95\\% confidence level expected (\\cmsLeft) and observed (\\cmsRight) limits on the heavy fermion mass ${m_\\PgS}$ (\\GeV) for each combination of branching fractions to the individual lepton flavors. The color scale represents the mass exclusion limit obtained at each point. The branching fraction to $\\Pgm$ can be obtained from $B_{\\Pgm}=1-[B_{\\Pe} + B_{\\Pgt}]$. The highlighted box indicates the limit on $m_{\\PgS}$ for the flavor-democratic scenario ($B_\\Pe=B_\\Pgm=B_\\Pgt$).","source":"arxiv","key":"e054369054c20fdb8f7a4be228a77ccc","url":"https://inspirehep.net/files/e054369054c20fdb8f7a4be228a77ccc"}],"accelerator_experiments":[{"legacy_name":"CERN-LHC-CMS","record":{"$ref":"https://inspirehep.net/api/experiments/1108642"}}],"urls":[{"description":"Open Access fulltext","value":"https://lss.fnal.gov/archive/openaccess/10.1103_PhysRevLett.119.221802.pdf"}],"first_author":{"full_name":"Sirunyan, Albert M","last_name":"Sirunyan","ids":[{"schema":"INSPIRE ID","value":"INSPIRE-00312131"},{"schema":"INSPIRE BAI","value":"A.M.Sirunyan.1"}],"first_name":"Albert M","recid":1064002},"control_number":1620205,"dois":[{"value":"10.1103/PhysRevLett.119.221802"}],"document_type":["article"],"texkeys":["CMS:2017ybg","Sirunyan:2017qkz"],"abstracts":[{"source":"APS","value":"A search for a signal consistent with the type-III seesaw mechanism in events with three or more electrons or muons is presented. The data sample consists of proton-proton collisions at s=13  TeV collected by the CMS experiment at the LHC in 2016 and corresponds to an integrated luminosity of 35.9  fb−1. Selection criteria based on the number of leptons and the invariant mass of oppositely charged lepton pairs are used to distinguish the signal from the standard model background. The observations are consistent with the expectations from standard model processes. The results are used to place limits on the production of heavy fermions of the type-III seesaw model as a function of the branching ratio to each lepton flavor. In the scenario of equal branching fractions to each lepton flavor, heavy fermions with masses below 840 GeV are excluded. This is the most sensitive probe to date of the type-III seesaw mechanism.","abstract_source_suggest":{"input":"APS"}},{"source":"arXiv","value":"A search for a signal consistent with the type-III seesaw mechanism in events with three or more electrons or muons is presented. The data sample consists of proton-proton collisions at sqrt(s) = 13 TeV collected by the CMS experiment at the LHC in 2016 and corresponds to an integrated luminosity of 35.9 inverse femtobarns. Selection criteria based on the number of leptons and the invariant mass of opposite-sign lepton pairs are used to distinguish the signal from the standard model background. The observations are consistent with the expectations from standard model processes. The results are used to place limits on the production of heavy fermions of the type-III seesaw model as a function of the branching ratio to each lepton flavor. In the scenario of equal branching fractions to each lepton flavor, heavy fermions with masses below 840 GeV are excluded. 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\\mtb distributions from the leptonic analysis in the 1 b tag (upper) and 2 b tag (lower) categories, for the electron (left) and muon (right) channels. The ``LF'' and ``HF'' notations indicate the light- and heavy-flavor components of the W+jets contribution, respectively. The simulated $\\PWRpr$ signal and background samples are normalized to the integrated luminosity of the analyzed data set. The distributions are shown after the application of all selections. The 68\\% uncertainty in the background estimate includes all contributions to the predicted background, while the total uncertainty is the combined uncertainty of the background and data.","source":"arxiv","key":"70e356e2555f4060d4027fd9883999c8","url":"https://inspirehep.net/files/70e356e2555f4060d4027fd9883999c8"},{"filename":"Figure_001-b.png","caption":"Reconstructed \\mtb distributions from the leptonic analysis in the 1 b tag (upper) and 2 b tag (lower) categories, for the electron (left) and muon (right) channels. The ``LF'' and ``HF'' notations indicate the light- and heavy-flavor components of the W+jets contribution, respectively. The simulated $\\PWRpr$ signal and background samples are normalized to the integrated luminosity of the analyzed data set. The distributions are shown after the application of all selections. The 68\\% uncertainty in the background estimate includes all contributions to the predicted background, while the total uncertainty is the combined uncertainty of the background and data.","source":"arxiv","key":"a53cf646e1a93dc1164b1d7535ce269c","url":"https://inspirehep.net/files/a53cf646e1a93dc1164b1d7535ce269c"},{"filename":"Figure_001-c.png","caption":"Reconstructed \\mtb distributions from the leptonic analysis in the 1 b tag (upper) and 2 b tag (lower) categories, for the electron (left) and muon (right) channels. The ``LF'' and ``HF'' notations indicate the light- and heavy-flavor components of the W+jets contribution, respectively. The simulated $\\PWRpr$ signal and background samples are normalized to the integrated luminosity of the analyzed data set. The distributions are shown after the application of all selections. The 68\\% uncertainty in the background estimate includes all contributions to the predicted background, while the total uncertainty is the combined uncertainty of the background and data.","source":"arxiv","key":"c9fa3163f136900e371e8284e7a02b87","url":"https://inspirehep.net/files/c9fa3163f136900e371e8284e7a02b87"},{"filename":"Figure_001-d.png","caption":"Reconstructed \\mtb distributions from the leptonic analysis in the 1 b tag (upper) and 2 b tag (lower) categories, for the electron (left) and muon (right) channels. The ``LF'' and ``HF'' notations indicate the light- and heavy-flavor components of the W+jets contribution, respectively. The simulated $\\PWRpr$ signal and background samples are normalized to the integrated luminosity of the analyzed data set. The distributions are shown after the application of all selections. The 68\\% uncertainty in the background estimate includes all contributions to the predicted background, while the total uncertainty is the combined uncertainty of the background and data.","source":"arxiv","key":"6837f8311d62830dc2d470779c860ba9","url":"https://inspirehep.net/files/6837f8311d62830dc2d470779c860ba9"},{"filename":"Figure_002.png","caption":"Reconstructed \\mtb distribution from the hadronic analysis. The simulated $\\PWRpr$ signal and backgrounds are normalized to the integrated luminosity of the analyzed data set. The distribution is shown after the application of all selections. The 68\\% uncertainty in the background estimate includes all contributions to the predicted background, while the total uncertainty is the combined uncertainty of the background and data.","source":"arxiv","key":"2aec8af3523c0da3526e78ca96692ed6","url":"https://inspirehep.net/files/2aec8af3523c0da3526e78ca96692ed6"},{"filename":"Figure_003-a.png","caption":"The 95\\% CL upper limit on the $\\PWRpr$ boson production cross section, separately for the leptonic (left) and hadronic (right) analyses. Masses for which the theoretical cross section is above the observed upper limit are excluded at 95\\% CL.","source":"arxiv","key":"dbe3c3bfe2151ed656e04cb04aef07b4","url":"https://inspirehep.net/files/dbe3c3bfe2151ed656e04cb04aef07b4"},{"filename":"Figure_003-b.png","caption":"The 95\\% CL upper limit on the $\\PWRpr$ boson production cross section, separately for the leptonic (left) and hadronic (right) analyses. Masses for which the theoretical cross section is above the observed upper limit are excluded at 95\\% CL.","source":"arxiv","key":"7b657553004c7280f70efb8880c0bdc5","url":"https://inspirehep.net/files/7b657553004c7280f70efb8880c0bdc5"},{"filename":"Figure_004.png","caption":"The 95\\% CL upper limit on the $\\PWRpr$ boson production cross section for the combined leptonic and hadronic analyses. Masses for which the theoretical cross section is above the observed upper limit are excluded at 95\\% CL.","source":"arxiv","key":"887ef92f05d881b01026c333fcce95d6","url":"https://inspirehep.net/files/887ef92f05d881b01026c333fcce95d6"}],"accelerator_experiments":[{"legacy_name":"CERN-LHC-CMS","record":{"$ref":"https://inspirehep.net/api/experiments/1108642"}}],"urls":[{"description":"Figures, tables and other information","value":"http://cms-results.web.cern.ch/cms-results/public-results/publications/B2G-16-016"}],"first_author":{"affiliations_identifiers":[{"schema":"GRID","value":"grid.48507.3e"},{"schema":"ROR","value":"https://ror.org/00ad27c73"}],"full_name":"Sirunyan, Albert M","ids":[{"schema":"INSPIRE ID","value":"INSPIRE-00312131"},{"schema":"INSPIRE BAI","value":"A.M.Sirunyan.1"}],"last_name":"Sirunyan","first_name":"Albert M","recid":1064002},"control_number":1605124,"dois":[{"value":"10.1007/JHEP08(2017)029"}],"document_type":["article"],"texkeys":["CMS:2017avb","Sirunyan:2017ukk"],"abstracts":[{"source":"Springer","value":"Searches are presented for heavy gauge bosons decaying into a top and a bottom quark in data collected by the CMS experiment at $ \\sqrt{s}=13 $ TeV that correspond to an integrated luminosity of 2.2 and 2.6 fb$^{−1}$ in the leptonic and hadronic analyses, respectively. Two final states are analyzed, one containing a single electron, or muon, and missing transverse momentum, and the other containing multiple jets and no electrons or muons. No evidence is found for a right-handed W′ boson (W′$_{R}$) and the combined analyses exclude at 95% confidence level W′$_{R}$ with masses below 2.4 TeV if $ {M}_{\\mathrm{W}{\\prime}_{\\mathrm{R}}}\\gg {M}_{\\nu_{\\mathrm{R}}} $ (mass of the right-handed neutrino), and below 2.6 TeV if $ {M}_{\\mathrm{W}{\\prime}_{\\mathrm{R}}}<{M}_{\\nu_{\\mathrm{R}}} $ . The results provide the most stringent limits for right-handed W′ bosons in the top and bottom quark decay channel.","abstract_source_suggest":{"input":"Springer"}},{"source":"arXiv","value":"Searches are presented for heavy gauge bosons decaying into a top and a bottom quark in data collected by the CMS experiment at sqrt(s) = 13 TeV that correspond to an integrated luminosity of 2.2 and 2.6 inverse femtobarns in the leptonic and hadronic analyses, respectively. Two final states are analyzed, one containing a single electron, or muon, and missing transverse momentum, and the other containing multiple jets and no electrons or muons. No evidence is found for a right-handed W' boson (W'[R]) and the combined analyses exclude at 95% confidence level W'[R] with masses below 2.4 TeV if M[W'[R]] >> M[nu[R]] (mass of the right-handed neutrino), and below 2.6 TeV if M[W'[R]] < M[nu[R]]. The results provide the most stringent limits for right-handed W' bosons in the top and bottom quark decay channel.","abstract_source_suggest":{"input":"arXiv"}}],"primary_arxiv_category":["hep-ex"],"titles":[{"source":"Springer","title":"Searches for W′ bosons decaying to a top quark and a bottom quark in proton-proton collisions at 13 TeV"},{"source":"arXiv","title":"Searches for W' bosons decaying to a top quark and a bottom quark in proton-proton collisions at 13 TeV"}],"imprints":[{"date":"2017-08-08"}],"curated":true},"updated":"2026-04-16T21:26:13.044605+00:00"},{"id":"1593762","created":"2017-04-21T00:00:00+00:00","links":{"bibtex":"https://inspirehep.net/api/literature/1593762?format=bibtex","latex-eu":"https://inspirehep.net/api/literature/1593762?format=latex-eu","latex-us":"https://inspirehep.net/api/literature/1593762?format=latex-us","json":"https://inspirehep.net/api/literature/1593762?format=json","json-expanded":"https://inspirehep.net/api/literature/1593762?format=json-expanded","cv":"https://inspirehep.net/api/literature/1593762?format=cv","citations":"https://inspirehep.net/api/literature/?q=refersto%3Arecid%3A1593762"},"metadata":{"citation_count":59,"report_numbers":[{"value":"CMS-TOP-15-008"},{"value":"CERN-EP-2017-050"}],"publication_info":[{"journal_volume":"96","artid":"032002","year":2017,"journal_issue":"3","journal_title":"Phys.Rev.D"}],"documents":[{"filename":"10.1103_PhysRevD.96.032002.pdf","attachment":{"content":"Measurement of the top quark mass in the dileptonic tt̄ decay channel using\nthe mass observables Mbl, MT2, and Mblν in pp collisions at\n\nffiffi\ns\n\np\n= 8 TeV\n\nA.M. Sirunyan et al.\n*\n\n(CMS Collaboration)\n(Received 20 April 2017; published 22 August 2017)\n\nA measurement of the top quark mass (Mt) in the dileptonic tt̄ decay channel is performed using data\nfrom proton-proton collisions at a center-of-mass energy of 8 TeV. The data was recorded by the CMS\nexperiment at the LHC and corresponds to an integrated luminosity of 19.7� 0.5 fb−1. Events are selected\nwith two oppositely charged leptons (l ¼ e, μ) and two jets identified as originating from b quarks. The\nanalysis is based on three kinematic observables whose distributions are sensitive to the value of Mt.\nAn invariant mass observable, Mbl, and a “stransverse mass” observable, MT2, are employed in a\nsimultaneous fit to determine the value ofMt and an overall jet energy scale factor (JSF). A complementary\napproach is used to construct an invariant mass observable, Mblν, that is combined with MT2 to measure\nMt. The shapes of the observables, along with their evolutions in Mt and JSF, are modeled by a\nnonparametric Gaussian process regression technique. The sensitivity of the observables to the value ofMt\n\nis investigated using a Fisher information density method. The top quark mass is measured to be\n172.22� 0.18ðstatÞ þ0.89\n\n−0.93 ðsystÞ GeV.\nDOI: 10.1103/PhysRevD.96.032002\n\nI. INTRODUCTION\n\nThe top quark mass is a fundamental parameter of the\nstandard model (SM), and an important component in\nglobal electroweak fits evaluating the self-consistency of\nthe SM [1]. In addition, the value ofMt has implications for\nthe stability of the SM electroweak vacuum due to the role\nof the top quark in the quartic term of the Higgs potential\n[2]. Measurements ofMt have been conducted by the CDF\nand D0 experiments at the Tevatron, and by the ATLAS and\nCMS experiments at the CERN LHC. These measurements\nare typically calibrated against the top quark mass param-\neter in Monte Carlo (MC) simulation. Studies suggest that\nthis parameter can be related to the top quark mass in a\ntheoretically well-defined scheme with a precision of about\n1 GeV [3]. A combination of measurements including\nall four experiments and tt̄ decay channels with zero, one,\nor two high-pT electrons or muons (all-hadronic, semi-\nleptonic, and dileptonic, respectively) gives a value of\n173.34� 0.36ðstatÞ � 0.67ðsystÞ GeV [4] for the top quark\nmass. Currently, the most precise experimental determi-\nnation of Mt is provided by CMS using a combination\nof measurements in all tt̄ decay channels, yielding a\nvalue of 172.44� 0.13ðstatÞ � 0.47ðsystÞ GeV [5]. In\nthe dileptonic tt̄ decay channel, the ATLAS [6] and\nCMS [5] collaborations have recently determined Mt to\n\nbe 172.99� 0.41ðstatÞ � 0.74ðsystÞ GeV and 172.82�\n0.19ðstatÞ � 1.22ðsystÞ GeV, respectively. This paper pre-\nsents a reanalysis of the dileptonic tt̄ data set recorded in\n2012, with a primary motivation of reducing the systematic\nuncertainties in Mt determination.\nThe dileptonic top quark pair (tt̄) decay topology,\n\ntt̄ → ðblþνÞðb̄l−ν̄Þ, with l ¼ ðe; μÞ, presents a challenge\nin mass measurement arising primarily from the presence\nof two neutrinos in the final state. While the undetected p⃗T\nof a single final-state neutrino in a semileptonic tt̄ decay\ncan be inferred from the momentum imbalance in the event,\nthe allocation of momentum imbalance between the two\nneutrinos in a dileptonic tt̄ decay is unknown a priori.\nFor this reason, the dileptonic tt̄ system is kinematically\nunderconstrained, and mass determination cannot be easily\nconducted on an event-by-event basis. Instead, the mass of\nthe parent top quarks in the dileptonic tt̄ system can be\nextracted from kinematic features over an ensemble of\nevents, with the help of appropriate observables and\nreconstruction techniques.\nThe measurement reported in this paper is based on a set\n\nof observables that have been proposed specifically for\nmass reconstruction in underconstrained decay topologies.\nThese observables include the invariant mass,Mbl, of a bl\nsystem, a “stransverse mass” variable, Mbb\n\nT2, constructed\nwith the b and b̄ daughters of the tt̄ system [7–9], and the\ninvariant mass of a blν system, Mblν, where the neutrino\nmomentum is estimated by the MT2-assisted on-shell\n(MAOS) reconstruction technique [10]. The MAOS\nreconstruction technique builds on MT2 by exploiting the\nneutrino momenta estimates that are by-products of the\nMT2 algorithm. The sensitivity of the Mbl, Mbb\n\nT2, and Mblν\n\n*Full author list given at the end of the article.\n\nPublished by the American Physical Society under the terms of\nthe Creative Commons Attribution 4.0 International license.\nFurther distribution of this work must maintain attribution to\nthe author(s) and the published article’s title, journal citation,\nand DOI.\n\nPHYSICAL REVIEW D 96, 032002 (2017)\n\n2470-0010=2017=96(3)=032002(31) 032002-1 © 2017 CERN, for the CMS Collaboration\n\nhttps://doi.org/10.1103/PhysRevD.96.032002\nhttps://doi.org/10.1103/PhysRevD.96.032002\nhttps://doi.org/10.1103/PhysRevD.96.032002\nhttps://doi.org/10.1103/PhysRevD.96.032002\nhttps://creativecommons.org/licenses/by/4.0/\nhttps://creativecommons.org/licenses/by/4.0/\n\n\nobservables to the value ofMt is investigated using a Fisher\ninformation density method. Distributions ofMbl andMbb\n\nT2\nin dileptonic events contain a sharp edge descending to a\nkinematic end point, the location of which is sensitive to the\nvalue of Mt. Recently, masses of the top quark, W boson\n(MW), and neutrino (Mν) were extracted in a simultaneous\nfit using the end points of these distributions in dileptonic tt̄\nevents [11]. The Mbl, Mbb\n\nT2, and MAOS Mblν observables\nare described in more detail in Sec. IV.\nOne of the dominant sources of systematic uncertainty\n\nlimiting the precision of this measurement comes from the\noverall uncertainty in jet energy scale (JES). To address the\nJES uncertainty, we introduce a technique that uses theMbl\n\nand Mbb\nT2 observables to determine an overall jet energy\n\nscale factor (JSF) simultaneously with the top quark mass,\nwhere the JSF is defined as a multiplicative factor scaling\nthe four-vectors of all jets in the event. Similar techniques\nhave been developed for the all-hadronic and semileptonic\ntt̄ channels, where the jet pair originating from a W boson\ndecay is used to determine the JSF [5]. Because light-quark\njets from theW boson decay are used to calibrate the energy\nscale of b jets arising from the t and t̄ decays, these methods\nare sensitive to flavor-dependent uncertainties that emerge\nfrom differences in the response of b jets and light-quark\njets. In the method featured here, the JSF is determined in\nthe dileptonic tt̄ channel without relying on a W boson\ndecaying to jets. Instead, it achieves sensitivity to the JSF\nthrough the kinematic differences between b jets, which are\nsubject to JSF scaling, and leptons, which are not. Because\nit does not use light quarks from a hadronic W boson decay,\nthis approach is insensitive to flavor-dependent JES\nuncertainties.\nTo model the Mbl, Mbb\n\nT2, and MAOS Mblν distribution\nshapes, we use a Gaussian process (GP) regression tech-\nnique [12,13]. This technique is nonparametric, and thus\nlargely model independent. It is effective in modeling\ndistribution shapes when no theoretical guidance is avail-\nable to specify a functional form. The distribution shapes\ncan conveniently be modeled as functions of multiple\nvariables. In this analysis, three variables are used: the\nvalue of the relevant observable (Mbl, Mbb\n\nT2, or Mblν), Mt,\nand the JSF. The shapes are determined using simulated\nevents generated with seven different values of Mt ranging\nfrom 166.5 to 178.5 GeV, and with five values of JSF,\nranging from 0.97 to 1.03, applied to the jets in each event.\nEach shape ultimately models the distributions of the\nobservables together with their evolution in Mt and in JSF.\n\nII. THE CMS DETECTOR\n\nThe central feature of the CMS apparatus is a super-\nconducting solenoid of 6 m internal diameter, providing a\nmagnetic field of 3.8 T. Within the solenoid volume are a\nsilicon pixel and strip tracker, a lead tungstate crystal\nelectromagnetic calorimeter (ECAL), and a brass and\n\nscintillator hadron calorimeter (HCAL), each composed\nof a barrel and two end cap sections. The tracker has a\ntrack-finding efficiency of more than 99% for muons with\ntransverse momentum pT > 1 GeV and pseudorapidity\njηj < 2.4. The ECAL is a fine-grained hermetic calorimeter\nwith quasiprojective geometry, and is distributed in the\nbarrel region of jηj < 1.48 and in two end caps that extend\nup to jηj < 3.0. The HCAL barrel and end caps similarly\ncover the region jηj < 3.0. In addition to the barrel and end\ncap detectors, CMS has extensive forward calorimetry.\nMuons are measured in gas-ionization detectors, which are\nembedded in the steel flux-return yoke outside of the\nsolenoid. The silicon tracker and muon systems play a\ncrucial role in the identification of jets originating from the\nhadronization of b quarks [14]. Events of interest are\nselected using a two-tiered trigger system [15]. The first\nlevel, composed of custom hardware processors, uses\ninformation from the calorimeters and muon detectors to\nselect events at a rate of around 100 kHz within a time\ninterval of less than 4 μs. The second level, known as the\nhigh-level trigger, consists of a farm of processors running\na version of the full event reconstruction software opti-\nmized for fast processing, and reduces the event rate to less\nthan 1 kHz before data storage. A more detailed description\nof the CMS detector, together with a definition of the\ncoordinate system used, can be found in Ref. [16].\n\nIII. DATA SETS AND EVENT SELECTION\n\nWe select dileptonic tt̄ events from a data set recorded atffiffiffi\ns\n\np ¼ 8 TeV during 2012 corresponding to an integrated\nluminosity of 19.7� 0.5 fb−1 [17]. Events are required\nto pass one of several triggers that require at least two\nleptons, ee, eμ, or μμ, where the leading (higher-pT) lepton\nsatisfies pT > 17 GeV and the subleading lepton satisfies\npT > 8 GeV.\nA particle-flow (PF) algorithm [18,19] is used to\n\nreconstruct and identify each individual particle in an event\nby combining information from various subdetectors of\nCMS. Each event is required to have at least one recon-\nstructed collision vertex, with the primary vertex selected as\nthe one containing the largest\n\nP\npT\n\n2 of associated tracks.\nElectron candidates are reconstructed by matching a cluster\nof energy deposits in the ECAL to a reconstructed track\n[20]. They are required to satisfy pT > 20 GeV and\njηj < 2.5. Muon candidates are reconstructed in a global\nfit that combines information from the silicon tracker and\nmuon system [21], and must have pT > 20 GeV and\njηj < 2.4. A requirement on the relative isolation is\nimposed inside a cone ΔR ¼\n\nffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi\nðΔηÞ2 þ ðΔϕÞ2\n\np\naround\n\neach lepton candidate, where ϕ is the azimuthal angle in\nradians. A parameter Irel ¼\n\nP\npTi=pl\n\nT is defined, where the\nsum includes all reconstructed PF candidates inside the\ncone (excluding the lepton itself), and pl\n\nT is the lepton pT.\nElectron (muon) candidates are required to have Irel < 0.15\n\nA.M. SIRUNYAN et al. PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-2\n\n\n\n(0.2) with ΔR < 0.3 (0.4). Events selected off-line are\nrequired to contain exactly two such leptons, ee, eμ, or μμ,\nwith opposite charge. For events containing an eþe− or\nμþμ− pair, contributions from low-mass resonances are\nsuppressed by requiring an invariant mass of the lepton pair\nMll > 20 GeV, while contributions from Z boson decays\nare suppressed by requiring that jMZ −Mllj > 15 GeV,\nwhere MZ ¼ 91.2 GeV [22].\nHadronic jets are clustered from PF candidates with the\n\ninfrared and collinear safe anti-kT algorithm [23], with a\ndistance parameter R of 0.5, as implemented in the FASTJET\n\npackage [24]. The jet momentum is determined as the\nvectorial sum of all particle momenta in this jet. Corrections\nto the JES and jet energy resolution (JER) are derived using\nMC simulation, and are confirmed with measurements\nof the energy balance in quantum chromodynamics\n(QCD) dijet, QCD multijet, photonþ jet, and Z þ jet\nevents [25]. Muons, electrons, and charged hadrons origi-\nnating from multiple collisions within the same or nearby\nbunch crossings (pileup), are not included in the jet\nreconstruction. Contributions from neutral hadrons origi-\nnating from pileup are estimated and subtracted from the\nJES. Jets originating from the hadronization of b quarks\nare identified with a combined secondary vertex (CSV) b\ntagging algorithm [14], combining information from the jet\nsecondary vertex with the impact parameter significances\nof its constituent tracks. The algorithm yields a tagging\nefficiency of approximately 85% and a misidentification\nrate of 10%. Events are required to contain at least two jets\nthat pass the b tagging algorithm and satisfy pT > 30 GeV\nand jηj < 2.5. In this analysis, the two jets satisfying these\nrequirements that have the highest CSV discriminator\nvalues are referred to as b jets.\nThe missing transverse momentum vector is defined as\n\np⃗miss\nT ¼ −\n\nP\np⃗Ti, where the sum includes all reconstructed\n\nPF candidates in an event [26]. Its magnitude is referred to\nas pmiss\n\nT . Corrections to the JES and JER are propagated\ninto pmiss\n\nT , as well as an offset correction that accounts for\npileup interactions. An additional correction mitigates a\nmild azimuthal dependence, arising from imperfect detec-\ntor alignment and other effects, which is observed in the\nreconstructed pmiss\n\nT . To further suppress contributions from\nDrell-Yan processes, events containing an eþe− or μþμ−\n\npair are required to have pmiss\nT > 40 GeV.\n\nSimulated tt̄ signal events are generated with the\nMADGRAPH 5.1.5.11 matrix-element generator [27], combined\nwith MADSPIN to include spin correlations of the top quark\ndecay products [28], PYTHIA 6.426 with the Z2� tune for\nparton showering [29], and TAUOLA for the decay of τ\nleptons [30]. Parton distribution functions (PDFs) are\ndescribed by the CTEQ6L1 set [31]. The tt̄ signal events\nare generated with seven different values of Mt ranging\nfrom 166.5 to 178.5 GeV. The contribution from the W\nassociated single top quark production (tW) is simulated\nwith POWHEG 1.380 [32–35], where the value of Mt is\n\nassumed to be 172.5 GeV. Background events from\nW þ jets and Z þ jets production are generated with\nMADGRAPH 5.1.3.30, and contributions from WW, WZ, ZZ\nprocesses are simulated with PYTHIA. The CMS detector\nresponse to the simulated events is modeled with GEANT4\n\n[36]. All background processes are normalized to their\npredicted cross sections [37–41].\nWith the requirements outlined previously, 41640 tt̄\n\ncandidate events are selected in data. The sample compo-\nsition is estimated in simulation to be 95% dileptonic tt̄,\n4% single top quark, and 1% other processes including\ndiboson, W þ jets, and Drell-Yan production, as well as\nsemileptonic and all-hadronic tt̄.\n\nIV. OBSERVABLES\n\nThe observables featured in this study have been\ndeveloped for physics scenarios where undetected particles,\nsuch as neutrinos, carry away a portion of the kinematic\ninformation necessary for full event reconstruction. In the\ndileptonic tt̄ system, distributions in these observables\ncontain end points, edges, and peak regions that are\nsensitive to the top quark mass. The observables are\ndescribed in more detail below.\n\nA. The Mbl observable\n\nThe Mbl observable is defined as\n\nMbl ¼\nffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi\nðpb þ plÞ2\n\nq\n; ð1Þ\n\nwhere pb and pl are four-vectors corresponding to a b jet\nand lepton, respectively. The bl pairs underlying each\nvalue of Mbl are chosen out of four possible combinations\nby an algorithm described in Sec. IVA 1. The Mbl\nobservable contains a kinematic end point that occurs\nwhen the b jet and lepton are directly back to back in\nthe top quark rest frame. The location of this end point,\nðMblÞmax, is a function of the masses involved in the decay:\n\nðMblÞmax ¼\nffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi\nðM2\n\nt −M2\nWÞðM2\n\nW −M2\nνÞ\n\np\nMW\n\n: ð2Þ\n\nWith Mt¼172.5GeV, MW ¼80.4GeV [22], and Mν¼0,\nwe have ðMblÞmax ¼ 152.6 GeV. Although this end point\nis a theoretical maximum on the value of Mbl at leading\norder, events are still observed beyond this value due to\nbackground contamination, resolution effects, and nonzero\nparticle widths.\nThe Mbl distribution is shown in data and MC simu-\n\nlation in Fig. 1 (upper), with a breakdown of signal and\nbackground events shown in the simulation. The “signal”\ncategory includes tt̄ dilepton decays where both b jets are\ncorrectly identified by the b tagging algorithm. The back-\nground categories include: “mistag” dilepton decays where\na light quark or gluon jet is incorrectly selected by the b\n\nMEASUREMENT OF THE TOP QUARK MASS IN THE … PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-3\n\n\n\ntagging algorithm; “τ decays” where dilepton events\ninclude at least one τ lepton in the final state subsequently\ndecaying leptonically; and “hadronic decays” that include\nevents where at least one of the top quarks decays hadroni-\ncally. The “non-tt̄ bkg” category consists of single top\n\nquark, diboson, W þ jets, and Drell-Yan processes. Events\nin which a top quark decays through a τ lepton contain extra\nneutrinos stemming from the leptonic τ decay. Although\nthe extra neutrinos cause a small distortion to the kinematic\ndistributions, these events still contribute to the sensitivity\nof the measurement.\nThe sensitivity of the Mbl observable to the value of Mt\n\nis demonstrated in Fig. 1 (lower), where Mbl shapes\ncorresponding to three values of the top quark mass in\nMC simulation (MMC\n\nt ) are shown. The variation between\nthese shapes reveals regions of theMbl distribution that are\nsensitive to the value ofMt, such as the edges to the left and\nright of the Mbl peak, and regions that are not sensitive,\nsuch as the stationary point where the three shapes\nintersect. To provide a quantitative description of these\neffects, we introduce a “local shape sensitivity” function,\nalso known as the Fisher information density, shown in\nFigs. 1, 3, and 4. This function conveys the sensitivity of an\nobservable at a specific point on its shape. For the Mbl\nobservable, the local shape sensitivity function peaks near\nthe kinematic end point (Mbl ∼ 150 GeV), and has a zero\nvalue at the stationary point (Mbl ∼ 105 GeV). The inte-\ngral of this function over its range is proportional to 1=σ2Mt\n\n,\nwhere σMt\n\nis the statistical uncertainty on a measurement of\nMt. A full description of the local shape sensitivity function\nis given in Appendix A.\n\n1. b jet and lepton combinatorics\n\nThe two b jets and two leptons stemming from each tt̄\ndecay give rise to a twofold matching ambiguity, with two\ncorrect and two incorrect bl pairings possible in each\nevent. Pairings in which the b jet and lepton emerge from\ndifferent top quarks do not necessarily obey the upper\nbound described in Eq. (2), and thus do not have a clean\nkinematic end point in Mbl. Although a priori it is\nexperimentally difficult to distinguish between correct\nand incorrect pairings, one possible approach is to select\nthe smallest two Mbl values in each event. This way, the\nkinematic end point of the distribution is preserved—even\nif the smallest two Mbl values do not correspond to the\ncorrect pairings, they are guaranteed to fall below the\ncorrect pairings, which do respect the end point. In this\nanalysis, we employ a slightly more sophisticated matching\ntechnique, introduced in Ref. [11], where either two or\nthree bl pairs are selected in each event.\nBy selecting either two or three bl pairs in each event,\n\nthe technique employed in this analysis has the benefit of\nincreased statistical power, while preserving the kinematic\nend point of Mbl. Although they are not necessarily the\ncorrect pairs, the corresponding Mbl values are guaranteed\nby construction to be less than or equal to those of the\ncorrect pairs. The matching technique is based on the\nfollowing prescription:\n(1) match each b jet with the lepton that produces the\n\nlower Mbl value;\n\nE\nnt\n\nrie\ns \n\n/ 1\n.9\n\n G\neV\n\n0\n\n0.5\n\n1\n\n1.5\n\n2\n\n2.5\n\n3\n310×\n\nData\nSignal\nMistag bkg\n decaysτ\n\nHad. decays\n bkgtNon-t\n\n (8 TeV)-119.7 fb\n\nCMS\n\n [GeV]blM\n\n40 60 80 100 120 140 160 180\n\nD\nat\n\na/\nM\n\nC\n\n0.5\n\n1\n\n1.5\nUncertainties\n\n [GeV]blM\n40 60 80 100 120 140 160 180\n\nA\nrb\n\nitr\nar\n\ny \nun\n\nits\n\n0\n\n2\n\n4\n\n6\n\n8\n\n10\n\n12\n\n14\n\n16\n\n18\n\n20\n\n22\n\n3−10×\n\n = 166.5 GeVMC\ntM\n\n = 172.5 GeVMC\ntM\n\n = 178.5 GeVMC\ntM\n\nLocal shape sensitivity\n\n(8 TeV)\n\nCMS\nSimulation\n\nFIG. 1. (Upper) The Mbl distribution in data and simulation\nwith MMC\n\nt ¼ 172.5 GeV, normalized to the number of events in\nthe 8 TeV data set corresponding to an integrated luminosity of\n19.7� 0.5 fb−1. The lower panel shows the ratio between the\ndata and simulation. Statistical and systematic uncertainties on\nthe distribution in simulation are represented by the shaded area.\nA description of the systematic uncertainties is given in Sec. VIII.\n(Lower) The Mbl distribution shapes in simulation, normalized\nto unit area, corresponding to three values of MMC\n\nt are shown\ntogether with the local shape sensitivity function, described in\nAppendix A. TheMbl distributions include two or three values of\nMbl for each event. The distribution shapes are modeled with a\nGP regression technique, described in Sec. VI.\n\nA. M. SIRUNYAN et al. PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-4\n\n\n\n(2) match each lepton with the b jet that produces the\nlower Mbl value.\n\nThis recipe produces either two or three values of Mbl. In\nthe latter case, two different leptons may be successfully\npaired with the same b jet, and vice versa. Such a\nconfiguration highlights the difference between this recipe\nand the simpler approach of choosing the smallest two\nvalues ofMbl, which do not necessarily incorporate both b\njets and both leptons in the event. For example, this could\noccur if both b jets are matched to a single lepton. In these\ncases, the next largest Mbl value is also needed to ensure\nboth b jets and both leptons from the event are used.\n\nB. The MT2 observable\n\nThe MT2 stransverse mass observable [7,8] is based on\nthe transverse mass, MT. The transverse mass of the W\nboson in a W → lν decay is given by\n\nMT ¼\nffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi\nm2\n\nl þm2\nν þ 2ðETlETν − p⃗Tl · p⃗TνÞ\n\nq\n; ð3Þ\n\nwhere E2\nTx ¼ m2\n\nx þ p⃗2\nT for x ∈ fl; νg, mx is the particle\n\nmass, and p⃗Tx is the particle momentum projected onto the\nplane perpendicular to the beams. This quantity exhibits a\nkinematic end point at the parent mass, MW , which occurs\nin configurations when both the lepton and neutrino\nmomenta lie entirely in the transverse plane (up to a\ncommon longitudinal boost).\nThe dileptonic tt̄ system has two layers of decays, with\n\nt → Wb in the first step followed byW → lν in the second.\nThe result is an event topology with two identical branches,\nt → blþν and t̄ → b̄l−ν̄, each with a visible (bl) and\ninvisible (ν) component. In this case, one value of MT can\nbe computed for each branch. The invisible particle\nmomentum associated with each branch, however, is not\nknown. While for a semileptonic tt̄ decay, with only one\nW → lν decay, the neutrino p⃗T is estimated from the p⃗miss\n\nT\nin the event, a dileptonic tt̄ decay includes two neutrinos,\nfor which the allocation of p⃗miss\n\nT between them is unknown.\nThe MT2 observable is an extension of MT for a system\n\nwith two identical decay branches, “a” and “b,” as those\nin the dileptonic tt̄ system. Here, the invisible particle\nmomenta, p⃗a\n\nT and p⃗b\nT, must add up to the total p⃗miss\n\nT . The\nstrategy of MT2 is to impose this constraint on the invisible\nparticle momenta, while also performing a minimization in\norder to preserve the kinematic end point of MT. For a\ngeneral event with a symmetric decay topology, MT2 is\ndefined as\n\nMT2 ¼ min\np⃗a\nTþp⃗ b\n\nT¼p⃗miss\nT\n\n½maxfMa\nT;M\n\nb\nTg�; ð4Þ\n\nwhereMa\nT andM\n\nb\nT correspond to the two decay branches. If\n\nthe invisible particle mass is known, it can be incorporated\ninto theMT2 calculation as well, yielding an end point at the\n\nparent particle mass. Although the final values of p⃗a\nT and p⃗\n\nb\nT\n\nare typically treated as intermediate quantities in the MT2\nalgorithm, they are employed as neutrino p⃗T estimates in\nthe MAOS reconstruction technique described in Sec. IV C.\n\n1. The MT2 subsystems\n\nIn the tt̄ system, there are several ways in whichMT2 can\nbe computed, depending on how the decay products are\ngrouped together. The MT2 algorithm classifies them into\nthree categories: upstream, visible, and child particles [42].\nThe child particles are those at the end of the decay chain\nthat are unobservable or simply treated as unobservable. In\nthe latter case, the child particle momenta are added to the\np⃗miss\nT vector. The visible particles are those whose p⃗T values\n\nare measured and used in the calculations; and the upstream\nparticles are those from further up in the decay chain,\nincluding any initial-state radiation (ISR) accompanying\nthe hard collision.\nIn general, the child, visible, and upstream particles may\n\nactually be collections of objects, creating three possible\nsubsystems in the dileptonic tt̄ event topology. These\nsubsystems are illustrated in Fig. 2. For simplicity, we\nrefer to the corresponding MT2 observables as Mbb\n\nT2, M\nll\nT2 ,\n\nand Mbl\nT2, where\n\n(i) The Mll\nT2 observable uses the two leptons as visible\n\nparticles, treating the neutrinos as invisible child\nparticles, and combining the b jets with all other\nupstream particles in the event.\n\n(ii) The Mbb\nT2 observable uses the b jets as visible\n\nparticles, and treats the W bosons as child particles,\nignoring the fact that their charged daughter leptons\nare indeed observable. It considers only ISR jets as\ngenerators of upstream momentum.\n\n(iii) The Mbl\nT2 observable combines the b jet and the\n\nlepton to form a single visible system, and takes\nthe neutrinos as the invisible particles. A twofold\nmatching ambiguity results from the matching of b\njets to leptons in each event. In order to preserve the\nkinematic end point of the Mbl\n\nT2 distribution, the bl\n\nFIG. 2. TheMT2 subsystems in the dileptonic tt̄ event topology.\n\nMEASUREMENT OF THE TOP QUARK MASS IN THE … PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-5\n\n\n\npair with the smallest value of Mbl\nT2 is used in\n\neach event.\n\nThese observables are identical, respectively, to Mð2;2;1Þ\nT2 ,\n\nMð2;1;0Þ\nT2 ,Mð2;2;0Þ\n\nT2 of Ref. [42], and μbb, μll, μbl of Ref. [11].\nThe subsystem observableMbb\n\nT2 is employed in this study\nto complement the observable Mbl. The Mbb\n\nT2 observable\ncontains an end point at the value of Mt, and can be\ncombined with Mbl to mitigate uncertainties due to the\nJES. This feature is discussed further in Sec. V. The\ndistribution of Mbb\n\nT2 and its sensitivity to the value of Mt\n\nare shown in Fig. 3. Although Mll\nT2 is not directly sensitive\n\ntoMt, the neutrino p⃗T estimates that are a by-product of its\ncomputation are used as an input into the MAOS Mblν\nreconstruction technique described in Sec. IV C.\nThe Mbb\n\nT2 distribution employed in this analysis includes\na kinematic requirement on the upstream momentum,\ndefined as p⃗upst\n\nT ¼P\nrecop⃗Ti−\n\nP\nbjetsp⃗Ti−\n\nP\nleptonsp⃗Ti, where\n\nthe sums are conducted over all reconstructed PF candidates,\nb jets, and leptons in each event, respectively. The direction\nof p⃗upst\n\nT is required to lie outside the opening angle between\nthe two b jet p⃗T vectors in the event. This requirement\nprimarily impacts events at low values ofMbb\n\nT2, and its effect\non the statistical sensitivity of the observable is small.\n\nC. The MAOS Mblν observable\n\nThe MAOS reconstruction technique employed in this\nanalysis is based on the subsystem observable Mll\n\nT2 . In the\nMll\n\nT2 algorithm, an MT variable, defined in Eq. (3), is\nconstructed from the lþν and l−ν̄ pairs corresponding to\neach of the tt̄ decay branches. Because the values of\nneutrino p⃗T are unknown, a minimization is conducted\nin Eq. (4) over possible values consistent with the measured\np⃗miss\nT in each event.\nThe MAOS technique employs the neutrino p⃗T values\n\nthat are determined by the Mll\nT2 minimization to construct\n\nfull blν invariant mass estimates corresponding to each of\nthe tt̄ decay branches. Given the neutrino p⃗T values, the\nremaining z-components of their momenta are obtained by\nenforcing the W mass on-shell requirement [22]\n\nMðlþνÞ ¼ Mðl−ν̄Þ ¼ MW ¼ 80.4 GeV: ð5Þ\nThis yields a longitudinal momentum for each neutrino\ngiven by\n\npzν ¼\n1\n\nE2\nTl\n\nh\npzlA�\n\nffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi\np2\nzl þ E2\n\nTl\n\nq ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi\nA2 − ðETlETνÞ2\n\nq i\n; ð6Þ\n\nwhere A ¼ 1\n2\nðMW\n\n2 þMν\n2 þM2\n\nlÞ þ p⃗Tl · p⃗Tν [10]. Given\nthese estimates for the neutrino three-momenta together\nwithMν ¼ 0, we have the required four vectors to construct\nan Mblν invariant mass corresponding to the decay prod-\nucts of each top quark.\nThe quadratic equations in Eq. (6) underlying the W\n\nmass on-shell requirement provide up to two solutions\nfor each value of pzν, yielding a twofold ambiguity for\neach neutrino momentum. In addition, there is a twofold\nambiguity resulting from the matching of b jets to lν pairs\nin the construction of blν invariant masses. No matching\nambiguity exists between leptons and neutrinos, since the\nlþν and l−ν̄ pairs have been fixed by the Mll\n\nT2 algorithm.\nThe combined fourfold ambiguity, along with the two top\nquark decays in each event, gives up to eight possible\nvalues of Mblν. In the measurement, all of the available\nvalues are used: for each lν pair, this includes up to two\n\nE\nnt\n\nrie\ns \n\n/ 1\n.3\n\n G\neV\n\n0\n\n50\n\n100\n\n150\n\n200\n\n250\n\n300\n\n350\n\n400\n\n450 Data\nSignal\nMistag bkg\n decaysτ\n\nHad. decays\n bkgtNon-t\n\n (8 TeV)-119.7 fb\n\nCMS\n\n [GeV]bb\nT2M\n\n120 140 160 180 200\n\nD\nat\n\na/\nM\n\nC\n\n0.5\n\n1\n\n1.5\nUncertainties\n\n [GeV]bb\nT2M\n\n120 140 160 180 200\n\nA\nrb\n\nitr\nar\n\ny \nun\n\nits\n\n0\n\n5\n\n10\n\n15\n\n20\n\n25\n\n30\n\n35\n\n3−10×\n\n = 166.5 GeVMC\ntM\n\n = 172.5 GeVMC\ntM\n\n = 178.5 GeVMC\ntM\n\nLocal shape sensitivity\n\n(8 TeV)\n\nCMS\nSimulation\n\nFIG. 3. Following the conventions of Fig. 1, shown are the\n(upper) Mbb\n\nT2 distribution in data and simulation with MMC\nt ¼\n\n172.5 GeV, and (lower) Mbb\nT2 distribution shapes in simulation\n\ncorresponding to three values ofMMC\nt , along with the local shape\n\nsensitivity function. The Mbb\nT2 distributions include one value of\n\nMbb\nT2 for each event if it satisfies the kinematic requirement outlined\n\nin Sec. IV B 1.\n\nA. M. SIRUNYAN et al. PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-6\n\n\n\nneutrino pzν solutions, and two b-lν matches. The dis-\ntribution of MAOS Mblν and its sensitivity to the value of\nMt are shown in Fig. 4.\n\nV. SIMULTANEOUS DETERMINATION\nOF Mt AND JSF\n\nTo mitigate the impact of JES uncertainties on the\nprecision of this measurement, we introduce a technique\nthat allows a JSF parameter to be fit simultaneously with\nMt. The JSF is a constant multiplicative factor that\ncalibrates the overall energy scale of reconstructed jets.\nIt is applied in addition to the standard JES calibration,\n\nwhich corrects the jet response as a function of pT and η.\nThe dominant component of uncertainty in the JES\ncalibration can be attributed to a global factor in jet\nresponse, which is captured in the JSF.\nThe challenge in determining the JSF simultaneously\n\nwithMt stems from the large degree of correlation between\nthese parameters. In the top quark decay, t → blν, the JSF\ndirectly affects the momentum of the b jet, and indirectly,\nthe inferred momentum of the neutrino, by scaling all jets\nentering the pmiss\n\nT sum. The Mt parameter affects the\nmomenta of these two particles in addition to the lepton\nproduced in the top quark decay. In the context of\nobservables and distribution shapes, variations in the Mt\nand JSF parameters cause shape changes that are difficult to\ndistinguish. For this reason, a shape-based analysis using a\nsingle observable can be implemented to determine either\nMt or JSF, but not both simultaneously.\n\nE\nnt\n\nrie\ns \n\n/ 2\n.7\n\n G\neV\n\n0\n\n1\n\n2\n\n3\n\n4\n\n5\n\n6\n\n7\n\n310×\n\nData\nSignal\nMistag bkg\n decaysτ\n\nHad. decays\n bkgtNon-t\n\n (8 TeV)-119.7 fb\n\nCMS\n\n [GeV]νblM\n100 150 200 250 300\n\nD\nat\n\na/\nM\n\nC\n\n0.9\n\n1\n\n1.1 Uncertainties\n\n [GeV]νblM\n\n100 150 200 250 300\n\nA\nrb\n\nitr\nar\n\ny \nun\n\nits\n\n0\n\n2\n\n4\n\n6\n\n8\n\n10\n\n12\n\n14\n\n3−10×\n\n = 166.5 GeVMC\ntM\n\n = 172.5 GeVMC\ntM\n\n = 178.5 GeVMC\ntM\n\nLocal shape sensitivity\n\n(8 TeV)\n\nCMS\nSimulation\n\nFIG. 4. Following the conventions of Fig. 1, shown are the\n(upper) MAOS Mblν distribution in data and simulation with\nMMC\n\nt ¼ 172.5 GeV, and (lower) the MAOS Mblν distribution\nshapes in simulation corresponding to three values ofMMC\n\nt , along\nwith the local shape sensitivity function. The MAOS Mblν\ndistributions include up to eight values of Mblν for each event.\n\n [GeV]blM\n40 60 80 100 120 140 160 180\n\nA\nrb\n\nitr\nar\n\ny \nun\n\nits\n\n0\n\n2\n\n4\n\n6\n\n8\n\n10\n\n12\n\n14\n\n16\n3−10×\n\nJSF = 0.97\n\nJSF = 1.00\n\nJSF = 1.03\n\n(8 TeV)\n\nCMS\nSimulation\n\n [GeV]bb\nT2M\n\n110 120 130 140 150 160 170 180 190 200\n\nA\nrb\n\nitr\nar\n\ny \nun\n\nits\n\n0\n\n5\n\n10\n\n15\n\n20\n\n25\n3−10×\n\nJSF = 0.97\n\nJSF = 1.00\n\nJSF = 1.03\n\n(8 TeV)\n\nCMS\nSimulation\n\nFIG. 5. The (upper) Mbl and (lower) Mbb\nT2 distributions in\n\nsimulation with Mt ¼ 172.5 GeV for several values of JSF. Two\nor three values are included in theMbl distribution for each event,\nand one value is included in theMbb\n\nT2 distribution if it satisfies the\nkinematic requirement outlined in Sec. IV B 1. The distributions\nare normalized to unit area. The three curves corresponding to\neach of the Mbl and Mbb\n\nT2 distributions are obtained using a GP\nregression technique described in Sec. VI.\n\nMEASUREMENT OF THE TOP QUARK MASS IN THE … PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-7\n\n\n\nTo determine the Mt and JSF parameters simultane-\nously, we construct a likelihood function that contains two\ndistributions corresponding to theMbl andMbb\n\nT2 observables.\nIn this configuration, variations in the parameters produce\nshifts in each individual distribution. They also create a\nrelative shift between the distributions that provides the\nadditional constraint needed for a simultaneous fit ofMt and\nJSF. The dependence of theMbl andMbb\n\nT2 distribution shapes\nonMt is shown in Figs. 1 and 3, and their dependence on the\nJSF is shown in Fig. 5. The difference in response between\nthe Mbl and Mbb\n\nT2 shapes to the JSF parameter is rooted in\nthe reconstructed objects underlying the Mbl and Mbb\n\nT2\nobservables—while each value of Mbl uses one b jet and\none lepton, each value ofMbb\n\nT2 uses two b jets and no leptons\nfor the visible system. Thus, Mbb\n\nT2 exhibits a stronger\ndependence on the JSF. The likelihood fit used in this\nmeasurement is described in more detail in Sec. VII.\n\nVI. GAUSSIAN PROCESSES FOR\nSHAPE ESTIMATION\n\nIn this analysis, the Mbl, Mbb\nT2, and Mblν distribution\n\nshapes are modeled with a GP regression technique that has\ntwo main advantages over other commonly used shape\nestimate methods. First, the GP shape is nonparametric,\ndetermined only by a set of training points and hyper-\nparameters that regulate smoothing; and second, it can be\neasily trained as a function of several variables simulta-\nneously. The latter feature allows one to capture the smooth\nevolution of the distribution shapes as the Mt and JSF\nparameters are varied. A detailed introduction to GPs can\nbe found in Refs. [12,13]. Here, we give a brief overview of\nthe GP regression technique, with further discussion\nprovided in Appendix B.\nThe likelihood fit described in Sec. VII uses distribution\n\nshapes of the form fðxjMt; JSFÞ, where x is the value of an\nobservable (Mbl, Mbb\n\nT2, or Mblν), and Mt and JSF are free\nparameters in the fit. The shapesf are shown inFigs. 1, 3, and\n4 for each observable, where the free parameters are set to\nMt ¼ 166.5, 172.5, or 178.5 GeV and JSF ¼ 1. In Fig. 5,\nshapes corresponding to the Mbl and Mbb\n\nT2 observables are\nshown with the free parameters set toMt ¼ 172.5 GeV and\nJSF ¼ 0.97, 1.00, or 1.03. In the figures, these shapes are\nrepresented as functions of a single variable (the observable\nx) with Mt and JSF fixed. In GP regression, however, each\nshape is treated as a function of all three quantities (x,Mt, and\nJSF), and can be described as a probability density in three\ndimensions.\nEach GP shape is trained using binned distributions\n\nof the observable x in MC simulation. For each observable,\n35 binned distributions are used, corresponding to seven\nvalues of MMC\n\nt ranging from 166.5 to 178.5 GeV and five\nvalues of JSF ranging from 0.97 to 1.03. Each distribution\nhas 75 bins in x, yielding a total of 2625 training points at\nwhich the value of f is known and used as an input into the\nGP regression process. Each training point is specified by\n\nits values of x, Mt, and JSF. The GP regression technique\ninterpolates between the discrete values of x, Mt, and JSF\ncovered by these training points to provide a shape that is\nsmooth over its range. The smoothness properties of each\nshape are determined by a kernel function that is set by the\nanalyzer. The GP shapes in this analysis correspond to the\nkernel function given in Eq. (B5) of Appendix B.\nThe binned distributions used to construct each GP shape\n\nare normalized to unity. However, the normalization of the\nGP shape itself may deviate slightly from unity due to\nminor imperfections in shape modeling. To mitigate this\neffect, the GP shape normalization is recomputed for each\nvalue of Mt and JSF at which the shape is evaluated. In a\nlikelihood fit, the normalization is recomputed for every\nvariation of the fit parameters.\n\nVII. FIT STRATEGY\n\nThis measurement employs an unbinned maximum-\nlikelihood fit using the Mbl, Mbb\n\nT2, and MAOS Mblν\nobservables described in Sec. IV, along with the GP shape\nestimate technique described in Sec. VI. The MC samples\nused to train the GP shapes include the tt̄ signal and\nbackground processes described in Sec. III.\nThe likelihood constructed from a single observable, x, is\n\ngiven by\n\nLxðMt; JSFÞ ¼\nY\ni\n\nfðxijMt; JSFÞ: ð7Þ\n\nHere, the distribution shape f depends on the value of the\nfree parametersMt and JSF, and expresses the likelihood of\ndrawing some event i where the value of the observable is\nxi. It is normalized to unity over its range for all values of\nMt and JSF. The parametersMt and JSF are varied in the fit\nto maximize the value of the likelihood.\nA likelihood containing two observables, x1 and x2, is\n\nconstructed as a product of individual likelihoods:\n\nLðMt; JSFÞ ¼ Lx1ðMt; JSFÞLx2ðMt; JSFÞ\n¼\n\nY\ni\n\nfðx1ijMt; JSFÞfðx2ijMt; JSFÞ: ð8Þ\n\nThis analysis employs three different versions of the\nlikelihood fit:\n(1) the 1D fit uses the Mbl and Mbb\n\nT2 observables to\ndetermine Mt, and JSF is constrained to be unity;\n\n(2) the 2D fit also uses Mbl and Mbb\nT2 but imposes no\n\nconstraint on the JSF and determines Mt and JSF\nsimultaneously;\n\n(3) the MAOS fit uses theMbb\nT2 andMblν observables to\n\ndetermine Mt, and JSF is constrained to be unity.\nAmong these versions, the 1D fit provides the best\nprecision on the value of Mt. The 2D fit mitigates the\nJES uncertainties, which are the largest source of system-\natic error in the 1D approach. The MAOS fit is expected to\n\nA. M. SIRUNYAN et al. PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-8\n\n\n\n [GeV]MC\ntM\n\n166 168 170 172 174 176 178\n\n [G\neV\n\n]\nM\n\nC\nt\n\n -\n M\n\nfit t\nM\n\n1.5−\n\n1−\n\n0.5−\n\n0\n\n0.5\n\n1\n\n1.5\n2D fit\n\n 0.022±slope = 0.031 \n 3.8±y-intercept = -5.4 \n\n(8 TeV)\n\nCMS\nSimulation\n\n [GeV]MC\ntM\n\n166 168 170 172 174 176 178\n\n -\n 1\n\n.0\nfit\n\nJS\nF\n\n20−\n\n15−\n\n10−\n\n5−\n\n0\n\n5\n\n10\n\n15\n\n20\n3−10×\n\n2D fit\n\n 0.0003±slope = -0.0003 \n 0.05±y-intercept = 0.06 \n\n(8 TeV)\n\nCMS\nSimulation\n\n [GeV]MC\ntM\n\n166 168 170 172 174 176 178\n\n [G\neV\n\n]\nM\n\nC\nt\n\n -\n M\n\nfit t\nM\n\n1.5−\n\n1−\n\n0.5−\n\n0\n\n0.5\n\n1\n\n1.5\n1D fit\n\n 0.006±slope = 0.004 \n 1.1±y-intercept = -0.7 \n\n(8 TeV)\n\nCMS\nSimulation\n\n [GeV]MC\ntM\n\n166 168 170 172 174 176 178\n\n [G\neV\n\n]\nM\n\nC\nt\n\n -\n M\n\nfit t\nM\n\n1.5−\n\n1−\n\n0.5−\n\n0\n\n0.5\n\n1\n\n1.5\nMAOS fit\n\n 0.008±slope = -0.004 \n 1.3±y-intercept = 0.6 \n\n(8 TeV)\n\nCMS\nSimulation\n\n [GeV]MC\ntM\n\n166 168 170 172 174 176 178\n\n [G\neV\n\n]\nM\n\nC\nt\n\n -\n M\n\nfit t\nM\n\n−1.5\n\n−1\n\n−0.5\n\n0\n\n0.5\n\n1\n\n1.5\nHybrid fit\n\n 0.008±slope = 0.009 \n 1.3±y-intercept = -1.6 \n\n(8 TeV)\n\nCMS\nSimulation\n\nFIG. 6. Likelihood fit results as a function ofMMC\nt corresponding to the (top) 2D, (center left) 1D, (center right) MAOS, and (bottom)\n\nhybrid fits. For each value of MMC\nt , the fit is conducted using 50 pseudo-experiments in MC simulation. The mean parameter values,\n\nMt\nfit and JSFfit, are represented by the points, with statistical uncertainties indicated by the error bars. A best-fit line of the form\n\ny ¼ axþ b is shown for each fit configuration.\n\nMEASUREMENT OF THE TOP QUARK MASS IN THE … PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-9\n\n\n\nyield results similar to the 1D fit, and is presented as a\nviable alternative that substitutes the Mbl observable for\nMAOSMblν. The best overall precision onMt is given by a\ncombination of the 1D and 2D fits, which is discussed in\nSec. VII A. The fit results are discussed in Sec. IX.\nThe central value and statistical uncertainty on Mt and\n\nJSF are determined using the bootstrapping technique [43].\nThis method is based on pseudo-experiments rather than\nthe shape of the total likelihood defined in Eq. (8) near its\nmaximum, and thus mitigates the effects of correlation\nbetween the two observables, x1 and x2, in the likelihood.\nThe technique also mitigates possible correlations within\nthe Mbl and Mblν observables when multiple values of the\nobservable occur in a single event. The bootstrapping\ntechnique is primarily relevant for statistical uncertainty\ndetermination, which may otherwise be affected by corre-\nlations in the likelihood. The technique has a negligible\nimpact on the central values of Mt and JSF. The bootstrap\npseudo-experiments are constructed by resampling the full\ndata set with replacement, where the size of each pseudo-\nexperiment is fixed to have the number of events in data\n(41640 events). Events are selected at random from the full\ndata set, so that a particular event has the same probability\nof being chosen at any stage during the sampling process.\nIn this procedure, a single event may be selected more than\nonce for any given pseudo-experiment. In data, all events\nhave an equal probability to be selected. In simulation, the\nprobability of selecting a particular event is proportional to\nits weight, containing the relevant cross sections, as well as\ncorrections for MC modeling and object reconstruction\nefficiencies.\nThe performance of the likelihood fitting approach\n\ndescribed above is evaluated using events in simulation,\nwhere the true values of Mt and JSF are known. The fit is\nconducted using seven different values ofMMC\n\nt ranging from\n166.5 to 178.5GeV for each version of the likelihood fit. The\nresults of this performance study are shown in Fig. 6. The\nlikelihood fits are consistent with zero bias, showing that\nthe GP shape modeling technique accurately captures the\ndistribution shapes and their evolution over several values of\nMMC\n\nt . For this reason, no calibration of the fit is necessary for\nan unbiased determination of the Mt and JSF parameters.\n\nA. Combination of 1D and 2D fits\n\nThe 1D and 2D fits discussed above have differing\nsensitivities to various sources of systematic uncertainty in\nthis measurement. Although the 2D fit successfully miti-\ngates the JES uncertainties, which dominate in the 1D fit,\nother uncertainties in the 2D method are larger and cause\nthe total precision to worsen (Sec. VIII). The best overall\nprecision on the value of Mt is provided by a hybrid fit,\ndefined as a linear combination of the 1D and 2D fits. The\nmeasured value of Mt in the hybrid fit is given by\n\nMhyb\nt ¼ whybM1D\n\nt þ ð1 − whybÞM2D\nt ; ð9Þ\n\nwhere the parameter whyb determines the relative weight\nbetween the 1D and 2D fits in the combination. The value\nof Mhyb\n\nt and its statistical uncertainty are extracted using\nbootstrap pseudo-experiments, as described above. In each\npseudo-experiment, the measured value ofMhyb\n\nt is given by\nthe linear combination in Eq. (9) of the measuredMt\n\n1D and\nMt\n\n2D values. A value of whyb ¼ 0.8 is found to achieve the\nbest precision on Mt when both statistical and systematic\nuncertainties are taken into account. The performance of\nthe hybrid fit, evaluated using MC samples corresponding\nto seven values of MMC\n\nt , is shown in Fig. 6.\n\nVIII. SYSTEMATIC UNCERTAINTIES\n\nThe systematic uncertainties evaluated in this measure-\nment are given in Table I. The uncertainties include\nexperimental effects from detector calibration and object\nreconstruction, and modeling effects mostly arising from\nthe simulation of QCD processes. All uncertainties are\ndetermined by conducting the likelihood fit using events\nfrom MC simulation with the relevant parameters varied by\n�1Δ, where Δ is the uncertainty on a particular parameter.\nThe difference in the measured top quark mass (δMt) or\nJSF (δJSF) is taken to be the corresponding systematic\nuncertainty. For uncertainties that are evaluated by compar-\ning two or more independent MC samples, the values of\nδMt and δJSF may be subject to statistical fluctuations. For\nthis reason, if the value of δMt or δJSF is smaller than its\nstatistical uncertainty in a particular systematic variation,\nthe statistical uncertainty is quoted as the systematic\nuncertainty. Finally, if a systematic uncertainty is one\nsided, where both þΔ and −Δ variations produce δMt\nor δJSF shifts of the same sign, the larger shift is taken as\nthe symmetric systematic uncertainty.\nIn the hybrid fit, the systematic uncertainties are evalu-\n\nated according to the linear combination in Eq. (9). For\neach systematic variation, this gives δMhyb\n\nt ¼ whybδM1D\nt þ\n\nð1 − whybÞδM2D\nt . This approach provides the smallest over-\n\nall uncertainty, with the largest contributions stemming\nfrom the JES, b quark fragmentation modeling, and hard\nscattering scale. The next most precise result is given by the\n1D fit, also dominated by the same sources of uncertainty.\nThe JES uncertainties are successfully mitigated in the 2D\nfit. The 2D fit, however, is more sensitive to the uncer-\ntainties in the top quark pT spectrum, matching scale, and\nunderlying event tune, so the total systematic uncertainty\nfor the 2D fit is larger than that of the 1D fit. The MAOS fit\nhas a larger total systematic uncertainty than the 1D fit due\nto its sensitivity to the JES, top quark pT spectrum, and b\nquark fragmentation modeling uncertainties. Further details\non each source of systematic uncertainty are given below.\n\n(i) Jet energy scale: The JES uncertainty is evaluated\nseparately for four components, which are then\nadded in quadrature [44]. The “Intercalibration”\nuncertainty arises from the modeling of radiation\n\nA. M. SIRUNYAN et al. PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-10\n\n\n\nin the pT- and η-dependent JES determination. The\n“In situ” category includes uncertainties stemming\nfrom the determination of the absolute JES using\nγ=Zþ jet events. The “Uncorrelated” uncertainty\nincludes uncertainties due to detector effects and\npileup. Finally, the “Flavor” uncertainty stems from\ndifferences in the energy response between different\njet flavors—it is a linear sum of contributions from\nthe light quark, charm quark, bottom quark, and\ngluon responses, which are estimated by comparing\nthe Lund string fragmentation in PYTHIA [29] and\ncluster fragmentation in HERWIG++ [45] for each type\nof jet. All JES uncertainties are propagated into the\nreconstructed pmiss\n\nT in each event.\n\n(ii) b quark fragmentation: The b quark fragmentation\nuncertainty includes two components that are imple-\nmented using event weights. The first component\nstems from the b quark fragmentation function,\nwhich can modeled using the Lund fragmentation\nmodel in the PYTHIA Z2� tune, or tuned to empirical\nresults from the ALEPH [46] and DELPHI [47]\nexperiments. This component is evaluated by com-\nparing the measurement results in MC simulation\nusing these two tunes of the b quark fragmentation\nfunction, with the difference symmetrized to obtain\nthe corresponding uncertainty. The second uncer-\ntainty component stems from the B hadron semi-\nleptonic branching fraction, which has an impact on\n\nTABLE I. Systematic uncertainties for the 2D, 1D, hybrid, and MAOS likelihood fits. The breakdown of JES and b quark\nfragmentation uncertainties into separate components is shown, where the components are added in quadrature to obtain the total. The\n“up” and “down” variations are given separately, with the sign of each variation indicating the direction of the corresponding shift inMt\nor JSF. The ⊛ character highlights the uncertainty sources that are large in at least one of the likelihood fits.\n\nδM2D\nt δJSF2D δM1D\n\nt δMhyb\nt δMMAOS\n\nt\n\n[GeV] [GeV] [GeV] [GeV]\n\nJES (total) ⊛ þ0.06\n−0.10\n\nþ0.007\n−0.006\n\nþ0.54\n−0.55\n\nþ0.43\n−0.46\n\nþ0.65\n−0.70\n\n–In situ þ0.04\n−0.04\n\n−0.002\nþ0.003\n\n−0.22\nþ0.21\n\n−0.18\nþ0.17\n\n−0.28\nþ0.24\n\n–Intercalibration −0.01\nþ0.01\n\n<0.001\n<0.001\n\n−0.04\nþ0.03\n\n−0.03\nþ0.03\n\n−0.04\nþ0.04\n\n–Uncorrelated þ0.04\n−0.04\n\n−0.005\nþ0.005\n\n−0.39\nþ0.39\n\n−0.32\nþ0.31\n\n−0.47\nþ0.47\n\n–Flavor þ0.02\n−0.09\n\nþ0.004\n−0.003\n\nþ0.31\n−0.32\n\nþ0.25\n−0.27\n\nþ0.39\n−0.43\n\nb quark fragmentation (total) ⊛ þ0.39\n−0.39\n\nþ0.001\n−0.001\n\nþ0.40\n−0.40\n\nþ0.40\n−0.40\n\nþ0.67\n−0.67\n\n–Fragmentation function þ0.38\n−0.38\n\n<0.001\n<0.001\n\nþ0.38\n−0.38\n\nþ0.38\n−0.38\n\nþ0.64\n−0.64\n\n–Branching fraction þ0.07\n−0.07\n\nþ0.001\n−0.001\n\nþ0.13\n−0.13\n\nþ0.12\n−0.12\n\nþ0.20\n−0.20\n\nJER −0.03\nþ0.08\n\nþ0.001\n−0.002\n\nþ0.01\n−0.05\n\n<0.00\n−0.03\n\nþ0.04\n−0.04\n\nUnclustered energy þ0.10\n−0.10\n\nþ0.001\n−0.001\n\n−0.02\nþ0.02\n\n−0.04\nþ0.01\n\n−0.11\nþ0.12\n\nPileup −0.06\nþ0.04\n\n<0.001\n<0.001\n\n−0.06\nþ0.05\n\n−0.06\nþ0.05\n\n−0.06\nþ0.05\n\nElectron energy scale −0.38\nþ0.39\n\nþ0.002\n−0.003\n\n−0.21\nþ0.21\n\n−0.24\nþ0.24\n\n−0.02\nþ0.05\n\nMuon momentum scale −0.11\nþ0.09\n\nþ0.001\n<0.001\n\n−0.06\nþ0.05\n\n−0.07\nþ0.06\n\n<0.01\nþ0.01\n\nElectron Id/Iso þ0.07\n−0.02\n\n−0.001\n<0.001\n\nþ0.03\n−0.01\n\nþ0.03\n−0.01\n\nþ0.01\n<0.01\n\nMuon Id/Iso <0.01\n<0.01\n\n<0.001\n<0.001\n\n<0.01\n<0.01\n\n<0.01\n<0.01\n\n<0.01\n<0.01\n\nb tagging þ0.03\n−0.03\n\n<0.001\n−0.001\n\n−0.01\nþ0.01\n\n<0.01\n<0.01\n\n<0.01\n<0.01\n\nTop quark pT reweighting ⊛ þ0.93��� −0.007��� þ0.40��� þ0.51��� þ0.72���\nHard scattering scale ⊛ −0.36\n\nþ0.20\nþ0.007\n−0.003\n\nþ0.31\n−0.49\n\nþ0.21\n−0.47\n\nþ0.33\n−0.08\n\nMatching scale ⊛ −0.86\nþ0.30\n\n−0.004\nþ0.008\n\n−0.25\nþ0.11\n\n−0.37\nþ0.12\n\nþ0.12\n−0.12\n\nUnderlying event tunes ⊛ þ0.56\n−0.56\n\nþ0.007\n−0.007\n\nþ0.08\n−0.08\n\nþ0.11\n−0.11\n\nþ0.09\n−0.09\n\nColor reconnection þ0.06\n−0.06\n\nþ0.001\n−0.001\n\nþ0.15\n−0.15\n\nþ0.13\n−0.13\n\nþ0.16\n−0.16\n\nME generator þ0.18\n−0.18\n\n−0.004\nþ0.002\n\n−0.19\nþ0.07\n\n−0.13\nþ0.07\n\nþ0.11\n−0.07\n\nPDFs þ0.14\n−0.14\n\nþ0.001\n−0.001\n\nþ0.17\n−0.16\n\nþ0.17\n−0.15\n\nþ0.17\n−0.16\n\nTotal þ1.31\n−1.25\n\nþ0.015\n−0.014\n\nþ0.91\n−0.95\n\nþ0.89\n−0.93\n\nþ1.27\n−1.02\n\nMEASUREMENT OF THE TOP QUARK MASS IN THE … PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-11\n\n\n\nthe b quark JES due to the production of a neutrino.\nThe corresponding uncertainty is evaluated by repeat-\ning themeasurementwith branching fractionvalues of\n10.05% and 11.27%, which are variations about the\nnominal value of 10.50% and encompass the range\nof values measured from B hadron decays and their\nuncertainties [22]. Both uncertainty components are\ncombined in quadrature to obtain the total uncertainty.\n\n(iii) Jet energy resolution: The energy resolution of jets is\nknown to be underestimated in MC simulation com-\npared to data. This effect is correctedwith a set of scale\nfactors that are used to smear the jet four-vectors to\nbroaden their resolutions. The scale factors are deter-\nmined in bins of η. Here, they are varied within their\nuncertainties,which are typically 2.5%–5%.Theeffect\nof these variations is also propagated into the pmiss\n\nT .\n(iv) Unclustered energy: The unclustered energy in each\n\nevent comprises the low-pT hadronic activity that is\nnot clustered into a jet. Here, the scale of the\nunclustered energy is varied by �10% [26].\n\n(v) Pileup: The uncertainty in the number of pileup\ninteractions in MC simulation stems from the in-\nstantaneous luminosity in eachbunch crossing and the\neffective inelastic cross section. In this analysis, the\nnumber of pileup interactions in MC is reweighted to\nmatch the data. The pileup uncertainty is evaluated by\nvarying the effective inelastic cross section by �5%.\n\n(vi) Lepton energy scale: The electron energy scale is\nvaried up and down by 0.6% in the ECAL barrel\n(jηj < 1.48) and by 1.5% in the ECAL end cap\n(1.48 < jηj < 3.0) [20]. The muon momentum scale\nis varied up and down by 0.2%. All variations are\npropagated into the pmiss\n\nT .\n(vii) Lepton identification and isolation: Event weights are\n\napplied to adjust the electron and muon yields in MC\nsimulation to account for differences in the identifi-\ncation and isolation efficiencies between data and\nsimulation. For muons, the uncertainty is taken to be\n0.5% of the identification event weight, and 0.2%\nof the isolation event weight [21]. For electrons, the\nuncertainties are estimated in bins ofpT and η, and are\napproximately 0.1%–0.5% of the combined event\nweight for identification and isolation [20].\n\n(viii) b tagging efficiency: Event weights are applied to\nadjust the b jet yields in MC simulation to account\nfor the difference in the b tagging efficiency between\ndata and MC simulation [14]. The uncertainties are\nevaluated in bins of pT and η.\n\n(ix) Top quarkpT reweighting: Event weights are applied\nin order to compensate for a difference in the top\nquark pT spectrum between data and MC simulation\n[48]. The uncertainty is evaluated by comparing the\nmeasurement in MC simulation with and without the\nweights applied. The event weights are not applied in\nthe nominal result. This uncertainty is one sided by\nconstruction, and is not symmetrized.\n\n(x) Hard scattering scale: The factorization scale,\nμF, determines the threshold separating the parton-\nparton hard scattering from softer interactions embod-\nied in the PDFs. The renormalization scale, μR, sets\nthe energy scale at which matrix-element calculations\nare evaluated. Both of these scales are set to μF ¼\nμR ¼ Q in the matrix-element calculation and the\ninitial-state parton shower of the MADGRAPH samples,\nwhereQ2 ¼ Mt\n\n2 þP\np2\nT.Here, the sumruns over all\n\nadditional final state partons in the matrix element.\nThe values of μF and μR are varied simultaneously up\nand down by a factor of 2 to estimate the correspond-\ning uncertainty.\n\n(xi) Matching scale: The matrix element-parton shower\nmatching threshold is used to interface the matrix\nelements generated in MADGRAPH with parton showers\nsimulated in PYTHIA. Its reference value of 20 GeV is\nvaried up and down by a factor of 2.\n\n(xii) Underlying event tunes and color reconnection: The\nunderlying event tunes affect the modeling of soft\nhadronic activity that results from beam remnants\nand multiparton interactions in each event. The\nmeasurement is conducted with a tt̄ sample from\nMC simulation using the “Perugia 2011” tune. It is\ncompared to results using samples with the “Perugia\n2011 mpiHi” and “Perugia 2011 Tevatron” tunes\n[49] in PYTHIA, corresponding to an increased and\ndecreased underlying event activity, respectively.\nThe largest difference is symmetrized to obtain\nthe final uncertainty. The color reconnection (CR)\nuncertainty is evaluated by comparing measurement\nresults using tt̄ samples with the “Perugia 2011” and\n“Perugia 2011 no CR” tunes [49], where CR effects\nare not included in the latter. The difference is\nsymmetrized to obtain the final uncertainty.\n\n(xiii) Matrix-element generator: The measurement is\nrepeated using MC samples produced with the\nPOWHEG event generator, which provides a next-\nto-leading-order calculation of the tt̄ production.\nThese measurement results are compared with the\nreference tt̄ MC sample, generated using MADGRAPH,\nto determine the corresponding uncertainty.\n\n(xiv) Parton distribution functions: Initial-state partons are\ndescribed by PDFs. The corresponding uncertainty\nis evaluated by applying event weights in the MC\nsimulation to reflect the CT10 PDF set [50] with 50\nerror eigenvectors. The total PDF uncertainty is\ndetermined by adding the variations corresponding\nto these error sets in quadrature.\n\nIX. RESULTS AND DISCUSSION\n\nThe results for each version of the likelihood fit, deter-\nmined from 1000 bootstrap pseudo-experiments in each fit,\nare shown in Fig. 7. The 2D fit uses the Mbl and Mbb\n\nT2\nobservables to simultaneously determine the values ofMt and\n\nA. M. SIRUNYAN et al. PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-12\n\n\n\n [GeV]tM\n170 170.5 171 171.5 172 172.5 173\n\nE\nnt\n\nrie\ns \n\n/ 0\n.0\n\n9 \nG\n\neV\n\n0\n\n10\n\n20\n\n30\n\n40\n\n50\n\n60\n\n70\n\n80\n\n90\n\n (8 TeV)-119.7 fb\n\nCMS 2D fit\n\n = 171.56 GeVtM\n = 0.46 GeV\n\ntMσ\n\nJSF\n\n0.99 1 1.01 1.02 1.03 1.04\n\nE\nnt\n\nrie\ns \n\n/ 0\n.0\n\n01\n5\n\n0\n\n20\n\n40\n\n60\n\n80\n\n100\n\n (8 TeV)-119.7 fb\n\nCMS 2D fit\n\nJSF = 1.011 \n = 0.006 JSFσ\n\n [GeV]tM\n172 172.5 173\n\nE\nnt\n\nrie\ns \n\n/ 0\n.0\n\n4 \nG\n\neV\n\n0\n\n20\n\n40\n\n60\n\n80\n\n100\n\n120\n (8 TeV)-119.7 fb\n\nCMS 1D fit\n\n = 172.39 GeVtM\n = 0.17 GeV\n\ntMσ\n\n [GeV]tM\n171 171.5 172\n\nE\nnt\n\nrie\ns \n\n/ 0\n.0\n\n4 \nG\n\neV\n\n0\n\n10\n\n20\n\n30\n\n40\n\n50\n\n60\n\n70\n\n80\n\n90\n\n (8 TeV)-119.7 fb\n\nCMS MAOS fit\n\n = 171.53 GeVtM\n = 0.19 GeV\n\ntMσ\n\n [GeV]tM\n\n172 172.5 173\n\nE\nnt\n\nrie\ns \n\n/ 0\n.0\n\n4 \nG\n\neV\n\n0\n\n20\n\n40\n\n60\n\n80\n\n100\n\n (8 TeV)-119.7 fb\n\nCMS Hybrid fit\n\n = 172.22 GeVtM\n = 0.18 GeV\n\ntMσ\n\nFIG. 7. Likelihood fit results using 1000 bootstrap pseudo-experiments for the (top) 2D fit, (center left) 1D fit, and (center right)\nMAOS fit. (Bottom) Hybrid fit results given by the linear combination in Eq. (9) of the 1D and 2D fits. The error bars represent the\nstatistical uncertainty corresponding to the number of pseudo-experiments in each bin.\n\nMEASUREMENT OF THE TOP QUARK MASS IN THE … PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-13\n\n\n\nJSF, yielding M2D\nt ¼171.56 �0.46ðstatÞþ1.31\n\n−1.25ðsystÞGeV\nand JSF2D¼1.011�0.006ðstatÞþ0.015\n\n−0.014ðsystÞ. The correlation\nbetween theMt and JSF fit parameters in the 2D fit is shown in\nFig. 8, with a correlation coefficient of ρ ¼ −0.94. TheMbl\n\nand Mbb\nT2 distribution shapes corresponding to the fit results\n\nin a typical pseudo-experiment are shown in Fig. 9. The 2D\nfit is successful in mitigating the uncertainty due to the\ndetermination of JES, which is otherwise the largest source\nof systematic uncertainty in this measurement. In particular,\nthis approach is insensitive to the flavor-dependent compo-\nnent of JES uncertainties—stemming from differences in the\nresponse between b jets, light-quark jets, and gluon jets—\nsince predominantly b jets are used for the determination of\nbothMt and JSF parameters. The underlying strategy, rooted\nin a simultaneous fit of two distributions with differing\n\nsensitivities to the JSF, does not rely on any specific\nassumptions about the event topology or final state. For this\nreason, it can be a viable option for JESuncertaintymitigation\nin a variety of physics scenarios.\nThe 1D fit is also based on theMbl andMbb\n\nT2 observables,\nbut constrains the JSF parameter to unity. The 1D fit gives a\nvalue of M1D\n\nt ¼ 172.39� 0.17ðstatÞ þ0.91\n−0.95ðsystÞ GeV. In\n\nthis approach, the JES accounts for the largest source of\nuncertainty. However, other uncertainties are reduced with\nrespect to the 2D fit, resulting in an improved overall\nprecision.\n\n [GeV]tM\n170 170.5 171 171.5 172 172.5 173\n\nJS\nF\n\n0.99\n0.995\n\n1\n\n1.005\n\n1.01\n\n1.015\n\n1.02\n\n1.025\n\n1.03\n\n1.035\n\n1.04\n\n0\n\n10\n\n20\n\n30\n\n40\n\n50\n (8 TeV)-119.7 fb\n\nCMS 2D fit\n\n = -0.94ρ\n\n [GeV]tM\n170 170.5 171 171.5 172 172.5 173\n\nJS\nF\n\n0.99\n\n0.995\n\n1\n\n1.005\n\n1.01\n\n1.015\n\n1.02\n\n1.025\n\n1.03\n\n1.035\n\n1.04\n\n0\n\n20\n\n40\n\n60\n\n80\n\n100\n\n120\n\n140\n\n160\n\n (8 TeV)-119.7 fb\n\nCMS Hybrid fit\n\n = -0.40ρ\n\nFIG. 8. Likelihood fit results corresponding to the 2D fit\n(upper) and hybrid fit (lower), obtained using 1000 pseudo-\nexperiments constructed with the bootstrapping technique. The\nshaded histogram represents the number of pseudo-experiments\nin each bin of Mt and JSF. Two-dimensional contours corre-\nsponding to −2Δ logðLÞ ¼ 1ð4Þ are shown, allowing the con-\nstruction of one (two) σ statistical intervals in Mt and JSF. The\nhybrid fit results are given by a linear combination of the 1D and\n2D fit results using Eq. (9).\n\nE\nnt\n\nrie\ns \n\n/ 1\n.9\n\n G\neV\n\n0\n\n0.5\n\n1\n\n1.5\n\n2\n\n2.5\n\n3\n\n310×  (8 TeV)-119.7 fb\n\nCMS\nblM\n\nData\n\nFit result\n\n [GeV]blM\n50 100 150\n\nD\nat\n\na/\nF\n\nit\n\n0.5\n\n1\n\n1.5\n\nE\nnt\n\nrie\ns \n\n/ 1\n.3\n\n G\neV\n\n0\n\n50\n\n100\n\n150\n\n200\n\n250\n\n300\n\n350\n\n400\n\n450\n\n (8 TeV)-119.7 fb\n\nCMS bb\nT2M\n\nData\n\nFit result\n\n [GeV]bb\nT2M\n\n120 140 160 180 200\n\nD\nat\n\na/\nF\n\nit\n\n0.5\n\n1\n\n1.5\n\nFIG. 9. Maximum-likelihood fit result in a typical pseudo-\nexperiment of the 2D likelihood fit in data. The best fit parameter\nvalues for this pseudo-experiment are Mt ¼ 171.99 GeV and\nJSF ¼ 1.007. When the JSF parameter is constrained to be unity\nin the 1D likelihood fit, the best fit value of Mt is 172.48 GeV.\nThe lower panel shows the ratio between the distribution in data\nand the best fit distribution in simulation.\n\nA. M. SIRUNYAN et al. PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-14\n\n\n\nThe best overall precision is given by the hybrid fit,\nwhich is given by a linear combination of the 1D and 2D fit\nresults. The 1D and 2D fits use the same set of events and\nan identical likelihood function constructed from the Mbl\n\nand Mbb\nT2 observables. These fits are fully correlated, with\n\nthe only difference between them stemming from the\ntreatment of the JSF parameter, which is fixed to unity\nin the 1D fit and acts as a free parameter in the 2D fit. The\nchoice to fix the JSF parameter or allow it to float has an\nimpact on the fit sensitivity to a variety of uncertainty\nsources in addition to the JES. A linear combination of the\n1D and 2D fits with whyb ¼ 0.8, as defined in Eq. (9),\nachieves an optimal balance between all uncertainty\nsources, thus providing the best overall precision. The\nhybrid fit gives\n\nMhyb\nt ¼ 172.22� 0.18ðstatÞ þ0.89\n\n−0.93ðsystÞ GeV:\n\nThe correlation between the Mt and JSF fit parameters\nin the hybrid fit is shown in Fig. 8, with a correlation\ncoefficient of ρ ¼ −0.40.\nThe MAOS fit substitutes the Mbl observable for an\n\nMblν invariant mass, yielding a value of MMAOS\nt ¼\n\n171.54� 0.19ðstatÞ þ1.27\n−1.02ðsystÞ GeV. The MAOS observ-\n\nable presents a new approach for mass reconstruction in a\ndecay topology characterized by underconstrained kin-\nematics. Here, the MAOS fit provides a determination of\nMt that is complementary to the 2D, 1D, and hybrid fits.\nTheMAOSMblν distribution shape corresponding to the fit\nresults in a typical pseudo-experiment is shown in Fig. 10.\n\nThe results for each version of the likelihood fit are\nsummarized in Fig. 11.\n\nX. SUMMARY\n\nA measurement of the top quark mass (Mt) in the\ndileptonic tt̄ decay channel is performed using proton-\nproton collisions at\n\nffiffiffi\ns\n\np ¼ 8 TeV, corresponding to an\nintegrated luminosity of 19.7� 0.5 fb−1. The measurement\nis based on the mass observables Mbl, Mbb\n\nT2, and Mblν,\nwhich allow for mass reconstruction in decay topologies\nthat are kinematically underconstrained. The sensitivity of\nthese observables to the value of Mt is investigated using a\nFisher information density technique. The observables are\nemployed in three versions of an unbinned likelihood fit,\nwhere a Gaussian process technique is used to model the\ncorresponding distribution shapes and their evolution inMt\nand an overall jet energy scale factor (JSF). The Gaussian\nprocess shapes are nonparametric, and allow for a like-\nlihood fitting framework that gives unbiased results. The\n2D fit provides the first simultaneous measurement\nofMt and JSF in the dileptonic channel. It is robust against\nuncertainties due to the determination of jet energy\nscale, including the flavor-dependent uncertainty compo-\nnent arising from differences in the response between\nb jets, light-quark jets, and gluon jets. The fit yields\nMt¼171.56�0.46ðstatÞþ1.31\n\n−1.25ðsystÞGeV and JSF¼1.011�\n0.006ðstatÞþ0.015\n\n−0.014ðsystÞ. The most precise measurement of\nMt is given by a linear combination of this result with a fit\nin which the JSF is constrained to be unity, yielding a value\n\nE\nnt\n\nrie\ns \n\n/ 2\n.7\n\n G\neV\n\n1\n\n2\n\n3\n\n4\n\n5\n\n6\n310×  (8 TeV)-119.7 fb\n\nCMS\nνblM\n\nData\n\nFit result\n\n [GeV]νblM\n100 150 200 250 300\n\nD\nat\n\na/\nF\n\nit\n\n0.9\n\n1\n\n1.1\n\nFIG. 10. The MAOS Mblν distribution corresponding to the\nmaximum-likelihood fit result in a typical pseudo-experiment of\nthe MAOS likelihood fit in data. The best fit value of Mt for this\npseudo-experiment is 171.54 GeV. The lower panel shows the\nratio between the distribution in data and the best fit distribution\nin simulation.\n\n [GeV]tM\n\n160 165 170 175 180 185\n\n1D fit\n\n2D fit\n\nHybrid fit\n\nMAOS fit\n\nCMS 2012, dilepton\nPRD 93, 2016, 072004\n\nCMS combination\nPRD 93, 2016, 072004\n\n  GeV 0.95−\n 0.91+ 0.17 ±172.39\n\n  GeV 1.25−\n 1.31+ 0.46 ±171.56\n\n  GeV 0.93−\n 0.89+ 0.18 ±172.22\n\n  GeV 1.02−\n 1.27+ 0.19 ±171.54\n\n 1.22 GeV± 0.19 ±172.82\n\n 0.47 GeV± 0.13 ±172.44\n\n syst)± stat ±(value\n\n (8 TeV)-119.7 fb\n\nCMS\n\nFIG. 11. Summary of the 1D, 2D, hybrid, and MAOS like-\nlihood fit results using the 2012 data set at\n\nffiffiffi\ns\n\np ¼ 8 TeV,\ncorresponding to an integrated luminosity of 19.7� 0.5 fb−1.\nA recent dileptonic channel measurement using the 2012 data\nset and the most recent combination of Mt measurements by\nCMS in all tt̄ decay channels [5] are shown below the dashed line\nfor reference.\n\nMEASUREMENT OF THE TOP QUARK MASS IN THE … PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-15\n\n\n\nof 172.22� 0.18ðstatÞ þ0.89\n−0.93ðsystÞ GeV. This measurement\n\nachieves a 25% improvement in overall precision on Mt\ncompared to previous dileptonic channel analyses using the\n2012 data set at CMS. The improvement can be attributed\nto a reduction of the systematic uncertainties in the\nmeasurement.\n\nACKNOWLEDGMENTS\n\nWe congratulate our colleagues in the CERN accelerator\ndepartments for the excellent performance of the LHC and\nthank the technical and administrative staffs at CERN and\nat other CMS institutes for their contributions to the success\nof the CMS effort. In addition, we gratefully acknowledge\nthe computing centers and personnel of the Worldwide\nLHC Computing Grid for delivering so effectively the\ncomputing infrastructure essential to our analyses. Finally,\nwe acknowledge the enduring support for the construction\nand operation of the LHC and the CMS detector provided\nby the following funding agencies: BMWFW and FWF\n(Austria); FNRS and FWO (Belgium); CNPq, CAPES,\nFAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN;\nCAS, MoST, and NSFC (China); COLCIENCIAS\n(Colombia); MSES and CSF (Croatia); RPF (Cyprus);\nSENESCYT (Ecuador); MoER, ERC IUT, and ERDF\n(Estonia); Academy of Finland, MEC, and HIP\n(Finland); CEA and CNRS/IN2P3 (France); BMBF,\nDFG, and HGF (Germany); GSRT (Greece); OTKA and\nNIH (Hungary); DAE and DST (India); IPM (Iran); SFI\n(Ireland); INFN (Italy); MSIP and NRF (Republic of\nKorea); LAS (Lithuania); MOE and UM (Malaysia);\nBUAP, CINVESTAV, CONACYT, LNS, SEP, and\nUASLP-FAI (Mexico); MBIE (New Zealand); PAEC\n(Pakistan); MSHE and NSC (Poland); FCT (Portugal);\nJINR (Dubna); MON, RosAtom, RAS, RFBR and RAEP\n(Russia); MESTD (Serbia); SEIDI, CPAN, PCTI and\nFEDER (Spain); Swiss Funding Agencies (Switzerland);\nMST (Taipei); ThEPCenter, IPST, STAR, and NSTDA\n(Thailand); TUBITAK and TAEK (Turkey); NASU and\nSFFR (Ukraine); STFC (United Kingdom); DOE and NSF\n(USA). Individuals have received support from the Marie-\nCurie program and the European Research Council and\nEPLANET (European Union); the Leventis Foundation;\nthe A. P. Sloan Foundation; the Alexander von Humboldt\nFoundation; the Belgian Federal Science Policy Office; the\nFonds pour la Formation à la Recherche dans l’Industrie\net dans l’Agriculture (FRIA-Belgium); the Agentschap\nvoor Innovatie door Wetenschap en Technologie (IWT-\nBelgium); the Ministry of Education, Youth and Sports\n(MEYS) of the Czech Republic; the Council of Science and\nIndustrial Research, India; the HOMING PLUS program\nof the Foundation for Polish Science, cofinanced from\nEuropean Union, Regional Development Fund, the\nMobility Plus program of the Ministry of Science and\nHigher Education, the National Science Center (Poland),\nContracts Harmonia No. 2014/14/M/ST2/00428, Opus\n\nNo. 2014/13/B/ST2/02543, No. 2014/15/B/ST2/03998,\nand No. 2015/19/B/ST2/02861, Sonata-bis No. 2012/07/\nE/ST2/01406; the National Priorities Research Program\nby Qatar National Research Fund; the Programa Clarín-\nCOFUND del Principado de Asturias; the Thalis and\nAristeia programs cofinanced by EU-ESF and the\nGreek NSRF; the Rachadapisek Sompot Fund for\nPostdoctoral Fellowship, Chulalongkorn University and\nthe Chulalongkorn Academic into Its 2nd Century\nProject Advancement Project (Thailand); and the Welch\nFoundation, Contract No. C-1845.\n\nAPPENDIX A: STATISTICAL SENSITIVITY OF\nKINEMATIC OBSERVABLES\n\nThe sensitivity of a kinematic observable to the value\nof a parameter such as Mt can be quantified by its Fisher\ninformation [51,52]. The Fisher information of an observ-\nable is related to its likelihood function, L, which we have\nintroduced in Eq. (7) and reproduce here:\n\nlogLðmÞ ¼\nXN\ni\n\nlog fðxijmÞ; ðA1Þ\n\nwhere fðxjmÞ is the distribution of observable x normalized\nto unity over its range, m is a free parameter, and N is\nthe number of observations of x. In this measurement, we\nhave x ¼ Mbl, Mbb\n\nT2, or Mblν, m ¼ Mt or JSF, and N is a\nmultiple of the total number of events. For simplicity we\nconsider the distribution shape f as a function of only one\nfree parameter. The Fisher information corresponding to\nthe shape fðxjmÞ is given by\n\nIðmÞ ¼\nZ � ∂\n\n∂m log fðxjmÞ\n�\n\n2\n\nfðxjmÞdx: ðA2Þ\n\nThe quantity IðmÞ provides a measure of curvature near the\nlikelihood maximum. It can be interpreted as the variance\nof the slope, ð∂ log fðxjmÞ=∂mÞ, known as the “statistical\nscore” of fðxjmÞ.\nThe Fisher information is related to the precision of a\n\nmeasurement by the Crámer-Rao bound:\n\nσm\n2 ≥\n\n1\n\nNIðmÞ ; ðA3Þ\n\nwhere σm is the statistical uncertainty on parameter m. In a\nlikelihood with large N, the shape of the likelihood near its\nmaximum is roughly Gaussian, and the bound approaches\nan equality. This expression confirms the expected rela-\ntionship σm ∝ 1=\n\nffiffiffiffi\nN\n\np\nbetween the statistical uncertainty\n\nand the value of N, but also reveals the proportionality\nfactor as the reciprocal of the Fisher information. It\nexpresses the uncertainty σm in terms of the total number\nof events, the shape f, and the derivative ∂f=∂m.\n\nA. M. SIRUNYAN et al. PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-16\n\n\n\nThe Fisher information also provides a mathematical\nframework for quantifying the sensitivity of an observable\nat a specific point on its shape. In this analysis, theMbl and\nMbb\n\nT2 observables have kinematic end points at approxi-\nmately\n\nffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi\nM2\n\nt −M2\nW\n\np\nandMt, respectively; the MAOSMblν\n\nobservable is an invariant mass whose shape contains a\npeak near the value of Mt. Because these features carry a\ndependence on the value of Mt, the regions near the end\npoints of Mbl and Mbb\n\nT2 and the peak of Mblν are expected\nto contribute significantly to the sensitivity of these\nobservables. To relate these local features to the Fisher\ninformation, we consider the integral in Eq. (A2) over the\nvalue of observable x. Here, the integrand of the Fisher\ninformation can be interpreted as the contribution to the\ntotal sensitivity stemming from a specific value of x.\nRewriting the integrand in a more convenient form, we\ndefine the local shape sensitivity function by\n\nsðxjmÞ≡ 1\n\nfðxjmÞ\n�∂fðxjmÞ\n\n∂m\n�\n2\n\n: ðA4Þ\n\nThis function is also known as the Fisher information\ndensity. It is shown for the Mbl, Mbb\n\nT2, and MAOS Mblν\nobservables in Figs. 1, 3, and 4, respectively, with m ¼ Mt\nand the JSF parameter fixed to unity. It is observed to peak\nnear the kinematic end points of Mbl and Mbb\n\nT2, and on the\nleft-side edge of Mblν. The values of x where sðxjmÞ ¼ 0\ncoincide with the stationary points at which the distribution\nshapes in Figs. 1, 3, and 4 intersect. This is a reflection of\nthe fact that in a likelihood fit, events with a value of x near\na stationary point make little or no contribution to the\ndetermination ofm. In general, the shape of sðxjmÞ for each\nobservable establishes a link between the underlying\nkinematic properties of the observable and regions of high\nand low sensitivity on its shape. In this analysis, it provides\nheuristic information about theMbl,Mbb\n\nT2, andMAOSMblν\ndistributions, and their sensitivity to the value of Mt.\nIn addition to providing heuristic information, the local\n\nshape sensitivity function is used in this analysis to identify\npotential overfitting effects in the Gaussian process (GP)\nshapes. Overfitting occurs when the interpolation between\nGP training points is not smooth, causing fluctuations in\nthe shape that may be difficult to identify by eye. Such\nfluctuations can be a source of bias, both in the determi-\nnation of Mt and its corresponding uncertainties. A typical\nsymptom of overfitting is an underestimated statistical\nuncertainty on the value of Mt. This can occur when\nfluctuations in the GP shape increase the value of the slope\n∂fðxjMtÞ=∂Mt appearing in Eq. (A2), thus artificially\nincreasing the Fisher information of the corresponding\nshape. The issue is easily revealed by the shape of sðxjMtÞ,\nwhich acquires visible fluctuations when overfitting is\nindeed present. In such cases, overfitting can be mitigated\nby increasing relevant GP hyperparameter values to\nimprove the smoothness of the GP shape.\n\nAPPENDIX B: GAUSSIAN PROCESS\nREGRESSION TECHNIQUE\n\nThe likelihood fit described in Sec. VII uses distribution\nshapes of the form fðxjMt; JSFÞ, where x is the value of an\nobservable (Mbl, Mbb\n\nT2, or Mblν), and Mt and JSF are free\nparameters in the fit. In this analysis, the distribution shapes\nf are modeled with a Gaussian process (GP) regression\ntechnique. We define a point, ui, on each distribution shape\nby its position in x, Mt, and JSF:\n\nui ≡ ðxi;Mti; JSFiÞ: ðB1Þ\n\nThe value of the shape at ui is given by fðuiÞ ¼\nfðxijMti; JSFiÞ. The point ui can be a training point, at\nwhich the value of f is known and used as an input into the\nGP regression process; or it can be a test point, at which the\nvalue of f is to be determined. Each GP shape is trained\nusing binned distributions of the observable x in MC\nsimulation. For each observable, 35 binned distributions\nare used, corresponding to seven values of MMC\n\nt ranging\nfrom 166.5 to 178.5 GeV and five values of JSF ranging\nfrom 0.97 to 1.03. Each distribution has 75 bins in x,\nyielding a total of 2625 training points. This binning\nscheme is chosen to provide an accurate modeling of the\ndistribution shapes, while mitigating the effects of statis-\ntical fluctuations. The GP regression technique interpolates\nbetween the discrete values of x, Mt, and JSF covered by\nthese training points to provide a shape that is smooth over\nits range.\nThe “Gaussian” in GP refers to the distribution of\n\npossible values of the shape f. The value at a single point,\nfðuiÞ, is distributed according to a one-dimensional\nGaussian function rather than being treated as an exact\nquantity. The mean of this Gaussian function is the most\nprobable value of the shape at that point ui, and it is the\nvalue used for likelihood fitting (Sec. VII); the variance\nstems from the modeling uncertainty inherent in the GP\nregression process. The values fðuiÞ and fðujÞ at any two\npoints follow a two-dimensional Gaussian distribution and\nare related by a covariance. The correlation between fðuiÞ\nand fðujÞ determines the degree to which the GP shape\nis allowed to vary between the points ui and uj. By\nextension, any N values of the shape are described by an\nN-dimensional Gaussian distribution, and are related by an\nN × N covariance matrix. To determine the value of the\nshape at a test point uNþ1, an (N þ 1)-dimensional\nGaussian distribution is constructed relating the training\npoint values fðu1Þ…fðuNÞ to the test point value fðuNþ1Þ.\nThen, fðu1Þ…fðuNÞ are fixed to their known values, and\nthe (N þ 1)-dimensional Gaussian distribution is reduced\nto a one-dimensional conditional Gaussian distribution\nrepresenting the possible values of fðuNþ1Þ.\nTo demonstrate this process graphically, we consider a\n\nsimple GP with one training point, utrain, at which the value\n\nMEASUREMENT OF THE TOP QUARK MASS IN THE … PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-17\n\n\n\nfðutrainÞ is known, and one test point, utest, at which the\nvalue fðutestÞ is to be evaluated. The values of fðutrainÞ and\nfðutestÞ follow a two-dimensional Gaussian prior distribu-\ntion with mean values μtrain and μtest, and a covariance\nrepresented by\n\nC ¼\n�\n\nσ2train ρσtrainσtest\n\nρσtrainσtest σ2test\n\n�\n; ðB2Þ\n\nwhere σ2train and σ2test are the variances of fðutrainÞ and\nfðutestÞ, and ρ is the correlation coefficient. We set μtrain ¼\nμtest ¼ 0 to reflect our zero prior knowledge of f over its\nrange. The resulting joint Gaussian distribution is repre-\nsented by the contours in Fig. 12. To evaluate the shape f at\nthe test point, we fix fðutrainÞ to its known value, indicated\nby the square point in Fig. 12. The possible values of\n\nfðutestÞ are now constrained to lie along the horizontal line,\ngiving rise to the conditional Gaussian distribution indi-\ncated by the dashed curve. The mean of the conditional\nGaussian is taken to be the value of the shape at the\ntest point.\nIn this analysis, the conditioning process described\n\nabove is generalized to N þ 1 dimensions to accommodate\nall N training points and one test point at which the shape f\nis evaluated. The mean, μNþ1, and variance, σ2Nþ1, of f at\ntest point uNþ1 are given by\n\nμNþ1 ¼ kTC−1\nN t; ðB3Þ\n\nσ2Nþ1 ¼ c − kTC−1\nN k; ðB4Þ\n\nwhere t is a column vector containing the fðuiÞ values\nfor all N training points, k ¼ covðfðuiÞ; fðuNþ1ÞÞ is the\ncovariance between the value of f at the ith training point\nand the value at the test point, and c ¼ covðfðuNþ1Þ;\nfðuNþ1ÞÞ. The matrix CN ¼ covðfðuiÞ; fðujÞÞ is the\nN × N covariance matrix expressing the joint Gaussian\ndistribution between the values of f at all N training points.\nIn this analysis, the value of f at each point is given by the\nmean defined in Eq. (B3). The variance in Eq. (B4) is\nprovided here for completeness.\nThe covariance covðfðuiÞ; fðujÞÞ between any two\n\npoints is determined by a kernel function that is set by\nthe analyzer. The kernel function defines the covariance\nmatrix CN in Eqs. (B3) and (B4), and its properties\ndetermine the smoothness characteristics of the final shape.\nA conventional choice for the GP kernel function is a\nGaussian—this ensures that the correlation between any\ntwo points is suppressed at a large separation. In practice,\nthe kernel is a three-dimensional function that controls the\nsmoothness of the shape along x, Mt, and JSF. It also\nincludes a correlation term between Mt and JSF to reflect\nthe kinematic relationship between them. The result is a\nproduct of a one-dimensional Gaussian (controlling the\nsmoothness along x) with a two-dimensional Gaussian\n(controlling the smoothness along Mt and JSF). For any\ntwo points ui and uj on the shape, the kernel is given by\n\ncovðfðuiÞ; fðujÞÞ ¼ N1\n\n�\nN2 exp\n\n�\n−\n\n1\n\n2θ21\nðxi − xjÞ2\n\n�\nexp\n\n�\n−\n\n1\n\n2ð1 − ρ2Þ\n�\n1\n\nθ22\nðMti −MtjÞ2 þ\n\n1\n\nθ23\nðJSFi − JSFjÞ2\n\n−\n2ρ\n\nθ2θ3\nðMti −MtjÞðJSFi − JSFjÞ\n\n��\nþ σ2i δij\n\n�\n: ðB5Þ\n\nHere, N1, N2, θ1, θ2, θ3, and ρ are the GP hyperparameters,\nσi is a noise parameter that accounts for the statistical\nuncertainty on the distribution bin underlying each training\npoint, and δij is the Kronecker delta function. The terms\ninside the exponentials specify the covariance between any\n\ntwo values of the shape as a function of their corresponding\nx, Mt, and JSF. The hyperparameters θ1, θ2, and θ3 specify\nthe length scales over which the GP shape is allowed to\nvary, and ρ is a correlation coefficient that couples the Mt\nand JSF parameters. The hyperparameter N1 specifies the\n\n)testuf(\n1− 0 1\n\n)\ntr\n\nai\nn\n\nu\nf(\n\n1−\n\n0\n\n1\n\nFIG. 12. Demonstration of the GP conditioning process, given\nin Eqs. (B3) and (B4), for one training point and one test point.\nThe covariance between the value of the shape at the training and\ntest point is represented by the ellipse. The known value of the\nshape at the training point (square point) determines the mean\nvalue of the shape at the test point (round point and vertical line).\nThe distribution of possible values of the shape at the test point is\nrepresented by the dashed curve.\n\nA. M. SIRUNYAN et al. PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-18\n\n\n\noverall normalization of the kernel function, and N2\n\ndetermines the relative normalization between the Gaussian\nand noise terms.\nThe values of all hyperparameters are determined with\n\nthe help of a cross-validation likelihood fit [12], conducted\nfor each observable separately. 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Kousouris,46 I. Evangelou,47 G. Flouris,47 C. Foudas,47 P. Kokkas,47 N. Loukas,47 N. Manthos,47\n\nI. Papadopoulos,47 E. Paradas,47 N. Filipovic,48 G. Pasztor,48 G. Bencze,49 C. Hajdu,49 D. Horvath,49,s F. Sikler,49\n\nV. Veszpremi,49 G. Vesztergombi,49,t A. J. Zsigmond,49 N. Beni,50 S. Czellar,50 J. Karancsi,50,u A. Makovec,50 J. Molnar,50\n\nZ. Szillasi,50 M. Bartók,51,t P. Raics,51 Z. L. Trocsanyi,51 B. Ujvari,51 S. Choudhury,52 J. R. Komaragiri,52 S. Bahinipati,53,v\n\nS. Bhowmik,53,w P. Mal,53 K. Mandal,53 A. Nayak,53,x D. K. Sahoo,53,v N. Sahoo,53 S. K. Swain,53 S. Bansal,54 S. B. Beri,54\n\nV. Bhatnagar,54 R. Chawla,54 U. Bhawandeep,54 A. K. Kalsi,54 A. Kaur,54 M. Kaur,54 R. Kumar,54 P. Kumari,54 A. Mehta,54\n\nM. Mittal,54 J. B. Singh,54 G. Walia,54 Ashok Kumar,55 A. Bhardwaj,55 B. C. Choudhary,55 R. B. Garg,55 S. Keshri,55\n\nA. Kumar,55 S. Malhotra,55 M. Naimuddin,55 K. Ranjan,55 R. Sharma,55 V. Sharma,55 R. Bhattacharya,56 S. Bhattacharya,56\n\nK. Chatterjee,56 S. Dey,56 S. Dutt,56 S. Dutta,56 S. Ghosh,56 N. Majumdar,56 A. Modak,56 K. Mondal,56 S. Mukhopadhyay,56\n\nS. Nandan,56 A. Purohit,56 A. Roy,56 D. Roy,56 S. Roy Chowdhury,56 S. Sarkar,56 M. Sharan,56 S. Thakur,56 P. K. Behera,57\n\nR. Chudasama,58 D. Dutta,58 V. Jha,58 V. Kumar,58 A. K. Mohanty,58,o P. K. Netrakanti,58 L. M. Pant,58 P. Shukla,58\n\nA. Topkar,58 T. Aziz,59 S. Dugad,59 G. Kole,59 B. Mahakud,59 S. Mitra,59 G. B. Mohanty,59 B. Parida,59 N. Sur,59 B. Sutar,59\n\nS. Banerjee,60 R. K. Dewanjee,60 S. Ganguly,60 M. Guchait,60 Sa. Jain,60 S. Kumar,60 M. Maity,60,w G. Majumder,60\n\nK. Mazumdar,60 T. Sarkar,60,w N. Wickramage,60,y S. Chauhan,61 S. Dube,61 V. Hegde,61 A. Kapoor,61 K. Kothekar,61\n\nS. Pandey,61 A. Rane,61 S. Sharma,61 S. Chenarani,62,z E. Eskandari Tadavani,62 S. M. Etesami,62,z M. Khakzad,62\n\nM. Mohammadi Najafabadi,62 M. Naseri,62 S. Paktinat Mehdiabadi,62,aa F. Rezaei Hosseinabadi,62 B. Safarzadeh,62,bb\n\nM. Zeinali,62 M. Felcini,63 M. Grunewald,63 M. Abbrescia,64a,64b C. Calabria,64a,64b C. Caputo,64a,64b A. Colaleo,64a\n\nD. Creanza,64a,64c L. Cristella,64a,64b N. De Filippis,64a,64c M. De Palma,64a,64b L. Fiore,64a G. Iaselli,64a,64c G. Maggi,64a,64c\n\nM. Maggi,64a G. Miniello,64a,64b S. My,64a,64b S. Nuzzo,64a,64b A. Pompili,64a,64b G. Pugliese,64a,64c R. Radogna,64a,64b\n\nA. Ranieri,64a G. Selvaggi,64a,64b A. Sharma,64a L. Silvestris,64a,o R. Venditti,64a,64b P. Verwilligen,64a G. Abbiendi,65a\n\nC. Battilana,65a D. Bonacorsi,65a,65b S. Braibant-Giacomelli,65a,65b L. Brigliadori,65a,65b R. Campanini,65a,65b\n\nP. Capiluppi,65a,65b A. Castro,65a,65b F. R. Cavallo,65a S. S. Chhibra,65a,65b G. Codispoti,65a,65b M. Cuffiani,65a,65b\n\nG. M. Dallavalle,65a F. Fabbri,65a A. Fanfani,65a,65b D. Fasanella,65a,65b P. Giacomelli,65a C. Grandi,65a L. Guiducci,65a,65b\n\nS. Marcellini,65a G. Masetti,65a A. Montanari,65a F. L. Navarria,65a,65b A. Perrotta,65a A. M. Rossi,65a,65b T. Rovelli,65a,65b\n\nG. P. Siroli,65a,65b N. Tosi,65a,65b,o S. Albergo,66a,66b S. Costa,66a,66b A. Di Mattia,66a F. Giordano,66a,66b R. Potenza,66a,66b\n\nA. Tricomi,66a,66b C. Tuve,66a,66b G. Barbagli,67a V. Ciulli,67a,67b C. Civinini,67a R. D’Alessandro,67a,67b E. Focardi,67a,67b\n\nP. Lenzi,67a,67b M. Meschini,67a S. Paoletti,67a L. Russo,67a,cc G. Sguazzoni,67a D. Strom,67a L. Viliani,67a,67b,o L. Benussi,68\n\nS. Bianco,68 F. Fabbri,68 D. Piccolo,68 F. Primavera,68,o V. Calvelli,69a,69b F. Ferro,69a M. R. Monge,69a,69b E. Robutti,69a\n\nS. Tosi,69a,69b L. Brianza,70a,70b,o F. Brivio,70a,70b V. Ciriolo,70a M. E. Dinardo,70a,70b S. Fiorendi,70a,70b,o S. Gennai,70a\n\nA. Ghezzi,70a,70b P. Govoni,70a,70b M. Malberti,70a,70b S. Malvezzi,70a R. A. Manzoni,70a,70b D. Menasce,70a L. Moroni,70a\n\nM. Paganoni,70a,70b D. Pedrini,70a S. Pigazzini,70a,70b S. Ragazzi,70a,70b T. Tabarelli de Fatis,70a,70b S. Buontempo,71a\n\nN. Cavallo,71a,71c G. De Nardo,71a S. Di Guida,71a,71d,o M. Esposito,71a,71b F. Fabozzi,71a,71c F. Fienga,71a,71b\n\nA. O. M. Iorio,71a,71b G. Lanza,71a L. Lista,71a S. Meola,71a,71d,o P. Paolucci,71a,o C. Sciacca,71a,71b F. Thyssen,71a P. Azzi,72a,o\n\nN. Bacchetta,72a L. Benato,72a,72b D. Bisello,72a,72b A. Boletti,72a,72b R. Carlin,72a,72b P. Checchia,72a M. Dall’Osso,72a,72b\n\nP. De Castro Manzano,72a T. Dorigo,72a U. Dosselli,72a F. Gasparini,72a,72b U. Gasparini,72a,72b S. Lacaprara,72a\n\nM. Margoni,72a,72b A. T. Meneguzzo,72a,72b J. Pazzini,72a,72b N. Pozzobon,72a,72b P. Ronchese,72a,72b R. Rossin,72a,72b\n\nF. Simonetto,72a,72b E. Torassa,72a S. Ventura,72a M. Zanetti,72a,72b P. Zotto,72a,72b G. Zumerle,72a,72b A. Braghieri,73a\n\nF. Fallavollita,73a,73b A. Magnani,73a,73b P. Montagna,73a,73b S. P. Ratti,73a,73b V. Re,73a M. Ressegotti,73a C. Riccardi,73a,73b\n\nP. Salvini,73a I. Vai,73a,73b P. Vitulo,73a,73b L. Alunni Solestizi,74a,74b G. M. Bilei,74a D. Ciangottini,74a,74b L. Fanò,74a,74b\n\nP. Lariccia,74a,74b R. Leonardi,74a,74b G. Mantovani,74a,74b V. Mariani,74a,74b M. Menichelli,74a A. Saha,74a A. Santocchia,74a,74b\n\nK. Androsov,75a,cc P. Azzurri,75a,o G. Bagliesi,75a J. Bernardini,75a T. Boccali,75a R. Castaldi,75a M. A. Ciocci,75a,75b,cc\n\nA. M. SIRUNYAN et al. PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-22\n\n\n\nR. Dell’Orso,75a G. Fedi,75a A. Giassi,75a M. T. Grippo,75a,cc F. Ligabue,75a,75c T. Lomtadze,75a L. Martini,75a,75b\n\nA. Messineo,75a,75b F. Palla,75a A. Rizzi,75a,75b A. Savoy-Navarro,75a,dd P. Spagnolo,75a R. Tenchini,75a G. Tonelli,75a,75b\n\nA. Venturi,75a P. G. Verdini,75a L. Barone,76 F. Cavallari,76 M. Cipriani,76 D. Del Re,76,o M. Diemoz,76 S. Gelli,76 E. Longo,76\n\nF. Margaroli,76 B. Marzocchi,76 P. Meridiani,76 G. Organtini,76 R. Paramatti,76 F. Preiato,76 S. Rahatlou,76 C. Rovelli,76\n\nF. Santanastasio,76 N. Amapane,77a,77b R. Arcidiacono,77a,77c,o S. Argiro,77a,77b M. Arneodo,77a,77c N. Bartosik,77a\n\nR. Bellan,77a,77b C. Biino,77a N. Cartiglia,77a F. Cenna,77a,77b M. Costa,77a,77b R. Covarelli,77a,77b A. Degano,77a,77b\n\nN. Demaria,77a B. Kiani,77a,77b C. Mariotti,77a S. Maselli,77a E. Migliore,77a,77b V. Monaco,77a,77b E. Monteil,77a,77b\n\nM. Monteno,77a M. M. Obertino,77a,77b L. Pacher,77a,77b N. Pastrone,77a M. Pelliccioni,77a G. L. Pinna Angioni,77a,77b\n\nF. Ravera,77a,77b A. Romero,77a,77b M. Ruspa,77a,77c R. Sacchi,77a,77b K. Shchelina,77a,77b V. Sola,77a A. Solano,77a,77b\n\nA. Staiano,77a P. Traczyk,77a,77b S. Belforte,78a M. Casarsa,78a F. Cossutti,78a G. Della Ricca,78a,78b A. Zanetti,78a D. H. Kim,79\n\nG. N. Kim,79 M. S. Kim,79 J. Lee,79 S. Lee,79 S. W. Lee,79 Y. D. Oh,79 S. Sekmen,79 D. C. Son,79 Y. C. Yang,79 A. Lee,80\n\nH. Kim,81 J. A. Brochero Cifuentes,82 T. J. Kim,82 S. Cho,83 S. Choi,83 Y. Go,83 D. Gyun,83 S. Ha,83 B. Hong,83 Y. Jo,83\n\nY. Kim,83 K. Lee,83 K. S. Lee,83 S. Lee,83 J. Lim,83 S. K. Park,83 Y. Roh,83 J. Almond,84 J. Kim,84 H. Lee,84 S. B. Oh,84\n\nB. C. Radburn-Smith,84 S. h. Seo,84 U. K. Yang,84 H. D. Yoo,84 G. B. Yu,84 M. Choi,85 H. Kim,85 J. H. Kim,85 J. S. H. Lee,85\n\nI. C. Park,85 G. Ryu,85 M. S. Ryu,85 Y. Choi,86 J. Goh,86 C. Hwang,86 J. Lee,86 I. Yu,86 V. Dudenas,87 A. Juodagalvis,87\n\nJ. Vaitkus,87 I. Ahmed,88 Z. A. Ibrahim,88 M. A. B. Md Ali,88,ee F. Mohamad Idris,88,ff W. A. T. Wan Abdullah,88\n\nM. N. Yusli,88 Z. Zolkapli,88 H. Castilla-Valdez,89 E. De La Cruz-Burelo,89 I. Heredia-De La Cruz,89,gg\n\nA. Hernandez-Almada,89 R. Lopez-Fernandez,89 R. Magaña Villalba,89 J. Mejia Guisao,89 A. Sanchez-Hernandez,89\n\nS. Carrillo Moreno,90 C. Oropeza Barrera,90 F. Vazquez Valencia,90 S. Carpinteyro,91 I. Pedraza,91 H. A. Salazar Ibarguen,91\n\nC. Uribe Estrada,91 A. Morelos Pineda,92 D. Krofcheck,93 P. H. Butler,94 A. Ahmad,95 M. Ahmad,95 Q. Hassan,95\n\nH. R. Hoorani,95 W. A. Khan,95 A. Saddique,95 M. A. Shah,95 M. Shoaib,95 M. Waqas,95 H. Bialkowska,96 M. Bluj,96\n\nB. Boimska,96 T. Frueboes,96 M. Górski,96 M. Kazana,96 K. Nawrocki,96 K. Romanowska-Rybinska,96 M. Szleper,96\n\nP. Zalewski,96 K. Bunkowski,97 A. Byszuk,97,hh K. Doroba,97 A. Kalinowski,97 M. Konecki,97 J. Krolikowski,97\n\nM. Misiura,97 M. Olszewski,97 A. Pyskir,97 M. Walczak,97 P. Bargassa,98 C. Beirão Da Cruz E Silva,98 B. Calpas,98\n\nA. Di Francesco,98 P. Faccioli,98 M. Gallinaro,98 J. Hollar,98 N. Leonardo,98 L. Lloret Iglesias,98 M. V. Nemallapudi,98\n\nJ. Seixas,98 O. Toldaiev,98 D. Vadruccio,98 J. Varela,98 S. Afanasiev,99 P. Bunin,99 M. Gavrilenko,99 I. Golutvin,99\n\nI. Gorbunov,99 A. Kamenev,99 V. Karjavin,99 A. Lanev,99 A. Malakhov,99 V. Matveev,99,ii,jj V. Palichik,99 V. Perelygin,99\n\nS. Shmatov,99 S. Shulha,99 N. Skatchkov,99 V. Smirnov,99 N. Voytishin,99 A. Zarubin,99 L. Chtchipounov,100 V. Golovtsov,100\n\nY. Ivanov,100 V. Kim,100,kk E. Kuznetsova,100,ll V. Murzin,100 V. Oreshkin,100 V. Sulimov,100 A. Vorobyev,100 Yu. Andreev,101\n\nA. Dermenev,101 S. Gninenko,101 N. Golubev,101 A. Karneyeu,101 M. Kirsanov,101 N. Krasnikov,101 A. Pashenkov,101\n\nD. Tlisov,101 A. Toropin,101 V. Epshteyn,102 V. Gavrilov,102 N. Lychkovskaya,102 V. Popov,102 I. Pozdnyakov,102\n\nG. Safronov,102 A. Spiridonov,102 M. Toms,102 E. Vlasov,102 A. Zhokin,102 T. Aushev,103 A. Bylinkin,103,jj\n\nM. Chadeeva,104,mm O. Markin,104 E. Tarkovskii,104 V. Andreev,105 M. Azarkin,105,jj I. Dremin,105,jj M. Kirakosyan,105\n\nA. Leonidov,105,jj A. Terkulov,105 A. Baskakov,106 A. Belyaev,106 E. Boos,106 V. Bunichev,106 M. Dubinin,106,nn L. Dudko,106\n\nV. Klyukhin,106 O. Kodolova,106 N. Korneeva,106 I. Lokhtin,106 I. Miagkov,106 S. Obraztsov,106 M. Perfilov,106 V. Savrin,106\n\nP. Volkov,106 V. Blinov,107,oo Y. Skovpen,107,oo D. Shtol,107,oo I. Azhgirey,108 I. Bayshev,108 S. Bitioukov,108 D. Elumakhov,108\n\nV. Kachanov,108 A. Kalinin,108 D. Konstantinov,108 V. Krychkine,108 V. Petrov,108 R. Ryutin,108 A. Sobol,108 S. Troshin,108\n\nN. Tyurin,108 A. Uzunian,108 A. Volkov,108 P. Adzic,109,pp P. Cirkovic,109 D. Devetak,109 M. Dordevic,109 J. Milosevic,109\n\nV. Rekovic,109 J. Alcaraz Maestre,110 M. Barrio Luna,110 E. Calvo,110 M. Cerrada,110 M. Chamizo Llatas,110 N. Colino,110\n\nB. De La Cruz,110 A. Delgado Peris,110 A. Escalante Del Valle,110 C. Fernandez Bedoya,110 J. P. Fernández Ramos,110\n\nJ. Flix,110 M. C. Fouz,110 P. Garcia-Abia,110 O. Gonzalez Lopez,110 S. Goy Lopez,110 J. M. Hernandez,110 M. I. Josa,110\n\nE. Navarro De Martino,110 A. Pérez-Calero Yzquierdo,110 J. Puerta Pelayo,110 A. Quintario Olmeda,110 I. Redondo,110\n\nL. Romero,110 M. S. Soares,110 J. F. de Trocóniz,111 M. Missiroli,111 D. Moran,111 J. Cuevas,112 C. Erice,112\n\nJ. Fernandez Menendez,112 I. Gonzalez Caballero,112 J. R. González Fernández,112 E. Palencia Cortezon,112\n\nS. Sanchez Cruz,112 I. Suárez Andrés,112 P. Vischia,112 J. M. Vizan Garcia,112 I. J. Cabrillo,113 A. Calderon,113 E. Curras,113\n\nM. Fernandez,113 J. Garcia-Ferrero,113 G. Gomez,113 A. Lopez Virto,113 J. Marco,113 C. Martinez Rivero,113 F. Matorras,113\n\nJ. Piedra Gomez,113 T. Rodrigo,113 A. Ruiz-Jimeno,113 L. Scodellaro,113 N. Trevisani,113 I. Vila,113 R. Vilar Cortabitarte,113\n\nD. Abbaneo,114 E. Auffray,114 G. Auzinger,114 P. Baillon,114 A. H. Ball,114 D. Barney,114 P. Bloch,114 A. Bocci,114 C. Botta,114\n\nT. Camporesi,114 R. Castello,114 M. Cepeda,114 G. Cerminara,114 Y. Chen,114 A. Cimmino,114 D. d’Enterria,114\n\nMEASUREMENT OF THE TOP QUARK MASS IN THE … PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-23\n\n\n\nA. Dabrowski,114 V. Daponte,114 A. David,114 M. De Gruttola,114 A. De Roeck,114 E. Di Marco,114,qq M. Dobson,114\n\nB. Dorney,114 T. du Pree,114 D. Duggan,114 M. Dünser,114 N. Dupont,114 A. Elliott-Peisert,114 P. Everaerts,114 S. Fartoukh,114\n\nG. Franzoni,114 J. Fulcher,114 W. Funk,114 D. Gigi,114 K. Gill,114 M. Girone,114 F. Glege,114 D. Gulhan,114 S. Gundacker,114\n\nM. Guthoff,114 P. Harris,114 J. Hegeman,114 V. Innocente,114 P. Janot,114 J. Kieseler,114 H. Kirschenmann,114 V. Knünz,114\n\nA. Kornmayer,114,o M. J. Kortelainen,114 M. Krammer,114,b C. Lange,114 P. Lecoq,114 C. Lourenço,114 M. T. Lucchini,114\n\nL. Malgeri,114 M. Mannelli,114 A. Martelli,114 F. Meijers,114 J. A. Merlin,114 S. Mersi,114 E. Meschi,114 P. Milenovic,114,rr\n\nF. Moortgat,114 S. Morovic,114 M. Mulders,114 H. Neugebauer,114 S. Orfanelli,114 L. Orsini,114 L. Pape,114 E. Perez,114\n\nM. Peruzzi,114 A. Petrilli,114 G. Petrucciani,114 A. Pfeiffer,114 M. Pierini,114 A. Racz,114 T. Reis,114 G. Rolandi,114,ss\n\nM. Rovere,114 H. Sakulin,114 J. B. Sauvan,114 C. Schäfer,114 C. Schwick,114 M. Seidel,114 A. Sharma,114 P. Silva,114\n\nP. Sphicas,114,tt J. Steggemann,114 M. Stoye,114 Y. Takahashi,114 M. Tosi,114 D. Treille,114 A. Triossi,114 A. Tsirou,114\n\nV. Veckalns,114,uu G. I. Veres,114,t M. Verweij,114 N. Wardle,114 H. K. Wöhri,114 A. Zagozdzinska,114,hh W. D. Zeuner,114\n\nW. Bertl,115 K. Deiters,115 W. Erdmann,115 R. Horisberger,115 Q. Ingram,115 H. C. Kaestli,115 D. Kotlinski,115\n\nU. Langenegger,115 T. Rohe,115 S. A. Wiederkehr,115 F. Bachmair,116 L. Bäni,116 L. Bianchini,116 B. Casal,116\n\nG. Dissertori,116 M. Dittmar,116 M. Donegà,116 C. Grab,116 C. Heidegger,116 D. Hits,116 J. Hoss,116 G. Kasieczka,116\n\nW. Lustermann,116 B. Mangano,116 M. Marionneau,116 P. Martinez Ruiz del Arbol,116 M. Masciovecchio,116\n\nM. T. Meinhard,116 D. Meister,116 F. Micheli,116 P. Musella,116 F. Nessi-Tedaldi,116 F. Pandolfi,116 J. Pata,116 F. Pauss,116\n\nG. Perrin,116 L. Perrozzi,116 M. Quittnat,116 M. Rossini,116 M. Schönenberger,116 A. Starodumov,116,vv V. R. Tavolaro,116\n\nK. Theofilatos,116 R. Wallny,116 T. K. Aarrestad,117 C. Amsler,117,ww L. Caminada,117 M. F. Canelli,117 A. De Cosa,117\n\nS. Donato,117 C. Galloni,117 A. Hinzmann,117 T. Hreus,117 B. Kilminster,117 J. Ngadiuba,117 D. Pinna,117 G. Rauco,117\n\nP. Robmann,117 D. Salerno,117 C. Seitz,117 Y. Yang,117 A. Zucchetta,117 V. Candelise,118 T. H. Doan,118 Sh. Jain,118\n\nR. Khurana,118 M. Konyushikhin,118 C. M. Kuo,118 W. Lin,118 A. Pozdnyakov,118 S. S. Yu,118 Arun Kumar,119 P. Chang,119\n\nY. H. Chang,119 Y. Chao,119 K. F. Chen,119 P. H. Chen,119 F. Fiori,119 W.-S. Hou,119 Y. Hsiung,119 Y. F. Liu,119 R.-S. Lu,119\n\nM. Miñano Moya,119 E. Paganis,119 A. Psallidas,119 J. f. Tsai,119 B. Asavapibhop,120 G. Singh,120 N. Srimanobhas,120\n\nN. Suwonjandee,120 A. Adiguzel,121 M. N. Bakirci,121,xx F. Boran,121 S. Cerci,121,yy S. Damarseckin,121 Z. S. Demiroglu,121\n\nC. Dozen,121 I. Dumanoglu,121 S. Girgis,121 G. Gokbulut,121 Y. Guler,121 I. Hos,121,zz E. E. Kangal,121,aaa O. Kara,121\n\nA. Kayis Topaksu,121 U. Kiminsu,121 M. Oglakci,121 G. Onengut,121,bbb K. Ozdemir,121,ccc B. Tali,121,yy S. Turkcapar,121\n\nI. S. Zorbakir,121 C. Zorbilmez,121 B. Bilin,122 S. Bilmis,122 B. Isildak,122,ddd G. Karapinar,122,eee M. Yalvac,122 M. Zeyrek,122\n\nE. Gülmez,123 M. Kaya,123,fff O. Kaya,123,ggg E. A. Yetkin,123,hhh T. Yetkin,123,iii A. Cakir,124 K. Cankocak,124 S. Sen,124,jjj\n\nB. Grynyov,125 L. Levchuk,126 P. Sorokin,126 R. Aggleton,127 F. Ball,127 L. Beck,127 J. J. Brooke,127 D. Burns,127\n\nE. Clement,127 D. Cussans,127 H. Flacher,127 J. Goldstein,127 M. Grimes,127 G. P. Heath,127 H. F. Heath,127 J. Jacob,127\n\nL. Kreczko,127 C. Lucas,127 D. M. Newbold,127,kkk S. Paramesvaran,127 A. Poll,127 T. Sakuma,127 S. Seif El Nasr-storey,127\n\nD. Smith,127 V. J. Smith,127 K.W. Bell,128 A. Belyaev,128,lll C. Brew,128 R. M. Brown,128 L. Calligaris,128 D. Cieri,128\n\nD. J. A. Cockerill,128 J. A. Coughlan,128 K. Harder,128 S. Harper,128 E. Olaiya,128 D. Petyt,128\n\nC. H. Shepherd-Themistocleous,128 A. Thea,128 I. R. Tomalin,128 T. Williams,128 M. Baber,129 R. Bainbridge,129\n\nO. Buchmuller,129 A. Bundock,129 S. Casasso,129 M. Citron,129 D. Colling,129 L. Corpe,129 P. Dauncey,129 G. Davies,129\n\nA. De Wit,129 M. Della Negra,129 R. Di Maria,129 P. Dunne,129 A. Elwood,129 D. Futyan,129 Y. Haddad,129 G. Hall,129\n\nG. Iles,129 T. James,129 R. Lane,129 C. Laner,129 L. Lyons,129 A.-M. Magnan,129 S. Malik,129 L. Mastrolorenzo,129 J. Nash,129\n\nA. Nikitenko,129,vv J. Pela,129 B. Penning,129 M. Pesaresi,129 D. M. Raymond,129 A. Richards,129 A. Rose,129 E. Scott,129\n\nC. Seez,129 S. Summers,129 A. Tapper,129 K. Uchida,129 M. Vazquez Acosta,129,mmm T. Virdee,129,o J. Wright,129 S. C. Zenz,129\n\nJ. E. Cole,130 P. R. Hobson,130 A. Khan,130 P. Kyberd,130 I. D. Reid,130 P. Symonds,130 L. Teodorescu,130 M. Turner,130\n\nA. Borzou,131 K. Call,131 J. Dittmann,131 K. Hatakeyama,131 H. Liu,131 N. Pastika,131 R. Bartek,132 A. Dominguez,132\n\nA. Buccilli,133 S. I. Cooper,133 C. Henderson,133 P. Rumerio,133 C. West,133 D. Arcaro,134 A. Avetisyan,134 T. Bose,134\n\nD. Gastler,134 D. Rankin,134 C. Richardson,134 J. Rohlf,134 L. Sulak,134 D. Zou,134 G. Benelli,135 D. Cutts,135\n\nA. Garabedian,135 J. Hakala,135 U. Heintz,135 J. M. Hogan,135 O. Jesus,135 K. H. M. Kwok,135 E. Laird,135 G. Landsberg,135\n\nZ. Mao,135 M. Narain,135 S. Piperov,135 S. Sagir,135 E. Spencer,135 R. Syarif,135 R. Breedon,136 D. Burns,136\n\nM. Calderon De La Barca Sanchez,136 S. Chauhan,136 M. Chertok,136 J. Conway,136 R. Conway,136 P. T. Cox,136\n\nR. Erbacher,136 C. Flores,136 G. Funk,136 M. Gardner,136 W. Ko,136 R. Lander,136 C. Mclean,136 M. Mulhearn,136 D. Pellett,136\n\nJ. Pilot,136 S. Shalhout,136 M. Shi,136 J. Smith,136 M. Squires,136 D. Stolp,136 K. Tos,136 M. Tripathi,136 M. Bachtis,137\n\nC. Bravo,137 R. Cousins,137 A. Dasgupta,137 A. Florent,137 J. Hauser,137 M. Ignatenko,137 N. Mccoll,137 D. Saltzberg,137\n\nA. M. SIRUNYAN et al. PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-24\n\n\n\nC. Schnaible,137 V. Valuev,137 M. Weber,137 E. Bouvier,138 K. Burt,138 R. Clare,138 J. Ellison,138 J. W. Gary,138\n\nS. M. A. Ghiasi Shirazi,138 G. Hanson,138 J. Heilman,138 P. Jandir,138 E. Kennedy,138 F. Lacroix,138 O. R. Long,138\n\nM. Olmedo Negrete,138 M. I. Paneva,138 A. Shrinivas,138 W. Si,138 H. Wei,138 S. Wimpenny,138 B. R. Yates,138\n\nJ. G. Branson,139 G. B. Cerati,139 S. Cittolin,139 M. Derdzinski,139 R. Gerosa,139 A. Holzner,139 D. Klein,139 V. Krutelyov,139\n\nJ. Letts,139 I. Macneill,139 D. Olivito,139 S. Padhi,139 M. Pieri,139 M. Sani,139 V. Sharma,139 S. Simon,139 M. Tadel,139\n\nA. Vartak,139 S. Wasserbaech,139,nnn C. Welke,139 J. Wood,139 F. Würthwein,139 A. Yagil,139 G. Zevi Della Porta,139\n\nN. Amin,140 R. Bhandari,140 J. Bradmiller-Feld,140 C. Campagnari,140 A. Dishaw,140 V. Dutta,140 M. Franco Sevilla,140\n\nC. George,140 F. Golf,140 L. Gouskos,140 J. Gran,140 R. Heller,140 J. Incandela,140 S. D. Mullin,140 A. Ovcharova,140 H. Qu,140\n\nJ. Richman,140 D. Stuart,140 I. Suarez,140 J. Yoo,140 D. Anderson,141 J. Bendavid,141 A. Bornheim,141 J. Bunn,141 J. Duarte,141\n\nJ. M. Lawhorn,141 A. Mott,141 H. B. Newman,141 C. Pena,141 M. Spiropulu,141 J. R. Vlimant,141 S. Xie,141 R. Y. Zhu,141\n\nM. B. Andrews,142 T. Ferguson,142 M. Paulini,142 J. Russ,142 M. Sun,142 H. Vogel,142 I. Vorobiev,142 M. Weinberg,142\n\nJ. P. Cumalat,143 W. T. Ford,143 F. Jensen,143 A. Johnson,143 M. Krohn,143 S. Leontsinis,143 T. Mulholland,143 K. Stenson,143\n\nS. R. Wagner,143 J. Alexander,144 J. Chaves,144 J. Chu,144 S. Dittmer,144 K. Mcdermott,144 N. Mirman,144 J. R. Patterson,144\n\nA. Rinkevicius,144 A. Ryd,144 L. Skinnari,144 L. Soffi,144 S. M. Tan,144 Z. Tao,144 J. Thom,144 J. Tucker,144 P. Wittich,144\n\nM. Zientek,144 D. Winn,145 S. Abdullin,146 M. Albrow,146 G. Apollinari,146 A. Apresyan,146 S. Banerjee,146\n\nL. A. T. Bauerdick,146 A. Beretvas,146 J. Berryhill,146 P. C. Bhat,146 G. Bolla,146 K. Burkett,146 J. N. Butler,146\n\nH.W. K. Cheung,146 F. Chlebana,146 S. Cihangir,146,a M. Cremonesi,146 V. D. Elvira,146 I. Fisk,146 J. Freeman,146\n\nE. Gottschalk,146 L. Gray,146 D. Green,146 S. Grünendahl,146 O. Gutsche,146 D. Hare,146 R. M. Harris,146 S. Hasegawa,146\n\nJ. Hirschauer,146 Z. Hu,146 B. Jayatilaka,146 S. Jindariani,146 M. Johnson,146 U. Joshi,146 B. Klima,146 B. Kreis,146\n\nS. Lammel,146 J. Linacre,146 D. Lincoln,146 R. Lipton,146 M. Liu,146 T. Liu,146 R. Lopes De Sá,146 J. Lykken,146\n\nK. Maeshima,146 N. Magini,146 J. M. Marraffino,146 S. Maruyama,146 D. Mason,146 P. McBride,146 P. Merkel,146\n\nS. Mrenna,146 S. Nahn,146 V. O’Dell,146 K. Pedro,146 O. Prokofyev,146 G. Rakness,146 L. Ristori,146 E. Sexton-Kennedy,146\n\nA. Soha,146 W. J. Spalding,146 L. Spiegel,146 S. Stoynev,146 J. Strait,146 N. Strobbe,146 L. Taylor,146 S. Tkaczyk,146\n\nN. V. Tran,146 L. Uplegger,146 E.W. Vaandering,146 C. Vernieri,146 M. Verzocchi,146 R. Vidal,146 M. Wang,146\n\nH. A. Weber,146 A. Whitbeck,146 Y. Wu,146 D. Acosta,147 P. Avery,147 P. Bortignon,147 D. Bourilkov,147 A. Brinkerhoff,147\n\nA. Carnes,147 M. Carver,147 D. Curry,147 S. Das,147 R. D. Field,147 I. K. Furic,147 J. Konigsberg,147 A. Korytov,147\n\nJ. F. Low,147 P. Ma,147 K. Matchev,147 H. Mei,147 G. Mitselmakher,147 D. Rank,147 L. Shchutska,147 D. Sperka,147\n\nL. Thomas,147 J. Wang,147 S. Wang,147 J. Yelton,147 S. Linn,148 P. Markowitz,148 G. Martinez,148 J. L. Rodriguez,148\n\nA. Ackert,149 T. Adams,149 A. Askew,149 S. Bein,149 S. Hagopian,149 V. Hagopian,149 K. F. Johnson,149 T. Kolberg,149\n\nT. Perry,149 H. Prosper,149 A. Santra,149 R. Yohay,149 M. M. Baarmand,150 V. Bhopatkar,150 S. Colafranceschi,150\n\nM. Hohlmann,150 D. Noonan,150 T. Roy,150 F. Yumiceva,150 M. R. Adams,151 L. Apanasevich,151 D. Berry,151 R. R. Betts,151\n\nR. Cavanaugh,151 X. Chen,151 O. Evdokimov,151 C. E. Gerber,151 D. A. Hangal,151 D. J. Hofman,151 K. Jung,151 J. Kamin,151\n\nI. D. Sandoval Gonzalez,151 H. Trauger,151 N. Varelas,151 H. Wang,151 Z. Wu,151 J. Zhang,151 B. Bilki,152,ooo W. Clarida,152\n\nK. Dilsiz,152 S. Durgut,152 R. P. Gandrajula,152 M. Haytmyradov,152 V. Khristenko,152 J.-P. Merlo,152 H. Mermerkaya,152,ppp\n\nA. Mestvirishvili,152 A. Moeller,152 J. Nachtman,152 H. Ogul,152 Y. Onel,152 F. Ozok,152,qqq A. Penzo,152 C. Snyder,152\n\nE. Tiras,152 J. Wetzel,152 K. Yi,152 B. Blumenfeld,153 A. Cocoros,153 N. Eminizer,153 D. Fehling,153 L. Feng,153\n\nA. V. Gritsan,153 P. Maksimovic,153 J. Roskes,153 U. Sarica,153 M. Swartz,153 M. Xiao,153 C. You,153 A. Al-bataineh,154\n\nP. Baringer,154 A. Bean,154 S. Boren,154 J. Bowen,154 J. Castle,154 L. Forthomme,154 S. Khalil,154 A. Kropivnitskaya,154\n\nD. Majumder,154 W. Mcbrayer,154 M. Murray,154 S. Sanders,154 R. Stringer,154 J. D. Tapia Takaki,154 Q. Wang,154\n\nA. Ivanov,155 K. Kaadze,155 Y. Maravin,155 A. Mohammadi,155 L. K. Saini,155 N. Skhirtladze,155 S. Toda,155 F. Rebassoo,156\n\nD. Wright,156 C. Anelli,157 A. Baden,157 O. Baron,157 A. Belloni,157 B. Calvert,157 S. C. Eno,157 C. Ferraioli,157\n\nJ. A. Gomez,157 N. J. Hadley,157 S. Jabeen,157 G. Y. Jeng,157 R. G. Kellogg,157 J. Kunkle,157 A. C. Mignerey,157\n\nF. Ricci-Tam,157 Y. H. Shin,157 A. Skuja,157 M. B. Tonjes,157 S. C. Tonwar,157 D. Abercrombie,158 B. Allen,158 A. Apyan,158\n\nV. Azzolini,158 R. Barbieri,158 A. Baty,158 R. Bi,158 K. Bierwagen,158 S. Brandt,158 W. Busza,158 I. A. Cali,158\n\nM. D’Alfonso,158 Z. Demiragli,158 G. Gomez Ceballos,158 M. Goncharov,158 D. Hsu,158 Y. Iiyama,158 G. M. Innocenti,158\n\nM. Klute,158 D. Kovalskyi,158 K. Krajczar,158 Y. S. Lai,158 Y.-J. Lee,158 A. Levin,158 P. D. Luckey,158 B. Maier,158\n\nA. C. Marini,158 C. Mcginn,158 C. Mironov,158 S. Narayanan,158 X. Niu,158 C. Paus,158 C. Roland,158 G. Roland,158\n\nJ. Salfeld-Nebgen,158 G. S. F. Stephans,158 K. Tatar,158 D. Velicanu,158 J. Wang,158 T. W. Wang,158 B. Wyslouch,158\n\nA. C. Benvenuti,159 R. M. Chatterjee,159 A. Evans,159 P. Hansen,159 S. Kalafut,159 S. C. Kao,159 Y. Kubota,159 Z. Lesko,159\n\nMEASUREMENT OF THE TOP QUARK MASS IN THE … PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-25\n\n\n\nJ. Mans,159 S. Nourbakhsh,159 N. Ruckstuhl,159 R. Rusack,159 N. Tambe,159 J. Turkewitz,159 J. G. Acosta,160 S. Oliveros,160\n\nE. Avdeeva,161 K. Bloom,161 D. R. Claes,161 C. Fangmeier,161 R. Gonzalez Suarez,161 R. Kamalieddin,161 I. Kravchenko,161\n\nA. Malta Rodrigues,161 J. Monroy,161 J. E. Siado,161 G. R. Snow,161 B. Stieger,161 M. Alyari,162 J. Dolen,162 A. Godshalk,162\n\nC. Harrington,162 I. Iashvili,162 J. Kaisen,162 D. Nguyen,162 A. Parker,162 S. Rappoccio,162 B. Roozbahani,162 G. Alverson,163\n\nE. Barberis,163 A. Hortiangtham,163 A. Massironi,163 D. M. Morse,163 D. Nash,163 T. Orimoto,163 R. Teixeira De Lima,163\n\nD. Trocino,163 R.-J. Wang,163 D. Wood,163 S. Bhattacharya,164 O. Charaf,164 K. A. Hahn,164 N. Mucia,164 N. Odell,164\n\nB. Pollack,164 M. H. Schmitt,164 K. Sung,164 M. Trovato,164 M. Velasco,164 N. Dev,165 M. Hildreth,165\n\nK. Hurtado Anampa,165 C. Jessop,165 D. J. Karmgard,165 N. Kellams,165 K. Lannon,165 N. Marinelli,165 F. Meng,165\n\nC. Mueller,165 Y. Musienko,165,ii M. Planer,165 A. Reinsvold,165 R. Ruchti,165 N. Rupprecht,165 G. Smith,165 S. Taroni,165\n\nM. Wayne,165 M. Wolf,165 A. Woodard,165 J. Alimena,166 L. Antonelli,166 B. Bylsma,166 L. S. Durkin,166 S. Flowers,166\n\nB. Francis,166 A. Hart,166 C. Hill,166 W. Ji,166 B. Liu,166 W. Luo,166 D. Puigh,166 B. L. Winer,166 H.W. Wulsin,166\n\nS. Cooperstein,167 O. Driga,167 P. Elmer,167 J. Hardenbrook,167 P. Hebda,167 D. Lange,167 J. Luo,167 D. Marlow,167\n\nT. Medvedeva,167 K. Mei,167 I. Ojalvo,167 J. Olsen,167 C. Palmer,167 P. Piroué,167 D. Stickland,167 A. Svyatkovskiy,167\n\nC. Tully,167 S. Malik,168 A. Barker,169 V. E. Barnes,169 S. Folgueras,169 L. Gutay,169 M. K. Jha,169 M. Jones,169 A.W. Jung,169\n\nA. Khatiwada,169 D. H. Miller,169 N. Neumeister,169 J. F. Schulte,169 X. Shi,169 J. Sun,169 F. Wang,169 W. Xie,169\n\nN. Parashar,170 J. Stupak,170 A. Adair,171 B. Akgun,171 Z. Chen,171 K. M. Ecklund,171 F. J. M. Geurts,171 M. Guilbaud,171\n\nW. Li,171 B. Michlin,171 M. Northup,171 B. P. Padley,171 J. Roberts,171 J. Rorie,171 Z. Tu,171 J. Zabel,171 B. Betchart,172\n\nA. Bodek,172 P. de Barbaro,172 R. Demina,172 Y. t. Duh,172 T. Ferbel,172 M. Galanti,172 A. Garcia-Bellido,172 J. Han,172\n\nO. Hindrichs,172 A. Khukhunaishvili,172 K. H. Lo,172 P. Tan,172 M. Verzetti,172 A. Agapitos,173 J. P. Chou,173 Y. Gershtein,173\n\nT. A. Gómez Espinosa,173 E. Halkiadakis,173 M. Heindl,173 E. Hughes,173 S. Kaplan,173 R. Kunnawalkam Elayavalli,173\n\nS. Kyriacou,173 A. Lath,173 R. Montalvo,173 K. Nash,173 M. Osherson,173 H. Saka,173 S. Salur,173 S. Schnetzer,173\n\nD. Sheffield,173 S. Somalwar,173 R. Stone,173 S. Thomas,173 P. Thomassen,173 M. Walker,173 A. G. Delannoy,174\n\nM. Foerster,174 J. Heideman,174 G. Riley,174 K. Rose,174 S. Spanier,174 K. Thapa,174 O. Bouhali,175,rrr A. Celik,175\n\nM. Dalchenko,175 M. De Mattia,175 A. Delgado,175 S. Dildick,175 R. Eusebi,175 J. Gilmore,175 T. Huang,175 E. Juska,175\n\nT. Kamon,175,sss R. Mueller,175 Y. Pakhotin,175 R. Patel,175 A. Perloff,175 L. Perniè,175 D. Rathjens,175 A. Safonov,175\n\nA. Tatarinov,175 K. A. Ulmer,175 N. Akchurin,176 J. Damgov,176 F. De Guio,176 C. Dragoiu,176 P. R. Dudero,176 J. Faulkner,176\n\nE. Gurpinar,176 S. Kunori,176 K. Lamichhane,176 S.W. Lee,176 T. Libeiro,176 T. Peltola,176 S. Undleeb,176 I. Volobouev,176\n\nZ. Wang,176 S. Greene,177 A. Gurrola,177 R. Janjam,177 W. Johns,177 C. Maguire,177 A. Melo,177 H. Ni,177 P. Sheldon,177\n\nS. Tuo,177 J. Velkovska,177 Q. Xu,177 M.W. Arenton,178 P. Barria,178 B. Cox,178 R. Hirosky,178 A. Ledovskoy,178 H. Li,178\n\nC. Neu,178 T. Sinthuprasith,178 X. Sun,178 Y. Wang,178 E. Wolfe,178 F. Xia,178 C. Clarke,179 R. Harr,179 P. E. Karchin,179\n\nJ. Sturdy,179 S. Zaleski,179 D. A. Belknap,180 J. Buchanan,180 C. Caillol,180 S. Dasu,180 L. Dodd,180 S. Duric,180\n\nB. Gomber,180 M. Grothe,180 M. Herndon,180 A. Hervé,180 U. Hussain,180 P. Klabbers,180 A. Lanaro,180 A. Levine,180\n\nK. Long,180 R. Loveless,180 G. A. Pierro,180 G. Polese,180 T. Ruggles,180 A. Savin,180 N. Smith,180 W. H. Smith,180\n\nD. Taylor,180 and N. Woods180\n\n(CMS Collaboration)\n\n1Yerevan Physics Institute, Yerevan, Armenia\n2Institut für Hochenergiephysik, Wien, Austria\n\n3Institute for Nuclear Problems, Minsk, Belarus\n4National Centre for Particle and High Energy Physics, Minsk, Belarus\n\n5Universiteit Antwerpen, Antwerpen, Belgium\n6Vrije Universiteit Brussel, Brussel, Belgium\n\n7Université Libre de Bruxelles, Bruxelles, Belgium\n8Ghent University, Ghent, Belgium\n\n9Université Catholique de Louvain, Louvain-la-Neuve, Belgium\n10Université de Mons, Mons, Belgium\n\n11Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil\n12Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil\n\n13aUniversidade Estadual Paulista, São Paulo, Brazil\n13bUniversidade Federal do ABC, São Paulo, Brazil\n\nA.M. SIRUNYAN et al. PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-26\n\n\n\n14Institute for Nuclear Research and Nuclear Energy, Sofia, Bulgaria\n15University of Sofia, Sofia, Bulgaria\n16Beihang University, Beijing, China\n\n17Institute of High Energy Physics, Beijing, China\n18State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China\n\n19Universidad de Los Andes, Bogota, Colombia\n20University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture,\n\nSplit, Croatia\n21University of Split, Faculty of Science, Split, Croatia\n\n22Institute Rudjer Boskovic, Zagreb, Croatia\n23University of Cyprus, Nicosia, Cyprus\n\n24Charles University, Prague, Czech Republic\n25Universidad San Francisco de Quito, Quito, Ecuador\n\n26Academy of Scientific Research and Technology of the Arab Republic of Egypt,\nEgyptian Network of High Energy Physics, Cairo, Egypt\n\n27National Institute of Chemical Physics and Biophysics, Tallinn, Estonia\n28Department of Physics, University of Helsinki, Helsinki, Finland\n\n29Helsinki Institute of Physics, Helsinki, Finland\n30Lappeenranta University of Technology, Lappeenranta, Finland\n\n31IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France\n32Laboratoire Leprince-Ringuet, Ecole polytechnique,\n\nCNRS/IN2P3, Université Paris-Saclay\n33Université de Strasbourg, CNRS, IPHC UMR 7178, Strasbourg, France\n\n34Centre de Calcul de l’Institut National de Physique Nucleaire et de Physique des Particules,\nCNRS/IN2P3, Villeurbanne, France\n\n35Université de Lyon, Université Claude Bernard Lyon 1, CNRS-IN2P3,\nInstitut de Physique Nucléaire de Lyon, Villeurbanne, France\n\n36Georgian Technical University, Tbilisi, Georgia\n37Tbilisi State University, Tbilisi, Georgia\n\n38RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany\n39RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany\n40RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany\n\n41Deutsches Elektronen-Synchrotron, Hamburg, Germany\n42University of Hamburg, Hamburg, Germany\n\n43Institut für Experimentelle Kernphysik, Karlsruhe, Germany\n44Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece\n\n45National and Kapodistrian University of Athens, Athens, Greece\n46National Technical University of Athens, Athens, Greece\n\n47University of Ioánnina, Ioánnina, Greece\n48MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University,\n\nBudapest, Hungary\n49Wigner Research Centre for Physics, Budapest, Hungary\n\n50Institute of Nuclear Research ATOMKI, Debrecen, Hungary\n51Institute of Physics, University of Debrecen\n\n52Indian Institute of Science (IISc)\n53National Institute of Science Education and Research, Bhubaneswar, India\n\n54Panjab University, Chandigarh, India\n55University of Delhi, Delhi, India\n\n56Saha Institute of Nuclear Physics, Kolkata, India\n57Indian Institute of Technology Madras, Madras, India\n\n58Bhabha Atomic Research Centre, Mumbai, India\n59Tata Institute of Fundamental Research-A, Mumbai, India\n60Tata Institute of Fundamental Research-B, Mumbai, India\n\n61Indian Institute of Science Education and Research (IISER), Pune, India\n62Institute for Research in Fundamental Sciences (IPM), Tehran, Iran\n\n63University College Dublin, Dublin, Ireland\n64aINFN Sezione di Bari, Bari, Italy\n\n64bUniversità di Bari, Bari, Italy\n64cPolitecnico di Bari, Bari, Italy\n\n65aINFN Sezione di Bologna, Bologna, Italy\n\nMEASUREMENT OF THE TOP QUARK MASS IN THE … PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-27\n\n\n\n65bUniversità di Bolognav, Bologna, Italy\n66aINFN Sezione di Catania, Catania, Italy\n\n66bUniversità di Catania, Catania, Italy\n67aINFN Sezione di Firenze, Firenze, Italy\n\n67bUniversità di Firenze, Firenze, Italy\n68INFN Laboratori Nazionali di Frascati, Frascati, Italy\n\n69aINFN Sezione di Genova, Università di Genova, Genova, Italy\n69bINFN Sezione di Genova, Genova, Italy\n\n69cUniversità di Genova, Genova, Italy\n70aINFN Sezione di Milano-Bicocca, Milano, Italy\n\n70bUniversità di Milano-Bicocca, Milano, Italy\n71aINFN Sezione di Napoli, Napoli, Italy\n\n71bUniversità di Napoli ’Federico II’, Napoli, Italy\n71cUniversità della Basilicata, Roma, Italy\n\n71dUniversità G. Marconi, Roma, Italy\n72aINFN Sezione di Padova, Padova, Italy\n\n72bUniversità di Padova, Padova, Italy\n72cUniversità di Trento, Trento, Italy\n\n73aINFN Sezione di Pavia, Pavia, Italy\n73bUniversità di Pavia, Pavia, Italy\n\n74aINFN Sezione di Perugia, Perugia, Italy\n74bUniversità di Perugia, Perugia, Italy\n\n75aINFN Sezione di Pisa, Pisa, Italy\n75bUniversità di Pisa, Pisa, Italy\n\n75cScuola Normale Superiore di Pisa, Pisa, Italy\n76INFN Sezione di Roma (a); Sapienza Università di Roma (b)\n\n77aINFN Sezione di Torino, Torino, Italy\n77bUniversità di Torino, Torino, Italy\n\n77cUniversità del Piemonte Orientale, Novara, Italy\n78aINFN Sezione di Trieste, Trieste, Italy\n\n78bUniversità di Trieste, Trieste, Italy\n79Kyungpook National University, Daegu, Korea\n80Chonbuk National University, Jeonju, Korea\n\n81Chonnam National University, Institute for Universe and Elementary Particles, Kwangju, Korea\n82Hanyang University, Seoul, Korea\n83Korea University, Seoul, Korea\n\n84Seoul National University, Seoul, Korea\n85University of Seoul, Seoul, Korea\n\n86Sungkyunkwan University, Suwon, Korea\n87Vilnius University, Vilnius, Lithuania\n\n88National Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia\n89Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico\n\n90Universidad Iberoamericana, Mexico City, Mexico\n91Benemerita Universidad Autonoma de Puebla, Puebla, Mexico\n\n92Universidad Autónoma de San Luis Potosí, San Luis Potosí, Mexico\n93University of Auckland, Auckland, New Zealand\n\n94University of Canterbury, Christchurch, New Zealand\n95National Centre for Physics, Quaid-I-Azam University, Islamabad, Pakistan\n\n96National Centre for Nuclear Research, Swierk, Poland\n97Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Warsaw, Poland\n\n98Laboratório de Instrumentação e Física Experimental de Partículas, Lisboa, Portugal\n99Joint Institute for Nuclear Research, Dubna, Russia\n\n100Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia\n101Institute for Nuclear Research, Moscow, Russia\n\n102Institute for Theoretical and Experimental Physics, Moscow, Russia\n103Moscow Institute of Physics and Technology, Moscow, Russia\n\n104National Research Nuclear University ’Moscow Engineering Physics Institute’ (MEPhI),\nMoscow, Russia\n\n105P. N. Lebedev Physical Institute, Moscow, Russia\n106Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia\n\nA.M. SIRUNYAN et al. PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-28\n\n\n\n107Novosibirsk State University (NSU), Novosibirsk, Russia\n108State Research Center of Russian Federation, Institute for High Energy Physics, Protvino, Russia\n\n109University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia\n110Centro de Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain\n\n111Universidad Autónoma de Madrid, Madrid, Spain\n112Universidad de Oviedo, Oviedo, Spain\n\n113Instituto de Física de Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain\n114CERN, European Organization for Nuclear Research, Geneva, Switzerland\n\n115Paul Scherrer Institut, Villigen, Switzerland\n116Institute for Particle Physics, ETH Zurich, Zurich, Switzerland\n\n117Universität Zürich, Zurich, Switzerland\n118National Central University, Chung-Li, Taiwan\n\n119National Taiwan University (NTU), Taipei, Taiwan\n120Chulalongkorn University, Faculty of Science, Department of Physics, Bangkok, Thailand\n\n121Çukurova University, Physics Department, Science and Art Faculty, Adana, Turkey\n122Middle East Technical University, Physics Department, Ankara, Turkey\n\n123Bogazici University, Istanbul, Turkey\n124Istanbul Technical University, Istanbul, Turkey\n\n125Institute for Scintillation Materials of National Academy of Science of Ukraine, Kharkov, Ukraine\n126National Scientific Center, Kharkov Institute of Physics and Technology, Kharkov, Ukraine\n\n127University of Bristol, Bristol, United Kingdom\n128Rutherford Appleton Laboratory, Didcot, United Kingdom\n\n129Imperial College, London, United Kingdom\n130Brunel University, Uxbridge, United Kingdom\n\n131Baylor University, Waco, USA\n132Catholic University of America\n\n133The University of Alabama, Tuscaloosa, USA\n134Boston University, Boston, USA\n\n135Brown University, Providence, USA\n136University of California, Davis, Davis, USA\n137University of California, Los Angeles, USA\n\n138University of California, Riverside, Riverside, USA\n139University of California, San Diego, La Jolla, USA\n\n140University of California, Santa Barbara—Department of Physics, Santa Barbara, USA\n141California Institute of Technology, Pasadena, USA\n\n142Carnegie Mellon University, Pittsburgh, USA\n143University of Colorado Boulder, Boulder, USA\n\n144Cornell University, Ithaca, USA\n145Fairfield University, Fairfield, USA\n\n146Fermi National Accelerator Laboratory, Batavia, USA\n147University of Florida, Gainesville, USA\n\n148Florida International University, Miami, USA\n149Florida State University, Tallahassee, USA\n\n150Florida Institute of Technology, Melbourne, USA\n151University of Illinois at Chicago (UIC), Chicago, USA\n\n152The University of Iowa, Iowa City, USA\n153Johns Hopkins University, Baltimore, USA\n154The University of Kansas, Lawrence, USA\n155Kansas State University, Manhattan, USA\n\n156Lawrence Livermore National Laboratory, Livermore, USA\n157University of Maryland, College Park, USA\n\n158Massachusetts Institute of Technology, Cambridge, USA\n159University of Minnesota, Minneapolis, USA\n\n160University of Mississippi, Oxford, USA\n161University of Nebraska-Lincoln, Lincoln, USA\n\n162State University of New York at Buffalo, Buffalo, USA\n163Northeastern University, Boston, USA\n\n164Northwestern University, Evanston, USA\n165University of Notre Dame, Notre Dame, USA\n166The Ohio State University, Columbus, USA\n\nMEASUREMENT OF THE TOP QUARK MASS IN THE … PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-29\n\n\n\n167Princeton University, Princeton, USA\n168University of Puerto Rico, Mayaguez, USA\n169Purdue University, West Lafayette, USA\n\n170Purdue University Northwest, Hammond, USA\n171Rice University, Houston, USA\n\n172University of Rochester, Rochester, USA\n173Rutgers, The State University of New Jersey, Piscataway, USA\n\n174University of Tennessee, Knoxville, USA\n175Texas A&M University, College Station, USA\n\n176Texas Tech University, Lubbock, USA\n177Vanderbilt University, Nashville, USA\n\n178University of Virginia, Charlottesville, USA\n179Wayne State University, Detroit, USA\n\n180University of Wisconsin—Madison, Madison, Wisconsin, USA\n\naDeceased.\nbAlso at Vienna University of Technology, Vienna, Austria.\ncAlso at State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China.\ndAlso at Universidade Estadual de Campinas, Campinas, Brazil.\neAlso at Universidade Federal de Pelotas, Pelotas, Brazil.\nfAlso at Université Libre de Bruxelles, Bruxelles, Belgium.\ngAlso at Universidad de Antioquia, Medellin, Colombia.\nhAlso at Joint Institute for Nuclear Research, Dubna, Russia.\niAlso at Suez University, Suez, Egypt.\njAlso at British University in Egypt, Cairo, Egypt.\nkAlso at Ain Shams University, Cairo, Egypt.\nlAlso at Helwan University, Cairo, Egypt.\nmAlso at Université de Haute Alsace, Mulhouse, France.\nnAlso at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia.\noAlso at CERN, European Organization for Nuclear Research, Geneva, Switzerland.\npAlso at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany.\nqAlso at University of Hamburg, Hamburg, Germany.\nrAlso at Brandenburg University of Technology, Cottbus, Germany.\nsAlso at Institute of Nuclear Research ATOMKI, Debrecen, Hungary.\ntAlso at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University, Budapest, Hungary.\nuAlso at Institute of Physics, University of Debrecen.\nvAlso at IIT Bhubaneswar.\nwAlso at University of Visva-Bharati, Santiniketan, India.\nxAlso at Institute of Physics, Bhubaneswar, India.\nyAlso at University of Ruhuna, Matara, Sri Lanka.\nzAlso at Isfahan University of Technology, Isfahan, Iran.\naaAlso at Yazd University, Yazd, Iran.\nbbAlso at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran.\nccAlso at Università degli Studi di Siena, Siena, Italy.\nddAlso at Purdue University, West Lafayette, USA.\neeAlso at International Islamic University of Malaysia, Kuala Lumpur, Malaysia.\nffAlso at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia.\nggAlso at Consejo Nacional de Ciencia y Tecnología, Mexico city, Mexico.\nhhAlso at Warsaw University of Technology, Institute of Electronic Systems, Warsaw, Poland.\niiAlso at Institute for Nuclear Research, Moscow, Russia.\njjAlso at National Research Nuclear University ’Moscow Engineering Physics Institute’ (MEPhI), Moscow, Russia.\nkkAlso at St. Petersburg State Polytechnical University, St. Petersburg, Russia.\nllAlso at University of Florida, Gainesville, USA.\n\nmmAlso at P. N. Lebedev Physical Institute, Moscow, Russia.\nnnAlso at California Institute of Technology, Pasadena, USA.\nooAlso at Budker Institute of Nuclear Physics, Novosibirsk, Russia.\nppAlso at Faculty of Physics, University of Belgrade, Belgrade, Serbia.\nqqAlso at INFN Sezione di Roma (a); Sapienza Università di Roma (b).\nrrAlso at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia.\nssAlso at Scuola Normale e Sezione dell’INFN, Pisa, Italy.\n\nA. M. SIRUNYAN et al. PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-30\n\n\n\nttAlso at National and Kapodistrian University of Athens, Athens, Greece.\nuuAlso at Riga Technical University, Riga, Latvia.\nvvAlso at Institute for Theoretical and Experimental Physics, Moscow, Russia.\nwwAlso at Albert Einstein Center for Fundamental Physics, Bern, Switzerland.\nxxAlso at Gaziosmanpasa University, Tokat, Turkey.\nyyAlso at Adiyaman University, Adiyaman, Turkey.\nzzAlso at Istanbul Aydin University, Istanbul, Turkey.\naaaAlso at Mersin University, Mersin, Turkey.\nbbbAlso at Cag University, Mersin, Turkey.\ncccAlso at Piri Reis University, Istanbul, Turkey.\ndddAlso at Ozyegin University, Istanbul, Turkey.\neeeAlso at Izmir Institute of Technology, Izmir, Turkey.\nfffAlso at Marmara University, Istanbul, Turkey.\n\ngggAlso at Kafkas University, Kars, Turkey.\nhhhAlso at Istanbul Bilgi University, Istanbul, Turkey.\niiiAlso at Yildiz Technical University, Istanbul, Turkey.\njjjAlso at Hacettepe University, Ankara, Turkey.\n\nkkkAlso at Rutherford Appleton Laboratory, Didcot, United Kingdom.\nlllAlso at School of Physics and Astronomy, University of Southampton, Southampton, United Kingdom.\n\nmmmAlso at Instituto de Astrofísica de Canarias, La Laguna, Spain.\nnnnAlso at Utah Valley University, Orem, USA.\noooAlso at beykent university.\npppAlso at Erzincan University, Erzincan, Turkey.\nqqqAlso at Mimar Sinan University, Istanbul, Istanbul, Turkey.\nrrrAlso at Texas A&M University at Qatar, Doha, Qatar.\nsssAlso at Kyungpook National University, Daegu, Korea.\n\nMEASUREMENT OF THE TOP QUARK MASS IN THE … PHYSICAL REVIEW D 96, 032002 (2017)\n\n032002-31"},"fulltext":true,"key":"6953ea276b065fbd930632ec9046341e","url":"https://inspirehep.net/files/6953ea276b065fbd930632ec9046341e"}],"authors":[{"affiliations_identifiers":[{"schema":"ROR","value":"https://ror.org/00ad27c73"}],"raw_affiliations":[{"value":"Yerevan Physics Institute , Yerevan, Armenia"}],"full_name_unicode_normalized":"sirunyan, albert m","full_name":"Sirunyan, Albert M","record":{"$ref":"https://inspirehep.net/api/authors/1064002"},"last_name":"Sirunyan","ids":[{"schema":"INSPIRE ID","value":"INSPIRE-00312131"},{"schema":"INSPIRE BAI","value":"A.M.Sirunyan.1"}],"affiliations":[{"record":{"$ref":"https://inspirehep.net/api/institutions/903361"},"value":"Yerevan Phys. 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the \\mbl\\ distribution in data and simulation with $\\mtmc = 172.5\\GeV$, normalized to the number of events in the 8 TeV data set corresponding to an integrated luminosity of \\luminosity. The lower panel shows the ratio between the data and simulation. Statistical and systematic uncertainties on the distribution in simulation are represented by the shaded area. A description of the systematic uncertainties is given in Section~\\ref{sec:systematics}. (\\cmsRRight) the \\mbl\\ distribution shapes in simulation, normalized to unit area, corresponding to three values of \\mtmc\\ are shown together with the `local shape sensitivity' function, described in Appendix~\\ref{sec:sensitivity}. The \\mbl\\ distributions include two or three values of \\mbl\\ for each event. The distribution shapes are modeled with a GP regression technique, described in Section~\\ref{sec:gp}.","source":"arxiv","key":"c5eee47791feb0009be662534f4cf29e","url":"https://inspirehep.net/files/c5eee47791feb0009be662534f4cf29e"},{"filename":"Figure_001-b.png","caption":"(\\cmsLLeft) the \\mbl\\ distribution in data and simulation with $\\mtmc = 172.5\\GeV$, normalized to the number of events in the 8 TeV data set corresponding to an integrated luminosity of \\luminosity. The lower panel shows the ratio between the data and simulation. Statistical and systematic uncertainties on the distribution in simulation are represented by the shaded area. A description of the systematic uncertainties is given in Section~\\ref{sec:systematics}. (\\cmsRRight) the \\mbl\\ distribution shapes in simulation, normalized to unit area, corresponding to three values of \\mtmc\\ are shown together with the `local shape sensitivity' function, described in Appendix~\\ref{sec:sensitivity}. The \\mbl\\ distributions include two or three values of \\mbl\\ for each event. The distribution shapes are modeled with a GP regression technique, described in Section~\\ref{sec:gp}.","source":"arxiv","key":"b3e6483f0e7ffb143f719c581d8398a4","url":"https://inspirehep.net/files/b3e6483f0e7ffb143f719c581d8398a4"},{"filename":"Figure_002.png","caption":"The \\mtt\\ subsystems in the dileptonic \\ttbar\\ event topology.","source":"arxiv","key":"209b70858d19d8a70a1e61130cb0b9f4","url":"https://inspirehep.net/files/209b70858d19d8a70a1e61130cb0b9f4"},{"filename":"Figure_003-a.png","caption":"Following the conventions of Fig.~\\ref{fig:dist_mbl}, shown are the (\\cmsLeft) \\mttbb\\ distribution in data and simulation with $\\mtmc = 172.5\\GeV$, and (\\cmsRight) \\mttbb\\ distribution shapes in simulation corresponding to three values of \\mtmc, along with the `local shape sensitivity' function.  The \\mttbb\\ distributions include one value of \\mttbb\\ for each event if it satisfies the kinematic requirement outlined in Section~\\ref{subsubsec:mt2sub}.","source":"arxiv","key":"6e0d6b0edfc0181bdec769108dd2a2a6","url":"https://inspirehep.net/files/6e0d6b0edfc0181bdec769108dd2a2a6"},{"filename":"Figure_003-b.png","caption":"Following the conventions of Fig.~\\ref{fig:dist_mbl}, shown are the (\\cmsLeft) \\mttbb\\ distribution in data and simulation with $\\mtmc = 172.5\\GeV$, and (\\cmsRight) \\mttbb\\ distribution shapes in simulation corresponding to three values of \\mtmc, along with the `local shape sensitivity' function.  The \\mttbb\\ distributions include one value of \\mttbb\\ for each event if it satisfies the kinematic requirement outlined in Section~\\ref{subsubsec:mt2sub}.","source":"arxiv","key":"e972f36809ec0844589ca9103f1a9e56","url":"https://inspirehep.net/files/e972f36809ec0844589ca9103f1a9e56"},{"filename":"Figure_004-a.png","caption":"Following the conventions of Fig.~\\ref{fig:dist_mbl}, shown are the (\\cmsLeft) MAOS \\mblv\\ distribution in data and simulation with $\\mtmc = 172.5\\GeV$, and (\\cmsRight) the MAOS \\mblv\\ distribution shapes in simulation corresponding to three values of \\mtmc, along with the `local shape sensitivity' function. The MAOS \\mblv\\ distributions include up to eight values of \\mblv\\ for each event.","source":"arxiv","key":"aaaef3cc2d9d89f312701aca3b02a252","url":"https://inspirehep.net/files/aaaef3cc2d9d89f312701aca3b02a252"},{"filename":"Figure_004-b.png","caption":"Following the conventions of Fig.~\\ref{fig:dist_mbl}, shown are the (\\cmsLeft) MAOS \\mblv\\ distribution in data and simulation with $\\mtmc = 172.5\\GeV$, and (\\cmsRight) the MAOS \\mblv\\ distribution shapes in simulation corresponding to three values of \\mtmc, along with the `local shape sensitivity' function. The MAOS \\mblv\\ distributions include up to eight values of \\mblv\\ for each event.","source":"arxiv","key":"b7c9c793f9c00fc10b8b7bc1f318a7ff","url":"https://inspirehep.net/files/b7c9c793f9c00fc10b8b7bc1f318a7ff"},{"filename":"Figure_005-a.png","caption":"The (\\cmsLeft) \\mbl\\ and (\\cmsRight) \\mttbb\\ distributions in simulation with $\\mt = 172.5$\\GeV for several values of JSF.  Two or three values are included in the \\mbl\\ distribution for each event, and one value is included in the \\mttbb\\ distribution if it satisfies the kinematic requirement outlined in Section~\\ref{subsubsec:mt2sub}.  The distributions are normalized to unit area.  The three curves corresponding to each of the \\mbl\\ and \\mttbb\\ distributions are obtained using a GP regression technique described in Section~\\ref{sec:gp}.","source":"arxiv","key":"770e3f47a82fc4b0d98d733601cb9552","url":"https://inspirehep.net/files/770e3f47a82fc4b0d98d733601cb9552"},{"filename":"Figure_005-b.png","caption":"The (\\cmsLeft) \\mbl\\ and (\\cmsRight) \\mttbb\\ distributions in simulation with $\\mt = 172.5$\\GeV for several values of JSF.  Two or three values are included in the \\mbl\\ distribution for each event, and one value is included in the \\mttbb\\ distribution if it satisfies the kinematic requirement outlined in Section~\\ref{subsubsec:mt2sub}.  The distributions are normalized to unit area.  The three curves corresponding to each of the \\mbl\\ and \\mttbb\\ distributions are obtained using a GP regression technique described in Section~\\ref{sec:gp}.","source":"arxiv","key":"93cebcd7ca8d4153c23530b8984210a0","url":"https://inspirehep.net/files/93cebcd7ca8d4153c23530b8984210a0"},{"filename":"Figure_006-a.png","caption":"Likelihood fit results as a function of \\mtmc\\ corresponding to the (top) 2D, (center left) 1D, (center right) MAOS, and (bottom) hybrid fits.  For each value of \\mtmc, the fit is conducted using $50$ \\PEs\\ in MC simulation.  The mean parameter values, $\\mt^{\\rm fit}$ and $\\jsf^{\\rm fit}$, are represented by the points, with statistical uncertainties indicated by the error bars.  A best-fit line of the form $y=ax + b$ is shown for each fit configuration.","source":"arxiv","key":"4a3cc4c31e2c1246610bdc49ea83fca0","url":"https://inspirehep.net/files/4a3cc4c31e2c1246610bdc49ea83fca0"},{"filename":"Figure_006-b.png","caption":"Likelihood fit results as a function of \\mtmc\\ corresponding to the (top) 2D, (center left) 1D, (center right) MAOS, and (bottom) hybrid fits.  For each value of \\mtmc, the fit is conducted using $50$ \\PEs\\ in MC simulation.  The mean parameter values, $\\mt^{\\rm fit}$ and $\\jsf^{\\rm fit}$, are represented by the points, with statistical uncertainties indicated by the error bars.  A best-fit line of the form $y=ax + b$ is shown for each fit configuration.","source":"arxiv","key":"a505d11929c745819d1a88e70d3b58a3","url":"https://inspirehep.net/files/a505d11929c745819d1a88e70d3b58a3"},{"filename":"Figure_006-c.png","caption":"Likelihood fit results as a function of \\mtmc\\ corresponding to the (top) 2D, (center left) 1D, (center right) MAOS, and (bottom) hybrid fits.  For each value of \\mtmc, the fit is conducted using $50$ \\PEs\\ in MC simulation.  The mean parameter values, $\\mt^{\\rm fit}$ and $\\jsf^{\\rm fit}$, are represented by the points, with statistical uncertainties indicated by the error bars.  A best-fit line of the form $y=ax + b$ is shown for each fit configuration.","source":"arxiv","key":"1430784e8d252baa47790ad2ba1fb6ba","url":"https://inspirehep.net/files/1430784e8d252baa47790ad2ba1fb6ba"},{"filename":"Figure_006-d.png","caption":"Likelihood fit results as a function of \\mtmc\\ corresponding to the (top) 2D, (center left) 1D, (center right) MAOS, and (bottom) hybrid fits.  For each value of \\mtmc, the fit is conducted using $50$ \\PEs\\ in MC simulation.  The mean parameter values, $\\mt^{\\rm fit}$ and $\\jsf^{\\rm fit}$, are represented by the points, with statistical uncertainties indicated by the error bars.  A best-fit line of the form $y=ax + b$ is shown for each fit configuration.","source":"arxiv","key":"10eaad80835a2900c42939bb2dae46d2","url":"https://inspirehep.net/files/10eaad80835a2900c42939bb2dae46d2"},{"filename":"Figure_006-e.png","caption":"Likelihood fit results as a function of \\mtmc\\ corresponding to the (top) 2D, (center left) 1D, (center right) MAOS, and (bottom) hybrid fits.  For each value of \\mtmc, the fit is conducted using $50$ \\PEs\\ in MC simulation.  The mean parameter values, $\\mt^{\\rm fit}$ and $\\jsf^{\\rm fit}$, are represented by the points, with statistical uncertainties indicated by the error bars.  A best-fit line of the form $y=ax + b$ is shown for each fit configuration.","source":"arxiv","key":"2560fe26c256bb6ad0cd7599d4249298","url":"https://inspirehep.net/files/2560fe26c256bb6ad0cd7599d4249298"},{"filename":"Figure_007-a.png","caption":"Likelihood fit results using $1000$ bootstrap \\PEs\\ for the (top) 2D fit, (center left) 1D fit, and (center right) MAOS fit.  (Bottom) hybrid fit results given by the linear combination in Eq.~\\eqref{eq:whyb} of the 1D and 2D fits.  The error bars represent the statistical uncertainty corresponding to the number of \\PEs\\ in each bin.","source":"arxiv","key":"880f40e3934279c23b21d78bdd266bb1","url":"https://inspirehep.net/files/880f40e3934279c23b21d78bdd266bb1"},{"filename":"Figure_007-b.png","caption":"Likelihood fit results using $1000$ bootstrap \\PEs\\ for the (top) 2D fit, (center left) 1D fit, and (center right) MAOS fit.  (Bottom) hybrid fit results given by the linear combination in Eq.~\\eqref{eq:whyb} of the 1D and 2D fits.  The error bars represent the statistical uncertainty corresponding to the number of \\PEs\\ in each bin.","source":"arxiv","key":"a28da961d841aad3fc213e01aec94358","url":"https://inspirehep.net/files/a28da961d841aad3fc213e01aec94358"},{"filename":"Figure_007-c.png","caption":"Likelihood fit results using $1000$ bootstrap \\PEs\\ for the (top) 2D fit, (center left) 1D fit, and (center right) MAOS fit.  (Bottom) hybrid fit results given by the linear combination in Eq.~\\eqref{eq:whyb} of the 1D and 2D fits.  The error bars represent the statistical uncertainty corresponding to the number of \\PEs\\ in each bin.","source":"arxiv","key":"903ea0145fc0c4f9060194f12623c720","url":"https://inspirehep.net/files/903ea0145fc0c4f9060194f12623c720"},{"filename":"Figure_007-d.png","caption":"Likelihood fit results using $1000$ bootstrap \\PEs\\ for the (top) 2D fit, (center left) 1D fit, and (center right) MAOS fit.  (Bottom) hybrid fit results given by the linear combination in Eq.~\\eqref{eq:whyb} of the 1D and 2D fits.  The error bars represent the statistical uncertainty corresponding to the number of \\PEs\\ in each bin.","source":"arxiv","key":"884e97fdb9588e3b6a568cad80acd90f","url":"https://inspirehep.net/files/884e97fdb9588e3b6a568cad80acd90f"},{"filename":"Figure_007-e.png","caption":"Likelihood fit results using $1000$ bootstrap \\PEs\\ for the (top) 2D fit, (center left) 1D fit, and (center right) MAOS fit.  (Bottom) hybrid fit results given by the linear combination in Eq.~\\eqref{eq:whyb} of the 1D and 2D fits.  The error bars represent the statistical uncertainty corresponding to the number of \\PEs\\ in each bin.","source":"arxiv","key":"688701ca2c890565b5de68748c9a58ee","url":"https://inspirehep.net/files/688701ca2c890565b5de68748c9a58ee"},{"filename":"Figure_008-a.png","caption":"Likelihood fit results corresponding to the 2D fit (\\cmsLeft) and hybrid fit (\\cmsRight), obtained using $1000$ \\PEs\\ constructed with the bootstrapping technique.  The shaded histogram represents the number of \\PEs\\ in each bin of \\mt  and \\jsf.  Two-dimensional contours corresponding to $-2\\Delta\\log(\\mathcal{L})=1 (4)$ are shown, allowing the construction of one (two) $\\sigma$ statistical intervals in \\mt  and JSF.  The hybrid fit results are given by a linear combination of the 1D and 2D fit results using Eq.~\\eqref{eq:whyb}.","source":"arxiv","key":"755f2f6717e88fda4cc9e16f6a6711f0","url":"https://inspirehep.net/files/755f2f6717e88fda4cc9e16f6a6711f0"},{"filename":"Figure_008-b.png","caption":"Likelihood fit results corresponding to the 2D fit (\\cmsLeft) and hybrid fit (\\cmsRight), obtained using $1000$ \\PEs\\ constructed with the bootstrapping technique.  The shaded histogram represents the number of \\PEs\\ in each bin of \\mt  and \\jsf.  Two-dimensional contours corresponding to $-2\\Delta\\log(\\mathcal{L})=1 (4)$ are shown, allowing the construction of one (two) $\\sigma$ statistical intervals in \\mt  and JSF.  The hybrid fit results are given by a linear combination of the 1D and 2D fit results using Eq.~\\eqref{eq:whyb}.","source":"arxiv","key":"a43d937ce2d3f1024b5ab74cefad3764","url":"https://inspirehep.net/files/a43d937ce2d3f1024b5ab74cefad3764"},{"filename":"Figure_009-a.png","caption":"Maximum-likelihood fit result in a typical \\PE\\ of the 2D likelihood fit in data.  The best fit parameter values for this \\PE\\ are $\\mt=171.99$\\GeV and $\\jsf = 1.007$.  When the \\jsf\\ parameter is constrained to be unity in the 1D likelihood fit, the best fit value of \\mt  is $172.48\\GeV$.  The lower panel shows the ratio between the distribution in data and the best fit distribution in simulation.","source":"arxiv","key":"a2f936f6847c1dcc379a64f74522d49a","url":"https://inspirehep.net/files/a2f936f6847c1dcc379a64f74522d49a"},{"filename":"Figure_009-b.png","caption":"Maximum-likelihood fit result in a typical \\PE\\ of the 2D likelihood fit in data.  The best fit parameter values for this \\PE\\ are $\\mt=171.99$\\GeV and $\\jsf = 1.007$.  When the \\jsf\\ parameter is constrained to be unity in the 1D likelihood fit, the best fit value of \\mt  is $172.48\\GeV$.  The lower panel shows the ratio between the distribution in data and the best fit distribution in simulation.","source":"arxiv","key":"3511562ef1887a0c3445bc819a8227b1","url":"https://inspirehep.net/files/3511562ef1887a0c3445bc819a8227b1"},{"filename":"Figure_010.png","caption":"The MAOS \\mblv\\ distribution corresponding to the maximum-likelihood fit result in a typical \\PE\\ of the MAOS likelihood fit in data.  The best fit value of \\mt  for this \\PE\\ is $171.54$\\GeV.  The lower panel shows the ratio between the distribution in data and the best fit distribution in simulation.","source":"arxiv","key":"ef84c31d08284e5df4fbb6523336df56","url":"https://inspirehep.net/files/ef84c31d08284e5df4fbb6523336df56"},{"filename":"Figure_011.png","caption":"Summary of the 1D, 2D, hybrid, and MAOS likelihood fit results using the 2012 data set at $\\sqrt{s}=8\\TeV$, corresponding to an integrated luminosity of \\luminosity.  A recent dileptonic channel measurement using the 2012 dataset and the most recent combination of \\mt  measurements by CMS in all \\ttbar decay channels \\cite{cms_comb} are shown below the dashed line for reference.","source":"arxiv","key":"050d59835cc96235485bceb9ae2369ff","url":"https://inspirehep.net/files/050d59835cc96235485bceb9ae2369ff"},{"filename":"Figure_012.png","caption":"Demonstration of the GP conditioning process, given in Eqs.~\\eqref{eq:gp_mean} and \\eqref{eq:gp_sigma}, for one training point and one test point.  The covariance between the value of the shape at the training and test point is represented by the ellipse.  The known value of the shape at the training point (square point) determines the mean value of the shape at the test point (round point and vertical line).  The distribution of possible values of the shape at the test point is represented by the dashed curve.","source":"arxiv","key":"063872cefd929f5af4ad1030f47e7002","url":"https://inspirehep.net/files/063872cefd929f5af4ad1030f47e7002"}],"legacy_version":"20210428121529.0","inspire_categories":[{"term":"Experiment-HEP"}],"accelerator_experiments":[{"legacy_name":"CERN-LHC-CMS","record":{"$ref":"https://inspirehep.net/api/experiments/1108642"}}],"urls":[{"description":"Figures, tables and other information","value":"http://cms-results.web.cern.ch/cms-results/public-results/publications/TOP-15-008"},{"description":"Open Access fulltext","value":"https://lss.fnal.gov/archive/openaccess/10.1103_PhysRevD.96.032002.pdf"}],"first_author":{"affiliations_identifiers":[{"schema":"ROR","value":"https://ror.org/00ad27c73"}],"full_name":"Sirunyan, Albert M","last_name":"Sirunyan","ids":[{"schema":"INSPIRE ID","value":"INSPIRE-00312131"},{"schema":"INSPIRE BAI","value":"A.M.Sirunyan.1"}],"first_name":"Albert M","recid":1064002},"control_number":1593762,"dois":[{"value":"10.1103/PhysRevD.96.032002"}],"document_type":["article"],"texkeys":["CMS:2017znf","Sirunyan:2017idq"],"abstracts":[{"source":"APS","value":"A measurement of the top quark mass (Mt) in the dileptonic tt¯ decay channel is performed using data from proton-proton collisions at a center-of-mass energy of 8 TeV. The data was recorded by the CMS experiment at the LHC and corresponds to an integrated luminosity of 19.7±0.5  fb−1. Events are selected with two oppositely charged leptons (ℓ=e, μ) and two jets identified as originating from b quarks. The analysis is based on three kinematic observables whose distributions are sensitive to the value of Mt. An invariant mass observable, Mbℓ, and a “stransverse mass” observable, MT2, are employed in a simultaneous fit to determine the value of Mt and an overall jet energy scale factor (JSF). A complementary approach is used to construct an invariant mass observable, Mbℓν, that is combined with MT2 to measure Mt. The shapes of the observables, along with their evolutions in Mt and JSF, are modeled by a nonparametric Gaussian process regression technique. The sensitivity of the observables to the value of Mt is investigated using a Fisher information density method. The top quark mass is measured to be 172.22±0.18(stat) -0.93+0.89(syst)  GeV.","abstract_source_suggest":{"input":"APS"}},{"source":"arXiv","value":"A measurement of the top quark mass (M[t]) in the dileptonic t t-bar decay channel is performed using data from proton-proton collisions at a center-of-mass energy of 8 TeV. The data was recorded by the CMS experiment at the LHC and corresponding to an integrated luminosity of 19.7 +/- 0.5 inverse femtobarns. Events are selected with two oppositely charged leptons (l = e, mu) and two jets identified as originating from b quarks. The analysis is based on three kinematic observables whose distributions are sensitive to the value of M[t]. An invariant mass observable, M[bl], and a `stransverse mass' observable, M[T2], are employed in a simultaneous fit to determine the value of M[t] and an overall jet energy scale factor (JSF). A complementary approach is used to construct an invariant mass observable, M[blnu], that is combined with M[T2] to measure M[t]. The shapes of the observables, along with their evolutions in M[t] and JSF, are modeled by a nonparametric Gaussian process regression technique. The sensitivity of the observables to the value of M[t] is investigated using a Fisher information density method. The top quark mass is measured to be 172.22 +/- 0.18 (stat) +0.89/-0.93 (syst) GeV.","abstract_source_suggest":{"input":"arXiv"}}],"primary_arxiv_category":["hep-ex"],"titles":[{"source":"APS","title":"Measurement of the top quark mass in the dileptonic $t\\bar{t}$ decay channel using the mass observables $M_{b\\ell}$, $M_{T2}$, and $M_{b\\ell\\nu}$ in pp collisions at $\\sqrt{s}=8$ TeV"},{"source":"arXiv","title":"Measurement of the top quark mass in the dileptonic ttbar decay channel using the mass observables Mbl, MT2, and Mblv in pp collisions at sqrt(s) = 8 TeV"},{"source":"arXiv","title":"Measurement of the top quark mass in the dileptonic t t-bar decay channel using the mass observables M[bl], M[T2], and M[blnu] in pp collisions at sqrt(s) = 8 TeV"}],"imprints":[{"date":"2017-08-22"}],"curated":true},"updated":"2026-04-16T20:56:56.958333+00:00"},{"id":"1340137","created":"2015-01-20T00:00:00+00:00","links":{"bibtex":"https://inspirehep.net/api/literature/1340137?format=bibtex","latex-eu":"https://inspirehep.net/api/literature/1340137?format=latex-eu","latex-us":"https://inspirehep.net/api/literature/1340137?format=latex-us","json":"https://inspirehep.net/api/literature/1340137?format=json","json-expanded":"https://inspirehep.net/api/literature/1340137?format=json-expanded","cv":"https://inspirehep.net/api/literature/1340137?format=cv","citations":"https://inspirehep.net/api/literature/?q=refersto%3Arecid%3A1340137"},"metadata":{"citation_count":5,"publication_info":[{"journal_volume":"91","artid":"045502","year":2015,"journal_issue":"4","journal_title":"Phys.Rev.C"}],"authors":[{"raw_affiliations":[{"value":"Departamento de Física Atómica, Molecular y Nuclear, Universidad de Sevilla , 41080 Sevilla, 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online) Feynman diagrams representing PVQE electron-nucleon scattering in Born approximation: (a) EM interactioon -- one photon ($\\gamma$) exchanged, (b) WNC interaction -- one $Z^0$ exchanged.","source":"arxiv","key":"e40b6bed224738d80766df9d44b1125f","url":"https://inspirehep.net/files/e40b6bed224738d80766df9d44b1125f"},{"filename":"IA_PW.png","caption":"Hadronic vertex in RPWIA.","source":"arxiv","key":"0d0950980a2f4c59f83a605f7461559a","url":"https://inspirehep.net/files/0d0950980a2f4c59f83a605f7461559a"},{"filename":"IA_FSI.png","caption":"Hadronic vertex when FSI are considered (RMF-FSI model).","source":"arxiv","key":"8af5c94d9e8df421fd68e4d25f401415","url":"https://inspirehep.net/files/8af5c94d9e8df421fd68e4d25f401415"},{"filename":"asi_contributions_RPWIA.png","caption":"(Color online) Inclusive PVQE asymmetry (red line) and the three separate components: longitudinal (L, dashed black line), transverse (T, dashed-dotted green line) and axial-transverse (T', dotted blue line). Results corresponding to two values of the momentum transferred $q=0.5$ GeV and $q=1$ GeV are shown in the upper and lower panels, respectively. The forward (backward) scattering situation, $\\theta_e=15^o$ ($\\theta_e=140^o$), is represented in the panels on the left (right) side. The NCC2 prescription is used to describe the current and the model RPWIA has been employed.","source":"arxiv","key":"1af840a685c71fa4fb3f5e36823dae9a","url":"https://inspirehep.net/files/1af840a685c71fa4fb3f5e36823dae9a"},{"filename":"WNC_resp_models.png","caption":"(Color online) PV responses computed with the models: RPWIA (black line), RMF-FSI (dashed red line) and EMA (dotted blue line). In the upper (lower) panels the momentum transferred is $q=0.5$ GeV ($q=1$ GeV). The prescription NCC2 has been used.","source":"arxiv","key":"0996e7c194b0c8940e081ff4ba70c38e","url":"https://inspirehep.net/files/0996e7c194b0c8940e081ff4ba70c38e"},{"filename":"asi_models.png","caption":"(Color online) As in Fig.~\\ref{fig:asi_contribuciones}, but in this case the PVQE asymmetry has been computed using the following models: RPWIA (solid black line), RMF-FSI (dashed red line), EMA (dotted blue line) and RFG (dashed-dotted green line).","source":"arxiv","key":"600283b39ce270ee27800bbe8593e353","url":"https://inspirehep.net/files/600283b39ce270ee27800bbe8593e353"},{"filename":"asi_nucleos.png","caption":"(Color online) PVQE asymmetry computed with RMF-FSI for several target nuclei: $^{16}$O (solid red line), $^{12}$C (dashed green line) and $^{40}$Ca (dotted blue line). Here the organization of the panels is the same as in Fig.~\\ref{fig:asi_contribuciones}.","source":"arxiv","key":"31d334a3a81b6dd6f5ae4460112bd30c","url":"https://inspirehep.net/files/31d334a3a81b6dd6f5ae4460112bd30c"},{"filename":"asi_CC1vsCC2_rmf.png","caption":"(Color online) PVQE asymmetry within RMF-FSI model, with the same organization of the panels as in Fig.~\\ref{fig:asi_contribuciones}. The results are computed using CC1 and CC2 currents in the different gauges (see legend).","source":"arxiv","key":"ff937a023ab0bf022a97ef7ed1a31454","url":"https://inspirehep.net/files/ff937a023ab0bf022a97ef7ed1a31454"},{"filename":"asi_nucleonic_500.png","caption":"(Color online) PVQE asymmetry at forward (left panels) and backward (right panels) scattering angles. The upper (lower) panels correspond to the momentum transfer $q=0.5$ GeV ($q=1$ GeV). The black band represents the uncertainty in ${\\cal A}^{PV}_{QE}$ due to the magnetic strange parameter $\\mu_s$. The red band (left panels) shows the effect of the electric strange parameter $\\rho_s$ while the green band (right panels) corresponds to the impact associated with the uncertainty in the isovector contribution to the axial-vector form factor (see text for details).","source":"arxiv","key":"e05822f93e5ebda9e1d3325f11448741","url":"https://inspirehep.net/files/e05822f93e5ebda9e1d3325f11448741"},{"filename":"asi_nucleonic_1000.png","caption":"(Color online) PVQE asymmetry at forward (left panels) and backward (right panels) scattering angles. The upper (lower) panels correspond to the momentum transfer $q=0.5$ GeV ($q=1$ GeV). The black band represents the uncertainty in ${\\cal A}^{PV}_{QE}$ due to the magnetic strange parameter $\\mu_s$. The red band (left panels) shows the effect of the electric strange parameter $\\rho_s$ while the green band (right panels) corresponds to the impact associated with the uncertainty in the isovector contribution to the axial-vector form factor (see text for details).","source":"arxiv","key":"c2758d5f04d050edfff082bf5f8b7785","url":"https://inspirehep.net/files/c2758d5f04d050edfff082bf5f8b7785"},{"filename":"scaling_rpwia_cc2_nucleos.png","caption":"(Color online) EM (dashed lines) and interference (solid lines) scaling functions computed using NCC2 prescription, the RPWIA model and two target nuclei: $^{12}$C (black) and $^{16}$O (red). The left (right) panels correspond to the momentum transfer $q=500$ MeV ($q=1000$ MeV). We represent the longitudinal ($L$, upper panels), transverse ($T$, central panels) and transverse axial ($T'$, lower panels) scaling functions. As reference, the experimental longitudinal scaling data are also represented (blue points)~\\cite{Maieron02}.","source":"arxiv","key":"8881ba37c4e4321b366ce82b94403220","url":"https://inspirehep.net/files/8881ba37c4e4321b366ce82b94403220"},{"filename":"scaling_rmf_cc2_nucleos.png","caption":"(Color online) As in Fig.~\\ref{fig:scaling_rpwia_cc2_nucleos}, but using the RMF-FSI model and only for $^{16}$O.","source":"arxiv","key":"8c1d7d4735644363d23c8dd3f17f6bc2","url":"https://inspirehep.net/files/8c1d7d4735644363d23c8dd3f17f6bc2"}],"legacy_version":"20170522172139.0","inspire_categories":[{"term":"Theory-Nucl"}],"first_author":{"affiliations_identifiers":[{"schema":"ROR","value":"https://ror.org/03yxnpp24"},{"schema":"ROR","value":"https://ror.org/00cv9y106"}],"full_name":"González-Jiménez, R.","ids":[{"schema":"INSPIRE ID","value":"INSPIRE-00550395"},{"schema":"ORCID","value":"0000-0002-0492-0619"},{"schema":"INSPIRE BAI","value":"R.Gonzalez.Jimenez.1"}],"last_name":"González-Jiménez","first_name":"R.","recid":1259699},"control_number":1340137,"dois":[{"value":"10.1103/PhysRevC.91.045502"}],"document_type":["article"],"texkeys":["Gonzalez-Jimenez:2015tla"],"abstracts":[{"source":"APS","value":"We study parity violation in quasielastic electron-nucleus scattering using the relativistic impulse approximation. Different fully relativistic approaches have been considered to estimate the effects associated with the final-state interactions. We have computed the parity-violating quasielastic (PVQE) asymmetry and have analyzed its sensitivity to the different ingredients that enter into the description of the reaction mechanism: final-state interactions, nucleon off-shellness effects, and current gauge ambiguities. Particular attention has been paid to the description of the weak neutral current form factors. The PVQE asymmetry is proven to be an excellent observable when the goal is to get precise information on the axial-vector sector of the weak neutral current. Specifically, from measurements of the asymmetry at backward scattering angles good knowledge of the radiative corrections entering in the isovector axial-vector sector can be gained. Finally, scaling properties shown by the interference γ−Z nuclear responses are also analyzed.","abstract_source_suggest":{"input":"APS"}},{"source":"arXiv","value":"We study parity violation in quasielastic (QE) electron-nucleus scattering using the relativistic impulse approximation. Different fully relativistic approaches have been considered to estimate the effects associated with the final-state interactions. We have computed the parity-violating quasielastic (PVQE) asymmetry and have analyzed its sensitivity to the different ingredients that enter in the description of the reaction mechanism: final-state interactions, nucleon off-shellness effects, current gauge ambiguities. Particular attention has been paid to the description of the weak neutral current form factors. The PVQE asymmetry is proven to be an excellent observable when the goal is to get precise information on the axial-vector sector of the weak neutral current. Specifically, from measurements of the asymmetry at backward scattering angles good knowledge of the radiative corrections entering in the isovector axial-vector sector can be gained. Finally, scaling properties shown by the interference $\\gamma-Z$ nuclear responses are also analyzed.","abstract_source_suggest":{"input":"arXiv"}}],"primary_arxiv_category":["nucl-th"],"titles":[{"source":"arXiv","title":"Parity violation in quasielastic electron-nucleus scattering within the relativistic impulse approximation"}],"imprints":[{"date":"2015-04-13"}],"curated":true},"updated":"2024-05-07T10:50:25.747511+00:00"},{"id":"1404695","created":"2015-11-16T00:00:00+00:00","links":{"bibtex":"https://inspirehep.net/api/literature/1404695?format=bibtex","latex-eu":"https://inspirehep.net/api/literature/1404695?format=latex-eu","latex-us":"https://inspirehep.net/api/literature/1404695?format=latex-us","json":"https://inspirehep.net/api/literature/1404695?format=json","json-expanded":"https://inspirehep.net/api/literature/1404695?format=json-expanded","cv":"https://inspirehep.net/api/literature/1404695?format=cv","citations":"https://inspirehep.net/api/literature/?q=refersto%3Arecid%3A1404695"},"metadata":{"citation_count":90,"publication_info":[{"journal_volume":"117","artid":"131602","year":2016,"journal_record":{"$ref":"https://inspirehep.net/api/journals/1214495"},"journal_issue":"13","journal_title":"Phys.Rev.Lett."}],"authors":[{"raw_affiliations":[{"value":"Department of Physics and 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(b) A bipartite cut: the edges along the cut are labeled by irreducible representations $r_1,\\ldots,r_6$ of the group action at the 6 different boundary vertices (thick points), giving rise to a direct sum structure. 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High Energy Phys. 1 (2016) 1], we show that the usual entanglement entropy for a spatial bipartition can be written as the sum of an undistillable gauge part and of another part corresponding to the local operations and classical communication distillable entanglement, which is obtained by depolarizing the local superselection sectors. We demonstrate that the distillable entanglement is zero for pure Abelian gauge theories at zero gauge coupling, while it is in general nonzero for the non-Abelian case. We also consider gauge theories with matter, and show in a perturbative approach how area laws—including a topological correction—emerge for the distillable entanglement. 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We also consider gauge theories with matter, and show in a perturbative approach how area laws -- including a topological correction -- emerge for the distillable entanglement.","abstract_source_suggest":{"input":"arXiv"}}],"primary_arxiv_category":["quant-ph"],"titles":[{"source":"arXiv","title":"The entanglement of distillation for gauge theories"}],"imprints":[{"date":"2016-09-21"}],"curated":true},"updated":"2025-10-02T16:40:33.558553+00:00"},{"id":"2659689","created":"2023-05-16T02:49:17.225821+00:00","links":{"bibtex":"https://inspirehep.net/api/literature/2659689?format=bibtex","latex-eu":"https://inspirehep.net/api/literature/2659689?format=latex-eu","latex-us":"https://inspirehep.net/api/literature/2659689?format=latex-us","json":"https://inspirehep.net/api/literature/2659689?format=json","json-expanded":"https://inspirehep.net/api/literature/2659689?format=json-expanded","cv":"https://inspirehep.net/api/literature/2659689?format=cv","citations":"https://inspirehep.net/api/literature/?q=refersto%3Arecid%3A2659689"},"metadata":{"citation_count":5,"report_numbers":[{"source":"arXiv","value":"CMS-EXO-20-012"},{"source":"arXiv","value":"CERN-EP-2023-064"}],"publication_info":[{"journal_volume":"12","artid":"189","year":2023,"journal_record":{"$ref":"https://inspirehep.net/api/journals/1213103"},"page_start":"189","journal_title":"JHEP"}],"documents":[{"filename":"document","material":"publication","fulltext":true,"description":"Fulltext from Publisher","source":"Springer","key":"ca2f4e28d4effd605dc4f20981ac9000","url":"https://inspirehep.net/files/ca2f4e28d4effd605dc4f20981ac9000"},{"filename":"FERMILAB-PUB-23-252-CMS.pdf","attachment":{"content":"EUROPEAN ORGANIZATION FOR NUCLEAR RESEARCH (CERN)\n\nCERN-EP-2023-064\n2023/05/16\n\nCMS-EXO-20-012\n\nSearch for resonances in events with photon and jet final\nstates in proton-proton collisions at\n\n√\ns = 13 TeV\n\nThe CMS Collaboration*\n\nAbstract\n\nA search for resonances in events with the γ+jet final state has been performed us-\ning proton-proton collision data collected at\n\n√\ns = 13 TeV by the CMS experiment at\n\nthe LHC. The total data analyzed correspond to an integrated luminosity of 138 fb−1.\nModels of excited quarks and quantum black holes are considered. The invariant\nmass spectrum of the γ+jet system is examined for the presence of resonances over\nthe standard model continuum background. The data exhibit no statistically signif-\nicant deviations from the expected standard model background. Exclusion limits\nat 95% confidence level on the resonance mass and other parameters are set. Ex-\ncited light-flavor quarks (excited bottom quarks) are excluded up to a mass of 6.0\n(3.8) TeV. Quantum black hole production is excluded for masses up to 7.5 (5.2) TeV\nin the Arkani-Hamed–Dimopoulos–Dvali (Randall–Sundrum) model. These lower\nmass bounds are the most stringent to date among those obtained in the γ+jet final\nstate.\n\nSubmitted to the Journal of High Energy Physics\n\n© 2023 CERN for the benefit of the CMS Collaboration. CC-BY-4.0 license\n\n*See Appendix A for the list of collaboration members\n\nar\nX\n\niv\n:2\n\n30\n5.\n\n07\n99\n\n8v\n1 \n\n [\nhe\n\np-\nex\n\n] \n 1\n\n3 \nM\n\nay\n 2\n\n02\n3\n\nhttp://creativecommons.org/licenses/by/4.0\n\n\n\n\n1\n\n1 Introduction\nVarious theoretical proposals of beyond the standard model (BSM) physics predict the produc-\ntion of new resonances at hadron collider experiments. In the last decade, experiments at the\nCERN LHC have searched extensively for signatures of such phenomena to help understand\nsome of the unresolved questions concerning features of the standard model (SM) of particle\nphysics, for example the existence of only three fermion families and the hierarchy problem [1].\nA variety of models have been proposed to address these questions, some of which predict new\nresonances producing a γ+jet final state. Models of compositeness [2–4] address the existence\nof three fermion families, and other models address the origin of the hierarchy problem by\npredicting the existence of extra dimensions [5, 6].\n\nThe composite models postulate that the quarks and leptons are composed of more fundamen-\ntal particles, known as “preons” [7]. These preons experience a new force that becomes very\nstrong at the compositeness scale (Λ), when forming the quark and lepton composite states.\nThis paper considers the excited states of composite quarks produced via gauge-mediated in-\nteractions with the dominant process qg → q∗, and decaying to SM particles. It is assumed\nthat the compositeness scale Λ is equal to the mass of the excited quark Mq∗ .\n\nThe interactions between excited quarks, SM quarks, and the gauge bosons can be described\nby an effective Lagrangian [8]\n\nLeff =\n1\n\n2 Λ\nq∗ σµν\n\n[\ngs fs\n\nλa\n2\n\nFa\nµν + g f\n\nτ\n\n2\nWµν + g′ f ′\n\nY\n2\n\nBµν\n\n]\nq + h.c., (1)\n\nwhere q∗ is the right-handed excited quark field; Fa\nµν, Wµν, and Bµν are the field strength ten-\n\nsors associated with the SU(3), SU(2), and U(1) gauge fields, respectively; λa, τ, and Y are the\ncorresponding Lie algebra generators; gs, g, and g′ are the gauge couplings; σ is the Pauli spin\nmatrix; and fs, f , and f ′ are coupling strengths between the excited quark and SM quarks. An\nassumption is also made that fs, f , and f ′ have identical values and henceforth these coupling\nstrengths will be collectively referred to as f .\n\nIn this paper we consider excited light-flavor quarks and bottom quarks (q∗ and b∗, respec-\ntively) radiating a photon and thus resulting in the γ+jet final state. The corresponding Feyn-\nman diagram for the production and decay of the q∗, b∗ signals through gauge mediation is\nshown in Fig. 1 (left). Additionally, an interpretation for b∗ production from contact interac-\ntions (CI) [4] is also considered for the search of excited bottom quarks. Similar searches for\nexcited quarks have been performed previously by the CMS [9–13] and ATLAS [14–17] Col-\nlaborations at the LHC and at other high-energy particle colliders [18–20] and have reported\nno evidence of a signal. Lately, the ATLAS and CMS experiments have set exclusion limits of\n5.3 [15] and 5.5 TeV [13] on the mass of q∗ in the γ+jet channel with data corresponding to 36\nand 37 fb−1 of integrated luminosity, respectively, collected at\n\n√\ns = 13 TeV.\n\nIn addition, we also consider the models of Arkani-Hamed, Dimopoulos, and Dvali (ADD) [5],\nand Randall–Sundrum (RS1) [6], which have extra spatial dimensions. The basic assumption\nof these models is that the fundamental gravitational scale (MD) can be as low as 1 TeV, while\nthe size of the extra dimensions can be as large as 1 millimeter, assuming the extra dimen-\nsions are only accessible to gravity and not to the SM fields. The ADD model assumes (4 + n)\ndimensions with n = 6 flat compact extra dimensions, and RS1 considers n = 1 extra di-\nmension with a warped metric. As a consequence, the models predict the production of mi-\ncroscopic black holes [21], which can be either semi-classical black holes or quantum black\nholes (QBHs) [22, 23]. In this model, the threshold mass Mth for production of a QBH at the\nLHC is assumed to be MD, and the maximum mass limit is set to the smaller of either 3MD\n\n\n\n2\n\nq\n\ng\n\nγ\n\nq,b\n\nq*,b*\n\n1\n\nQBH\n\nq\n\ng\n\nγ\n\nq\n\n1\nFigure 1: Illustrative Feynman diagrams for qg → γ+jet resonance signal models of q∗, b∗\n\n(left), and QBH production (right).\n\nor\n√\n\ns = 13 TeV. A QBH with a mass in this range will decay preferentially to a few-particle\nstate, rather than undergo thermal decay. The QBH production occurs with a continuous QBH\nmass spectrum, falling rapidly from Mth toward the maximum mass limit; however, because of\nradiation and experimental effects on the low-mass side of the mass spectrum, the signal shape\nresembles a resonance-like structure, as shown in Fig. 2. Previous searches for QBHs performed\nat\n√\n\ns = 13 TeV by the CMS and ATLAS experiments are reported in Refs. [10, 12, 15, 24–27].\nThis paper also reports the first search by the CMS experiment for QBHs in the γ+jet final state\n(as shown in the Feynman diagram of Fig. 1 (right)). The ATLAS Collaboration has excluded\nQBH production in the γ+jet channel with mass up to 7.1 (4.4) TeV in the ADD (RS1) model\nusing 13 TeV data corresponding to 37 fb−1 of integrated luminosity [15].\n\nThe main background to this analysis are γ+jet production, quantum chromodynamics (QCD)\nmultijet production, and W/Z + γ processes of the SM. The γ+jet background is an irreducible\nbackground, and is the largest contributing. Despite its large cross section, the QCD multijet\nbackground is only the second largest, contributing when one of the jets fragments decays into\nan high energy π0 decaying into two overlapping photons that are reconstructed as a single\nphoton in the detector. Electroweak processes contribute to the background via the production\nof W/Z + γ, with the heavy boson decaying to a pair of jets, in the scenario where just one jet\npasses the selections or where one jet is reconstructed and the second jet is either merged with\nthe first or escapes detection.\n\nThis search for excited quarks and QBHs is performed using proton-proton (pp) collision data\ncollected at\n\n√\ns = 13 TeV by the CMS experiment, corresponding to an integrated luminosity\n\nof 138 fb−1. The analysis strategy consists of searching for a resonance-like excess in the γ+jet\ninvariant mass, above the expected SM background.\n\nThis paper is organized as follows: Section 2 provides a brief description of the CMS detector.\nThe triggers used for data selection are discussed in Section 3. In Section 4, the data sets and\nsimulation samples used in this analysis are described. The event reconstruction and selection\ncriteria are detailed in Section 5. The background estimation and systematic uncertainties are\ndiscussed in Sections 6 and 7, respectively. The results and their interpretation are presented\nin Section 8, followed by a summary given in Section 9. Tabulated results are provided in the\nHEPData record for this analysis [28].\n\n\n\n3\n\n2 The CMS detector\nThe central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diame-\nter, providing a magnetic field of 3.8 T. Within the solenoid volume are a silicon pixel and strip\ntracker, a lead tungstate crystal electromagnetic calorimeter (ECAL), and a brass and scintilla-\ntor hadron calorimeter (HCAL), each composed of a barrel and two endcap sections. Forward\ncalorimeters extend the pseudorapidity (η) coverage provided by the barrel and endcap de-\ntectors. The muon detection system consists of a gas-ionization detector installed outside the\nsolenoid and embedded in the steel flux-return yoke.\n\nIn the barrel section of the ECAL, an energy resolution of about 1% is achieved for unconverted\nor late-converting photons in the tens of GeV energy range. The energy resolution of the re-\nmaining barrel photons is about 1.3% up to |η| = 1, changing to about 2.5% at |η| = 1.4. In the\nendcaps, the energy resolution is about 2.5% for unconverted or late-converting photons, and\nbetween 3 and 4% for the other ones [29]. The jet energy resolution amounts typically to 15–\n20% at 30 GeV, 10% at 100 GeV, and 5% at 1 TeV [30]. A more detailed description of the CMS\ndetector, together with a definition of the coordinate system used and the relevant kinematic\nvariables, can be found in Ref. [31].\n\nEvents of interest are selected using a two-tiered trigger system. The first level, composed of\ncustom hardware processors, uses information from the calorimeters and muon detectors to\nselect events at a rate of around 100 kHz within a fixed latency of about 4 µs [32]. The second\nlevel, known as the high-level trigger (HLT), consists of a farm of processors running a version\nof the full event reconstruction software optimized for fast processing, and reduces the event\nrate to around 1 kHz before data storage [33].\n\n3 Trigger selection\nEvents used in this analysis must pass a HLT single-photon trigger, which requires the photon\ntransverse momentum pT greater than 175 GeV in 2016, and greater than 200 GeV in 2017–2018.\nThe higher pT threshold in 2017–2018 is set to optimize available bandwidth and storage of\nevents for offline analysis. The trigger also requires that the fraction of energy associated with\nthe photon deposited in the HCAL is less than 15% of that deposited in the ECAL (H/E < 0.15).\nThe efficiency of single-photon triggers is calculated using the single-photon data set with a\nlow-pT requirement and is found to be 99%. To calculate the possible bias on single-photon\ntrigger due to any systematic detector effects, the efficiency is also calculated using jet- and\nmuon-triggered independent data sets. The trigger efficiency with the independent data sets\nis found to be about 97–98% and the trigger inefficiency is taken as an estimate of systematic\nuncertainty.\n\n4 Simulated data samples\nThe signal and background samples are obtained from event generators using Monte Carlo\n(MC) simulations. The signal samples for q∗ and b∗ are generated at leading order (LO) with the\nPYTHIA 8.205 (8.230) event generator [34] for 2016 (2017/2018) using coupling values f = 1.0,\n0.5, and 0.1 and different resonance masses. The generated events are processed through the\nfull CMS detector simulation based on GEANT4 [35]. Additional pp interactions in the same\nand nearby proton bunch crossings, referred to as pileup, are also simulated and a weight is ap-\nplied to simulated events to reproduce the same pileup distribution as measured in data. The\nsimulation uses the CUETP8M1 and CP5 underlying event tunes [36, 37] for 2016 and 2017–\n\n\n\n4\n\n2018 data sets, respectively, and renormalization (µR) and factorization scale (µF) correspond-\ning to µR = µF = µ = pT for the hard-scattered partons. The samples with the CUETP8M1\ntune use the NNPDF3.0 LO [38] parton distribution functions (PDFs), while simulated samples\ngenerated with the CP5 tune use the NNPDF3.1 next-to-next-LO [39] PDFs. For b∗ signals,\nonly events with Mb∗ within ±20% of the input Mb∗ are considered in order to avoid sizable\noff-shell nonresonant contributions, which are otherwise present for high-Mb∗ scenarios with\ncoupling parameters f = 0.5 and 1.0 but do not contribute to the search sensitivity. The sig-\nnals for intermediate mass values are extracted with an interpolation technique at intervals of\n0.1 TeV.\n\nThe QBH signal events in the ADD (n = 6) and the RS1 (n = 1) models are generated with\nthe QBH generator [40] version v3.0 using CTEQ6L [41] PDFs. The signals are generated for\nmasses ranging from 3.0 to 8.5 TeV for the ADD model and from 2.0 to 7.0 TeV for the RS1 model\nat intervals of 0.5 TeV. The γ+jet mass distribution for QBH is similar between the RS1 and\nADD models; therefore, the RS1 simulated sample is used for the ADD model for Mth < 3 TeV.\nThe resonance shapes for q∗, b∗, and QBH for the ADD (n = 6) and RS1 (n = 1) models for a\nmass of 4 TeV are shown in Fig. 2.\n\n0 1 2 3 4 5 6 7 8\nResonance mass [TeV]\n\n0\n\n0.05\n\n0.1\n\n0.15\n\n0.2\n\n0.25\n\na.\nu\n\nCMS\nSimulation\n\n13 TeV\n\nq*\n b*)→b* (bg \n\nADD QBH (n = 6)\nRS1 QBH (n = 1)\n\nFigure 2: Distributions of reconstructed γ+jet invariant mass for the q* and b* signal models\nwith resonance mass of 4 TeV, and for QBH from the ADD and RS1 models with Mth = 4 TeV.\n\nFigure 3 shows the product of the cross section (σ) and branching fraction B for the production\nat\n√\n\ns = 13 TeV of the photon and jet final state as a function of the resonance mass, for excited\nquark models, or the threshold mass, for QBH models.\n\nThe γ+jet, Drell–Yan, and W+jet background are simulated using the MADGRAPH5 aMC@NLO\n\nversion 2.2.2 (2.4.2) generators for 2016 (2017–2018) [42] at LO in QCD with the MLM matching\nscheme [43] between jets produced via matrix element calculations and from parton showers.\nThe QCD multijet background simulation is obtained at LO with the PYTHIA generator using\nversion 8.205 (8.230) for 2016 (2017–2018). Hadronization and parton showering of all sim-\nulated samples are performed using the PYTHIA program versions 8.205 and 8.230 with the\nCUETP8M1 and CP5 tunes, respectively.\n\n\n\n5\n\n1 2 3 4 5 6 7 8 9\nMass [TeV]\n\n7−10\n\n5−10\n\n3−10\n\n1−10\n\n10\n\n310\n\n510\n\n710\n\n910\n [f\n\nb]\nΒ σ\n\nCMS\nSimulation\n\n13 TeV\n\nADD QBH (n = 6)\nRS1 QBH (n = 1)\nq* f = 1.0\nq* f = 0.5\nb* f = 1.0\nb* f = 0.5\n\nFigure 3: The product of the cross section and branching fraction, σB, as a function of the\nresonance mass of q∗ or b∗ signals (Mq∗ or Mb∗ ) or the threshold mass of QBH signal models\n(Mth).\n\n5 Event reconstruction and selection\nThe particle-flow (PF) algorithm [44] reconstructs and identifies photons, electrons, muons,\ncharged and neutron hadrons (called PF candidates), with an optimized combination of in-\nformation from the various elements of the CMS detector. The energy of photons is obtained\nfrom the ECAL detector. The clusters of energy deposited in the ECAL are combined together\nwithin a defined geometric area to form a supercluster around the seed cluster [45]. The en-\nergy of electrons is determined from a combination of the electron momentum at the primary\ninteraction vertex as determined by the tracker, the energy of the corresponding ECAL cluster,\nand the energy sum of all bremsstrahlung photons spatially compatible with their origin from\nthe electron track. The energy of muons is obtained from the curvature of the corresponding\ntrack. The energy of charged hadrons is determined from a combination of their momentum\nmeasured in the tracker with the matched ECAL and HCAL energy deposits, corrected for\nthe response function of the calorimeters to hadronic showers. Finally, the energy of neutral\nhadrons is obtained from the corresponding corrected ECAL and HCAL energies.\n\nFor each event, hadronic jets are reconstructed from PF candidates using the infrared- and\ncollinear-safe anti-kT algorithm [46, 47] with a distance parameter of 0.4. Jet momentum is\ndetermined as the vectorial sum of all particle momenta in the jet, and is found from simula-\ntion to be, on average, within 5–10% of the true momentum over the whole pT spectrum and\ndetector acceptance. Pileup interactions can contribute additional tracks and calorimetric en-\nergy depositions to the jet momentum. To mitigate this effect, charged particles identified to\nbe originating from pileup vertices are discarded and an offset correction is applied to correct\nfor remaining contributions. Jet energy corrections are derived from simulation to bring the\nmeasured response of jets to that of particle level jets on average. In situ measurements of\nthe momentum balance in dijet, γ+jet, Z+jet, and multijet events are used to account for any\nresidual differences in the jet energy scale between data and simulation [30].\n\nThe primary vertex (PV) is taken to be the vertex corresponding to the hardest scattering in the\nevent, evaluated using tracking information alone, as described in Section 9.4.1 of Ref. [48].\n\n\n\n6\n\nCandidate events are required to have at least one photon with transverse momentum pγ\nT >\n\n240 GeV in the barrel region (|ηγ | < 1.44) of the detector. At the pγ\nT threshold of 240 GeV, the\n\ntrigger is more than 95% efficient. The photon with the highest pT is selected as the candidate\nphoton in the event. To reject jets misreconstructed as photons, candidate photons are required\nto satisfy identification and isolation requirements [45] having a selection efficiency of 80% on\nsignal-like events. The requirements placed on the identification and isolation variables are the\nfollowing:\n\n• The ratio H/E of the energy deposited in the single HCAL tower behind the ECAL\nsupercluster seed crystal over the total supercluster energy in ECAL within a cone\nof ∆R =\n\n√\n(∆η)2 + (∆φ)2 = 0.15 centered around the supercluster must be less than\n\n0.021.\n\n• The transverse η spread of the shower shape (σiηiη) [45] must be less than 0.01. This\nvariable differentiates between prompt photons and photons from π0 decays.\n\n• The pT sum of the charged hadrons within a cone of radius ∆R = 0.3 around the\nphoton must be less than 1.14 GeV.\n\n• The pT sum of the neutral hadrons within a cone of ∆R = 0.3 around the photon\nmust be less than 1.19 GeV + 0.015pγ\n\nT + 2.26× 10−5(pγ\nT)\n\n2/ GeV.\n\n• The pT sum of additional photons within a cone of ∆R = 0.3 around the photon\ncandidate must be less than 2.08 GeV + 0.0040pγ\n\nT .\n\n• An electron veto must also be applied to remove photon candidates in the cases\nwhere the candidate’s supercluster is matched to a reconstructed electron’s track\nthat has no missing hits in the innermost tracker layers.\n\nThe observed difference between data and MC simulation in the efficiency for photon identifi-\ncation and isolation is accounted for by applying a data-to-simulation scale factor, as a function\nof pT and η [45].\n\nEach candidate event is also required to have at least one jet that passes identification criteria\nin order to remove spurious jets arising from detector noise [49]. Among the selected jets, a list\nof jets having at least pjet\n\nT > 30 GeV and |ηjet| < 3.0 is made in decreasing order of pT. Setting a\nminimum value for pjet\n\nT reduces the number of pileup jets in the selected events.\n\nThe jets passing all the above criteria and calibrated as discussed above are clustered to form\nwide jets. The clustering captures final-state radiation and improves the γ+jet invariant mass\nresolution. To construct wide jets, the highest pT jet is used as a seed jet, and other jets are\nmerged with it if they are within ∆R < 1.1. The jets are merged by adding the four momenta\nof jets. The resultant jet is stored as a wide jet and the constituent jets are removed from the\njet list. The procedure is repeated with the remaining highest pT jet as a seed jet to form the\nnext wide jet. These clustered wide jets are ordered in pT and the highest one is used as the\nfinal jet candidate to study signal-like characteristics, such as the invariant mass of the photon\nand jet. The use of wide jets improves the mass resolution in the q∗/b∗ signal by 1.0–1.3%\nover the entire mass range considered in this analysis. The leading wide jet is required to\nhave pT(wide jet) > 170 GeV with |η(wide jet)| < 2.4. The final selected photon and wide-jet\ncandidates are required to be separated by ∆R > 1.1 and to be back-to-back in the azimuthal\nangle φ.\n\nA large reduction in the number of QCD multijet events is achieved by the requirements on\nphoton isolation. To suppress this background further, an additional requirement of |∆η| <\n1.5 is imposed on the photon and wide-jet system. This requirement mainly reduces QCD\n\n\n\n7\n\ndijet events produced by t-channel processes, which have a relatively large spread in ∆η. If\na leading wide-jet (or photon) candidate fails any of the selections described above, the event\nis discarded. The events selected are assigned to the ”inclusive category” for the q∗ and QBH\nsignal searches.\n\nThe b∗ signal search separates the data sets into two categories based on the identification of\njets originating from b quarks (b jets). The identification of b jets is performed using the neural\nnetwork-based DEEPJET tagger [50, 51] at an operating point with 75% b quark efficiency and\n1% light quarks misidentification probability. b tag category (events with at least 1 b tagged jet)\nand 0-b tag category (events without any b tagged jet). The sensitivity of the b∗ signal search\nis improved by combining the results of the 0-b tag category and of the b tag category. This\nis done to mitigate the effect of a slightly reduced acceptance of the b tag category at higher\nmasses.\n\nThe wide-jet, in the case of a b∗, is constructed with the same process described previously, but\nwith an additional requirement that at least one of the constituent jets within ∆R < 1.1 must\npass the b tag discriminator selection and fall into the b tag category. This jet will be referred to\nas a b-tagged jet. In a wide-jet, there could be one, or more b-tagged jets and also light jets. The\nsimulated distributions in both b tag and 0-b tag categories are weighted using scale factors\n(SF) that account for differences between data and simulation in the b tagging efficiencies.\n\nTo avoid the turn-on region in the photon + wide-jet invariant mass distribution that arises due\nto the various kinematic selections, only events with mγ+jet > 0.76 TeV are considered, where\nγ+jet denotes the photon and wide-jet system. The products of acceptance and efficiency for\nthe q∗/b∗ and QBH (ADD/RS1) signals are shown in Fig. 4 for the years 2016, 2017, and 2018.\nFor the ADD and RS1 signals with mass Mth > 5 TeV, the reduction in the product of acceptance\nand efficiency mainly comes from the application of photon isolation criteria. In the following\nsections, we will refer to wide-jets simply as jets.\n\n1 2 3 4 5 6\nResonance mass [TeV]\n\n0\n\n0.1\n\n0.2\n\n0.3\n\n0.4\n\n0.5\n\n0.6\n\n e\nffi\n\nci\nen\n\ncy\n×\n\nA\ncc\n\nep\nta\n\nnc\ne \n\n2016 q* 2017 q* 2018 q*\n\n2016 btag 2017 btag 2018 btag\n\n2016 0-btag 2017 0-btag 2018 0-btag\n\nCMS\nSimulation\n\n13 TeV\n\n2 3 4 5 6 7 8\n [TeV]thM\n\n0\n\n0.1\n\n0.2\n\n0.3\n\n0.4\n\n0.5\n\n0.6\n\n e\nffi\n\nci\nen\n\ncy\n×\n\nA\ncc\n\nep\nta\n\nnc\ne \n\n2016 ADD 2016 RS1\n\n2017 ADD 2017 RS1\n\n2018 ADD 2018 RS1\n\nCMS\nSimulation\n\n13 TeV\n\nFigure 4: The product of acceptance and efficiency for the q∗ signal in the inclusive category\nand the b∗ signal in the b tag and 0-b tag categories, for SM coupling f = 1.0 and for different\nresonance values (left), and the signal for the QBH (ADD/RS1) model in the inclusive category,\nfor different Mth values (right), for the years 2016, 2017, and 2018.\n\n6 Signal and background modeling\nThe background is estimated directly from data. However, MC-simulated background samples\nare used to perform optimization studies for the event selection and validation of various data\ndistributions.\n\n\n\n8\n\nTo extract the background from data, the γ+jet mass spectrum is parameterized with the fol-\nlowing empirical functional form\n\ndσ\n\ndm\n=\n\nP0(1−m/\n√\n\ns)P1\n\n(m/\n√\n\ns)P2+P3ln(m/\n√\n\ns)\n, (2)\n\nwhere P0, P1, P2, and P3 are the fit parameters, and\n√\n\ns = 13 TeV. The search uses the signal\nplus background fit method, where the mass spectrum is fitted with this functional form and\nthe signal template is obtained from simulation. The parameters P0, P1, P2, and P3 in this\nfunctional form are kept floating. This same functional form has also been used in a number\nof earlier searches [9, 11, 13, 14, 20] to describe the SM background distribution. The fitting\nrange for the q∗, b∗, and RS1 signal is 0.76 < mγ+jet < 8.40 TeV while for the ADD signal\ninterpretation, where a better signal sensitivity is reached, it is extended up to 9.4 TeV.\n\nThe invariant mass distributions for the γ+jet and γ+b jet channels, after all selections, are\nshown in Figs. 5 and 6, respectively. The bin size of the mass distribution is varied to match the\nγ+jet mass resolution, which is approximately 4.5% at 1 TeV and 3.3% at 6 TeV.\n\n1\n\n10\n\n210\n\n310\n\n410\n\n510\n\nE\nve\n\nnt\ns/\n\nbi\nn\n\nData\nFit to data\n\n 1 s.d.±Fit \n 2 s.d.±Fit \n\n (13 TeV)-1138 fb\n\nCMS\n\nq*(2.0 TeV, f = 1.0)\n\nADD(3.0 TeV)\n\nRS1(4.0 TeV)\n\n1−10×8 1 2 3 4 5 6 7 8 9\n [TeV]+jetγm\n\n2−\n0\n2\n\nst\nat\n\n. u\nnc\n\n.\nD\n\nat\na-\n\nF\nit\n\nFigure 5: Fit to the γ+jet invariant mass distribution in data with Eq. (2) for the ”inclusive”\ncategory of q∗ and QBH after all selections. Simulations of the q∗ signal with a 2 TeV mass\nand coupling f = 1.0, the QBH ADD signal with Mth = 3 TeV, and the QBH RS1 signal with\nMth = 4 TeV are also shown. The lower panel shows the difference between the data yield and\nthe background prediction divided by the statistical uncertainty of the data. The green (inner)\nand yellow (outer) bands, respectively, represent the 68 and 95% confidence level statistical\nuncertainties in the fit.\n\nAlternative polynomial functions with 4 and 5 parameters are also considered, to evaluate any\npossible bias due to the chosen functional form shown in Eq. (2). The choice of the background\nfunction is made on the basis of the results of the Fisher test [52]. The procedure used to eval-\nuate the possible bias is the following: pseudo-experiment data distributions are generated for\na given alternative function that is fitted to the invariant mass distribution of the SM back-\nground and injecting the signal of cross section corresponding to a value of 95% confidence\n\n\n\n9\n\n1\n\n10\n\n210\n\n310\n\n410\n\n510\n\nE\nve\n\nnt\ns/\n\nbi\nn\n\nData\nFit to data\n\n 1 s.d.±Fit \n 2 s.d.±Fit \n\n (13 TeV)-1138 fb\n\nCMS\n\nb*(2.0 TeV, f = 1.0)\n\nb*(1.0 TeV, f = 1.0)\nγ b→b* \n\nb tag Category\n\n1−10×8 1 2 3 4 5 6 7 8\n [TeV]+jetγm\n\n2−\n0\n2\n\nst\nat\n\n. u\nnc\n\n.\nD\n\nat\na-\n\nF\nit\n\n1\n\n10\n\n210\n\n310\n\n410\n\n510\n\nE\nve\n\nnt\ns/\n\nbi\nn\n\nData\nFit to data\n\n 1 s.d.±Fit \n 2 s.d.±Fit \n\n (13 TeV)-1138 fb\n\nCMS\n\nb*(2.0 TeV, f = 1.0)\n\nb*(1.0 TeV, f = 1.0)\n\nγ b→b* \n0-b tag Category\n\n1−10×8 1 2 3 4 5 6 7 8\n [TeV]+jetγm\n\n2−\n0\n2\n\nst\nat\n\n. u\nnc\n\n.\nD\n\nat\na-\n\nF\nit\n\nFigure 6: Fits to the γ+jet invariant mass distributions in data with Eq. (2) for the b∗ selection\nfor the b tag category (left) and 0-b tag category (right). Simulations of b∗ signals are shown for\nmass values of 1.0 and 2.0 TeV and for f = 1.0. The lower panel shows the difference between\nthe data yield and background prediction divided by the statistical uncertainty of the data. The\ngreen (inner) and yellow (outer) bands, respectively, represent the 68 and 95% confidence level\nstatistical uncertainties in the fit.\n\nlevel (CL) expected limit to it. These pseudo-experiment mass distributions are then fitted with\nthe functional form shown in Eq. (2) using the maximum log likelihood approach to obtain the\nfitted signal cross section. The possible bias due to the choice of the function is estimated by\nconstructing pull distributions for each mass hypothesis and for each alternative fit function,\nwhere the pull is the difference between the injected and extracted signal cross section divided\nby statistical uncertainty of extracted signal cross section. The pull distributions are found to\nhave a mean bias of less than one half standard deviation for the normalized Gaussian form.\nA bias of this magnitude is considered acceptable since it contributes ∼11% to the total uncer-\ntainty when added in quadrature with the statistical uncertainty and has a negligible effect on\nthe sensitivity to signal.\n\nTo test the goodness-of-fit for the function used for the alternate fit functions and for the func-\ntion described in Eq. (2), two different test statistics, the log-likelihood ratio and χ2, are used.\nThe test is performed by generating 1000 pseudo-datasets from the best fit model parame-\nters, and each pseudo-dataset is refitted with a maximum log likelihood fit. The estimated\np-value [53] for the test statistic is found to be greater than 5% for all the alternative fit func-\ntions.\n\n7 Systematic uncertainties\nThe systematic uncertainties due to various sources can affect both the normalization and the\nshape of the mass distribution. The dominant source of uncertainty comes from the parametriza-\ntion of the background fit to data. The background uncertainties are considered as floating\nnuisance parameters, while the uncertainties in the signal predictions are implemented either\nas log-normal or Gaussian constraints on the nuisance parameters.\n\nThe signal yield and shape are affected by the uncertainties related to the energy or momentum\nmeasurements for the reconstructed photons and jets.\n\nTo evaluate the effect of uncertainties in wide jets, the jet-related uncertainties are first applied\n\n\n\n10\n\nto the constituent jets. The jet energy scale and jet energy resolution effects are measured by\napplying the respective ±1 standard deviation uncertainties in the four-momenta of the con-\nstituent jets and reconstructing the mass of the γ+jet system. The effects of the jet energy scale\nand resolution on the mean and width of the signal shape are found to be in the range 1.0–2.0%.\n\nThe photon energy scale and photon energy resolution are measured with Z → e+e− events,\nwith the electrons reconstructed as photons, using the procedure described in Ref. [45]. The\nuncertainties in the photon energy scale and photon energy resolution translate into a varia-\ntion of 1.0–1.5% in the signal mean and width. The uncertainty associated with the photon\nidentification inefficiency due to the extrapolation at very high pT is taken to be about 10%,\nwhich covers all related systematic effects in the procedure used in its measurement.\n\nThe b∗ signal shape mean and yield have 0.2–3.0% and 7.9–14.3% uncertainties, respectively,\nobtained by varying the b tagging SF within its ±1 standard deviation uncertainty. The other\nsub-dominant uncertainties for the b∗ signal shape and normalization are found to be of the\norder of 1.0–2.0%, as in the case of q∗.\n\nTo account for the uncertainty in the HLT inefficiency as discussed in Section 3, a 2.5% system-\natic uncertainty is used.\n\nThe uncertainties associated with the integrated luminosity measurement [54–56] and pileup\nare also considered. The integrated luminosities of the 2016, 2017, and 2018 data-taking periods\nare individually known with uncertainties in the 1.2–2.5% range, while the total 2016–2018\nintegrated luminosity has an uncertainty of 1.6%, used in this paper. The uncertainty due\nto pileup is calculated by varying the inelastic cross section of 69.4 mb [57] by ±5% and its\nimpact is estimated to be ∼0.1% on the signal yield. The uncertainty in the signal shapes due\nto interpolation for intermediate masses is considered to be ∼1%, evaluated by comparing the\ninterpolated mass shape with the corresponding generated mass point.\n\nThe statistical interpretation considers the systematic uncertainties to be fully correlated among\ndifferent data-taking years, except for the integrated luminosity uncertainty, which is partially\ncorrelated between the years. The effect of uncorrelated systematic uncertainties is also studied\nby taking the respective uncertainties for each data set separately and obtaining the results\nagain. The results obtained are found to be similar to the case when fully correlated systematic\nuncertainties are considered for all years.\n\nThe details of systematic uncertainties and their relative effects on the shape and normalization\nare listed in Table 1.\n\nTable 1: Systematic uncertainties in the signal yields for the mass range analyzed.\n\nSource Type Uncertainty Applied to (q∗/b∗/QBH)\nIntegrated luminosity Normalization 1.6% All\nJet energy scale Shape (mean) ∼1.0% All\nJet energy resolution Shape (width) 0.6–1.9% All\nPhoton energy scale Shape (mean) ∼1.0% All\nPhoton energy resolution Shape (width) 0.4–1.2% All\nPileup Normalization 0.1% All\nHigh-pT photon efficiency Normalization ∼10.0% All\nHLT efficiency Normalization 2.5% All\nSignal shape interpolation Shape (mean) ∼1.0% All\nb tag SF uncertainty Shape (mean) 0.2–3.0% Only b∗\n\nb tag SF uncertainty Normalization 7.9–14.3% Only b∗\n\n\n\n11\n\n8 Results and interpretation\nThe observed mass spectrum is found to be consistent with the background-only prediction.\nWe set limits on potential signals by using a CLs approach [58, 59] based on an asymptotic\napproximation [60, 61] of the multibin counting experiment likelihood, taken to be a product\nof Poisson distributions corresponding to individual bins:\n\nL(data|µ, θ) =\nnbin\n\n∏\ni=1\n\nP (xi|si(µ, θ) + bi(θ))C(θ), (3)\n\nwhere P stands for the Poisson probability to observe xi data events in the ith bin, C represents\na constraint term for the nuisance parameters (θ) associated with the systematic uncertainties,\nµ is the signal strength (parameter of interest), si(µ, θ) the corresponding signal yield, bi(θ) the\ncorresponding background yield, and the product runs over the number of bins (nbin). The\nsystematic uncertainties are considered as nuisance parameters with log-normal constraints on\nthe integrated luminosity and trigger efficiency, and Gaussian constraints on the energy scales\nand resolutions for the photon and jet. The observed and expected limits are computed and\nshown in Figs. 7–9 in terms of the product of the cross-section and the branching fraction, σB.\n\nThe observed (expected) lower limits on Mq∗ are found to be 6.0 (6.0), 5.4 (5.2) and 2.4 (2.8) TeV\nfor the coupling strength f = 1.0, 0.5, and 0.1, respectively.\n\nFor the b∗ resonance search with the process bg → b∗ → bγ, the observed (expected) lower\nbounds are 2.2 (2.3) and 1.6 (1.7) TeV for a coupling strength of f = 1.0 and 0.5, respectively. For\nf = 0.1, the analysis did not have sufficient sensitivity to set a mass limit. For b∗ production via\nCI, several processes contribute, with the dominant one being qq → bb∗(or bb\n\n?\n) → bbγ. Us-\n\ning the same exclusion limit for the bg → b∗ signal with f = 1.0, the observed lower bound on\nthe b∗ mass is 3.8 TeV when combining both the processes (b∗ produced via gauge interaction\nand the resonant component of b∗ via CI) in the total signal cross section, as shown in Fig. 8\n(upper left).\n\nFor the QBH search with the ADD (RS1) model with n = 6 (1) extra dimensions, the observed\nlower bound is set to 7.5 (5.2) TeV and the expected exclusion limits are estimated to have the\nsame values. In comparison to q∗, the limits are weaker for b∗ resonances and QBH resonances\nat higher masses.\n\nThe two-dimensional representation of the excluded mass region for excited quarks (q∗ and b∗)\nas a function of the coupling strength f , with the assumption Mq∗ = Λ, is shown in Fig. 10.\nThe exclusion of the excited quark mass, as a function of Mq∗/Λ, is also presented in the same\nfigure on the right hand axis. The excluded Mq∗ region could also be interpreted in terms\nof the Mq∗/Λ ratio; this interpretation is based on the fact that the detector resolution effects\ndominate compared to the change in the signal intrinsic width (Γq∗ ∼ 0.03 f 2Mq∗ ) [4] arising\nfrom the change in the coupling strength f . Consequently, the variation of f effectively changes\nthe production cross section in a similar way to the variations in Mq∗/Λ, since both appear as\nmultiplicative factors in the cross section calculation.\n\n9 Summary\nA search for resonances in the γ+jet final state has been performed using proton-proton colli-\nsion data at\n\n√\ns = 13 TeV, corresponding to an integrated luminosity of 138 fb−1. The results\n\nare compared with standard model extensions postulating excited quarks, excited b quarks,\nand quantum black holes.\n\n\n\n12\n\n1 2 3 4 5 6 7\nResonance mass [TeV]\n\n5−10\n\n4−10\n\n3−10\n\n2−10\n\n1−10\n\n1\n\n [p\nb]\n\nΒ σ \n\nCMS\n\n (13 TeV)-1138 fb\n\nγ q→q* \n95% CL limits\n\nObserved\nExpected\n\n 1 std. deviation±Expected \n 2 std. deviation±Expected \n\nExcited quark (f=1.0)  \n\n \n\n1 2 3 4 5 6 7\nResonance mass [TeV]\n\n5−10\n\n4−10\n\n3−10\n\n2−10\n\n1−10\n\n1\n\n [p\nb]\n\nΒ σ \n\nCMS\n\n (13 TeV)-1138 fb\n\nγ q→q* \n95% CL limits\n\nObserved\nExpected\n\n 1 std. deviation±Expected \n 2 std. deviation±Expected \n\nExcited quark (f=0.5)  \n\n \n\n1 2 3 4 5 6 7\nResonance mass [TeV]\n\n5−10\n\n4−10\n\n3−10\n\n2−10\n\n1−10\n\n1\n\n [p\nb]\n\nΒ σ \n\nCMS\n\n (13 TeV)-1138 fb\n\nγ q→q* \n95% CL limits\n\nObserved\nExpected\n\n 1 std. deviation±Expected \n 2 std. deviation±Expected \n\nExcited quark (f=0.1)  \n\n \n\nFigure 7: The expected (dashed) and observed (solid) 95% CL upper limits on the product of\nthe cross section and branching fraction, as functions of q∗ mass, for coupling strength f =\n1.0 (upper left), f = 0.5 (upper right), and f = 0.1 (lower). The green (inner) and yellow\n(outer) bands correspond to 1 and 2 standard deviation uncertainties in the expected limit,\nrespectively. The limits are compared with the theoretical predictions for q∗ production for the\ncorresponding coupling strengths.\n\n\n\n13\n\n1 2 3 4 5 6 7\nResonance mass [TeV]\n\n5−10\n\n4−10\n\n3−10\n\n2−10\n\n1−10\n\n1\n\n [p\nb]\n\nΒ σ \n\nCMS\n\n (13 TeV)-1138 fb\n\nγ b→b* 95% CL upper limits\nObserved\nMedian expected\n\n 1 std. deviation±Expected \n 2 std. deviation±Expected \n\nb*, f=1.0)→Excited b quark (bg\nExcited b quark (b* via CI)\nExcited b quark (Total b*)\n\n \n\n1 2 3 4 5 6 7\nResonance mass [TeV]\n\n5−10\n\n4−10\n\n3−10\n\n2−10\n\n1−10\n\n1\n\n [p\nb]\n\nΒ σ \n\nCMS\n\n (13 TeV)-1138 fb\n\nγ b→b* \n95% CL limits\n\nObserved\nExpected\n\n 1 std. deviation±Expected \n 2 std. deviation±Expected \n\nb*, f=0.5)→Excited b-quark (bg\n\n \n\n1 2 3 4 5 6 7\nResonance mass [TeV]\n\n5−10\n\n4−10\n\n3−10\n\n2−10\n\n1−10\n\n1\n\n [p\nb]\n\nΒ σ \n\nCMS\n\n (13 TeV)-1138 fb\n\nγ b→b* 95% CL limits\nObserved\nExpected\n\n 1 std. deviation±Expected \n 2 std. deviation±Expected \n\nb*, f=0.1)→Excited b-quark (bg\n\n \n\nFigure 8: The expected (dashed) and observed (solid) 95% CL upper limits on the product of\nthe cross section and branching fraction, as functions of b∗ mass, for coupling strength f =\n1.0 (upper left), f = 0.5 (upper right), and f = 0.1 (lower). The green (inner) and yellow\n(outer) bands correspond to 1 and 2 standard deviation uncertainties in the expected limit,\nrespectively. The limits are compared with the theoretical predictions for b∗ production for\nthe corresponding coupling strengths. For coupling f = 1.0, the limits are compared for b∗\n\nproduction by gauge interactions (red), contact interactions (violet), and total b∗ signal by the\naddition of these two production modes.\n\nFor the coupling strength f = 1.0, the observed (expected) lower mass bounds on the ex-\ncited light-flavor quarks and excited bottom quarks from gauge interactions are estimated to\nbe 6.0 (6.0) and 2.2 (2.3) TeV, respectively. For the same coupling strength, the observed lower\nmass bounds on the excited bottom quarks extends to 3.8 TeV, when the production mode from\ncontact interactions is also considered. For quantum black hole production, observed exclu-\nsion limits are estimated to be 7.5 and 5.2 TeV for the Arkani-Hamed–Dimopoulos–Dvali and\nthe Randall–Sundrum models with 6 and 1 extra dimensions, respectively. These lower mass\nbounds are the most stringent to date among those obtained in the γ+jet final state.\n\n\n\n14\n\n2 3 4 5 6 7 8\n [TeV]thM\n\n5−10\n\n4−10\n\n3−10\n\n2−10\n\n1−10\n\n1\n\n [p\nb]\n\nΒ σ \n\nCMS\n\n (13 TeV)-1138 fb\n\nγ q→ADD QBH (n=6) \n95% CL limits\n\nObserved\nExpected\n\n 1 std. deviation±Expected \n 2 std. deviation±Expected \n\nADD QBH (n=6)  \n\n \n\n2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7\n [TeV]thM\n\n5−10\n\n4−10\n\n3−10\n\n2−10\n\n1−10\n\n1\n\n [p\nb]\n\nΒ σ \n\nCMS\n\n (13 TeV)-1138 fb\n\nγ q→RS1 QBH (n=1) \n95% CL limits\n\nObserved\nExpected\n\n 1 std. deviation±Expected \n 2 std. deviation±Expected \n\nRS1 QBH (n=1)  \n\n \n\nFigure 9: The expected (dashed) and observed (solid) 95% CL upper limit on the product of\nthe cross section and branching fraction as a function of the minimum black hole mass for the\nADD (n = 6) and RS1 (n = 1) models on the left and right, respectively. The green (inner) and\nyellow (outer) bands correspond to 1 and 2 standard deviation uncertainties in the expected\nlimit. The limits are compared with the theoretical predictions for QBH production for ADD\n(n = 6) and RS1 (n = 1) models.\n\n1 2 3 4 5 6 7 8 9\nResonance mass [TeV]\n\n0\n\n0.2\n\n0.4\n\n0.6\n\n0.8\n\n1)f\nC\n\nou\npl\n\nin\ngs\n\n (\n\n0\n\n0.2\n\n0.4\n\n0.6\n\n0.8\n\n1\n\nΛ/\nq*\n\nM\n\n (13 TeV)-1138 fb\n\nCMS\n\nγ q → Exp. excluded q* \n\n γ b → Exp. excluded b* \n\nγ q → Obs. excluded q* \n\n γ b → Obs. excluded b* \n\nFigure 10: The expected and observed 95% CL exclusion mass limit variation with the SM\ncouplings for the excited q∗ and b∗ signal models.\n\nAcknowledgments\nWe congratulate our colleagues in the CERN accelerator departments for the excellent perfor-\nmance of the LHC and thank the technical and administrative staffs at CERN and at other\n\n\n\n15\n\nCMS institutes for their contributions to the success of the CMS effort. In addition, we grate-\nfully acknowledge the computing centers and personnel of the Worldwide LHC Computing\nGrid and other centers for delivering so effectively the computing infrastructure essential to\nour analyses. Finally, we acknowledge the enduring support for the construction and oper-\nation of the LHC, the CMS detector, and the supporting computing infrastructure provided\nby the following funding agencies: BMBWF and FWF (Austria); FNRS and FWO (Belgium);\nCNPq, CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES and BNSF (Bulgaria); CERN;\nCAS, MoST, and NSFC (China); MINCIENCIAS (Colombia); MSES and CSF (Croatia); RIF\n(Cyprus); SENESCYT (Ecuador); MoER, ERC PUT and ERDF (Estonia); Academy of Finland,\nMEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany);\nGSRI (Greece); NKFIH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN\n(Italy); MSIP and NRF (Republic of Korea); MES (Latvia); LAS (Lithuania); MOE and UM\n(Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MOS (Mon-\ntenegro); MBIE (New Zealand); PAEC (Pakistan); MES and NSC (Poland); FCT (Portugal);\nMESTD (Serbia); MCIN/AEI and PCTI (Spain); MOSTR (Sri Lanka); Swiss Funding Agen-\ncies (Switzerland); MST (Taipei); MHESI and NSTDA (Thailand); TUBITAK and TENMAK\n(Turkey); NASU (Ukraine); STFC (United Kingdom); DOE and NSF (USA).\n\nIndividuals have received support from the Marie-Curie program and the European Re-\nsearch Council and Horizon 2020 Grant, contract Nos. 675440, 724704, 752730, 758316, 765710,\n824093, 884104, and COST Action CA16108 (European Union); the Leventis Foundation; the\nAlfred P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal\nScience Policy Office; the Fonds pour la Formation à la Recherche dans l’Industrie et dans\nl’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technolo-\ngie (IWT-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the “Excellence of Science –\nEOS” – be.h project n. 30820817; the Beijing Municipal Science & Technology Commission,\nNo. Z191100007219010; the Ministry of Education, Youth and Sports (MEYS) of the Czech\nRepublic; the Hellenic Foundation for Research and Innovation (HFRI), Project Number 2288\n(Greece); the Deutsche Forschungsgemeinschaft (DFG), under Germany’s Excellence Strategy –\nEXC 2121 “Quantum Universe” – 390833306, and under project number 400140256 - GRK2497;\nthe Hungarian Academy of Sciences, the New National Excellence Program - ÚNKP, the NK-\nFIH research grants K 124845, K 124850, K 128713, K 128786, K 129058, K 131991, K 133046, K\n138136, K 143460, K 143477, 2020-2.2.1-ED-2021-00181, and TKP2021-NKTA-64 (Hungary); the\nCouncil of Science and Industrial Research, India; the Latvian Council of Science; the Ministry\nof Education and Science, project no. 2022/WK/14, and the National Science Center, con-\ntracts Opus 2021/41/B/ST2/01369 and 2021/43/B/ST2/01552 (Poland); the Fundação para\na Ciência e a Tecnologia, grant CEECIND/01334/2018 (Portugal); the National Priorities Re-\nsearch Program by Qatar National Research Fund; MCIN/AEI/10.13039/501100011033, ERDF\n“a way of making Europe”, and the Programa Estatal de Fomento de la Investigación Cientı́fica\ny Técnica de Excelencia Marı́a de Maeztu, grant MDM-2017-0765 and Programa Severo Ochoa\ndel Principado de Asturias (Spain); the Chulalongkorn Academic into Its 2nd Century Project\nAdvancement Project, and the National Science, Research and Innovation Fund via the Pro-\ngram Management Unit for Human Resources & Institutional Development, Research and In-\nnovation, grant B05F650021 (Thailand); the Kavli Foundation; the Nvidia Corporation; the Su-\nperMicro Corporation; the Welch Foundation, contract C-1845; and the Weston Havens Foun-\ndation (USA).\n\n\n\n16\n\nReferences\n[1] M. 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Tumasyan1\n\nInstitut für Hochenergiephysik, Vienna, Austria\nW. Adam , J.W. Andrejkovic, T. Bergauer , S. Chatterjee , K. Damanakis , M. Dragice-\nvic , A. Escalante Del Valle , P.S. Hussain , M. Jeitler2 , N. Krammer , L. Lechner ,\nD. Liko , I. Mikulec , P. Paulitsch, J. Schieck2 , R. Schöfbeck , D. Schwarz ,\nM. Sonawane , S. Templ , W. Waltenberger , C.-E. Wulz2\n\nUniversiteit Antwerpen, Antwerpen, Belgium\nM.R. Darwish3 , T. Janssen , T. Kello4, P. Van Mechelen\n\nVrije Universiteit Brussel, Brussel, Belgium\nE.S. Bols , J. D’Hondt , A. De Moor , M. Delcourt , H. El Faham , S. Lowette ,\nA. Morton , D. Müller , A.R. Sahasransu , S. Tavernier , W. Van Doninck, S. Van Putte ,\nD. Vannerom\n\nUniversité Libre de Bruxelles, Bruxelles, Belgium\nB. Clerbaux , S. Dansana , G. De Lentdecker , L. Favart , D. Hohov , J. Jaramillo ,\nK. Lee , M. Mahdavikhorrami , I. Makarenko , A. Malara , S. Paredes , L. Pétré ,\nN. Postiau, L. Thomas , M. Vanden Bemden, C. Vander Velde , P. Vanlaer\n\nGhent University, Ghent, Belgium\nD. Dobur , J. Knolle , L. Lambrecht , G. Mestdach, C. Rendón, A. Samalan, K. Skovpen ,\nM. Tytgat , N. Van Den Bossche , B. Vermassen, L. Wezenbeek\n\nUniversité Catholique de Louvain, Louvain-la-Neuve, Belgium\nA. Benecke , G. Bruno , F. Bury , C. Caputo , P. David , C. Delaere , I.S. Donertas ,\nA. Giammanco , K. Jaffel , Sa. Jain , V. Lemaitre, K. Mondal , A. Taliercio , T.T. Tran ,\nP. Vischia , S. Wertz\n\nCentro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil\nG.A. Alves , E. Coelho , C. Hensel , A. Moraes , P. Rebello Teles\n\nUniversidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil\nW.L. Aldá Júnior , M. Alves Gallo Pereira , M. Barroso Ferreira Filho , H. Bran-\ndao Malbouisson , W. Carvalho , J. Chinellato5, E.M. Da Costa , G.G. Da Silveira6 ,\nD. De Jesus Damiao , V. Dos Santos Sousa , S. Fonseca De Souza , J. Martins7 ,\nC. Mora Herrera , K. Mota Amarilo , L. Mundim , H. Nogima , A. Santoro ,\nS.M. Silva Do Amaral , A. Sznajder , M. Thiel , A. Vilela Pereira\n\nUniversidade Estadual Paulista, Universidade Federal do ABC, São Paulo, Brazil\nC.A. Bernardes6 , L. Calligaris , T.R. Fernandez Perez Tomei , E.M. Gregores ,\nP.G. Mercadante , S.F. Novaes , Sandra S. Padula\n\nInstitute for Nuclear Research and Nuclear Energy, Bulgarian Academy of Sciences, Sofia,\nBulgaria\nA. Aleksandrov , G. Antchev , R. Hadjiiska , P. Iaydjiev , M. Misheva , M. Rodozov,\nM. Shopova , G. Sultanov\n\nUniversity of Sofia, Sofia, Bulgaria\nA. Dimitrov , T. Ivanov , L. Litov , B. Pavlov , P. Petkov , A. Petrov, E. Shumka\n\nInstituto De Alta Investigación, Universidad de Tarapacá, Casilla 7 D, Arica, Chile\n\nhttps://orcid.org/0009-0000-0684-6742\nhttps://orcid.org/0000-0001-9099-4341\nhttps://orcid.org/0000-0002-5786-0293\nhttps://orcid.org/0000-0003-2660-0349\nhttps://orcid.org/0000-0001-5389-2872\nhttps://orcid.org/0000-0003-1967-6783\nhttps://orcid.org/0000-0002-9702-6359\nhttps://orcid.org/0000-0002-4825-5278\nhttps://orcid.org/0000-0002-5141-9560\nhttps://orcid.org/0000-0002-0548-0985\nhttps://orcid.org/0000-0002-3065-1141\nhttps://orcid.org/0000-0002-3380-473X\nhttps://orcid.org/0000-0003-0385-2746\nhttps://orcid.org/0000-0002-1058-8093\nhttps://orcid.org/0000-0002-2332-8784\nhttps://orcid.org/0000-0002-3821-7331\nhttps://orcid.org/0000-0003-0510-7010\nhttps://orcid.org/0000-0003-3137-5692\nhttps://orcid.org/0000-0002-6215-7228\nhttps://orcid.org/0000-0001-9226-5812\nhttps://orcid.org/0000-0003-2894-2377\nhttps://orcid.org/0000-0002-3998-4081\nhttps://orcid.org/0000-0002-8731-9051\nhttps://orcid.org/0000-0002-8564-8732\nhttps://orcid.org/0000-0002-9598-6241\nhttps://orcid.org/0000-0001-5964-1935\nhttps://orcid.org/0000-0001-8206-1787\nhttps://orcid.org/0000-0001-8894-2390\nhttps://orcid.org/0000-0003-3984-9987\nhttps://orcid.org/0000-0002-9919-3492\nhttps://orcid.org/0000-0002-1752-4527\nhttps://orcid.org/0000-0003-1505-1743\nhttps://orcid.org/0000-0002-6792-9522\nhttps://orcid.org/0000-0003-1559-3606\nhttps://orcid.org/0000-0002-2747-5095\nhttps://orcid.org/0000-0001-8547-8211\nhttps://orcid.org/0000-0002-7752-7471\nhttps://orcid.org/0000-0001-5124-7693\nhttps://orcid.org/0000-0003-1645-7454\nhttps://orcid.org/0000-0002-4760-1597\nhttps://orcid.org/0000-0003-3885-6608\nhttps://orcid.org/0000-0003-0808-4184\nhttps://orcid.org/0000-0002-8265-3595\nhttps://orcid.org/0000-0002-8553-4508\nhttps://orcid.org/0000-0001-8645-9282\nhttps://orcid.org/0000-0001-8487-9603\nhttps://orcid.org/0009-0000-7979-5771\nhttps://orcid.org/0000-0002-2756-3853\nhttps://orcid.org/0000-0003-3392-7294\nhttps://orcid.org/0000-0002-7931-4496\nhttps://orcid.org/0000-0003-0012-4866\nhttps://orcid.org/0000-0002-4781-5704\nhttps://orcid.org/0000-0001-9108-1560\nhttps://orcid.org/0000-0002-1160-0621\nhttps://orcid.org/0000-0002-3990-2074\nhttps://orcid.org/0000-0003-2973-4991\nhttps://orcid.org/0000-0001-6952-891X\nhttps://orcid.org/0000-0003-0252-3609\nhttps://orcid.org/0000-0001-8857-8197\nhttps://orcid.org/0000-0002-3077-2090\nhttps://orcid.org/0000-0001-7522-4808\nhttps://orcid.org/0000-0001-9260-9371\nhttps://orcid.org/0000-0001-8707-6021\nhttps://orcid.org/0000-0001-7485-412X\nhttps://orcid.org/0000-0001-9640-8294\nhttps://orcid.org/0000-0001-7419-4248\nhttps://orcid.org/0000-0001-5078-3689\nhttps://orcid.org/0000-0001-5967-1245\nhttps://orcid.org/0000-0002-5119-6280\nhttps://orcid.org/0000-0003-3060-350X\nhttps://orcid.org/0000-0002-7088-8557\nhttps://orcid.org/0000-0002-8645-3670\nhttps://orcid.org/0000-0002-8369-1446\nhttps://orcid.org/0000-0001-6114-9907\nhttps://orcid.org/0000-0001-8874-7624\nhttps://orcid.org/0000-0002-5157-5686\nhttps://orcid.org/0000-0001-9029-8506\nhttps://orcid.org/0000-0001-5855-9817\nhttps://orcid.org/0000-0003-4296-7028\nhttps://orcid.org/0000-0003-3904-0571\nhttps://orcid.org/0000-0002-1326-318X\nhttps://orcid.org/0000-0003-0738-6615\nhttps://orcid.org/0000-0002-5016-6434\nhttps://orcid.org/0000-0003-3514-7056\nhttps://orcid.org/0000-0002-3769-1680\nhttps://orcid.org/0000-0002-4681-9340\nhttps://orcid.org/0000-0001-7830-0837\nhttps://orcid.org/0000-0002-2120-2782\nhttps://orcid.org/0000-0003-3915-3170\nhttps://orcid.org/0000-0003-1707-3348\nhttps://orcid.org/0000-0001-9964-7805\nhttps://orcid.org/0000-0001-7705-1066\nhttps://orcid.org/0000-0002-0568-665X\nhttps://orcid.org/0000-0002-0209-9687\nhttps://orcid.org/0000-0001-6998-1108\nhttps://orcid.org/0000-0001-7139-7963\nhttps://orcid.org/0000-0003-3177-4626\nhttps://orcid.org/0000-0001-5790-9563\nhttps://orcid.org/0000-0002-9951-9448\nhttps://orcid.org/0000-0002-1809-5226\nhttps://orcid.org/0000-0003-0205-1672\nhttps://orcid.org/0000-0001-8333-4302\nhttps://orcid.org/0000-0003-0471-8549\nhttps://orcid.org/0000-0003-3071-0559\nhttps://orcid.org/0000-0001-6934-2541\nhttps://orcid.org/0000-0003-3210-5037\nhttps://orcid.org/0000-0003-1824-1737\nhttps://orcid.org/0000-0001-6330-0607\nhttps://orcid.org/0000-0003-4854-5301\nhttps://orcid.org/0000-0001-6664-2493\nhttps://orcid.org/0000-0002-8030-3866\nhttps://orcid.org/0000-0003-2899-701X\nhttps://orcid.org/0000-0003-0489-9191\nhttps://orcid.org/0000-0002-8511-6883\nhttps://orcid.org/0000-0003-3635-0646\nhttps://orcid.org/0000-0002-0420-9480\nhttps://orcid.org/0000-0002-0104-2574\n\n\n22\n\nS.Thakur\n\nBeihang University, Beijing, China\nT. Cheng , Q. Guo, T. Javaid8 , M. Mittal , L. Yuan\n\nDepartment of Physics, Tsinghua University, Beijing, China\nG. Bauer9, Z. Hu , S. Lezki , K. Yi9,10\n\nInstitute of High Energy Physics, Beijing, China\nG.M. Chen8 , H.S. Chen8 , M. Chen8 , F. Iemmi , C.H. Jiang, A. Kapoor , H. Liao , Z.-\nA. Liu11 , V. Milosevic , F. Monti , R. Sharma , J. Tao , J. Thomas-Wilsker , J. Wang ,\nH. Zhang , J. Zhao\n\nState Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China\nA. Agapitos , Y. An , Y. Ban , A. Carvalho Antunes De Oliveira , A. Levin , C. Li ,\nQ. Li , X. Lyu, Y. Mao, S.J. Qian , X. Sun , D. Wang , J. Xiao , H. Yang\n\nSun Yat-Sen University, Guangzhou, China\nM. Lu , Z. You\n\nUniversity of Science and Technology of China, Hefei, China\nN. Lu\n\nInstitute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam\nApplication (MOE) - Fudan University, Shanghai, China\nX. Gao4 , D. Leggat, H. Okawa , Y. Zhang\n\nZhejiang University, Hangzhou, Zhejiang, China\nZ. Lin , C. Lu , M. Xiao\n\nUniversidad de Los Andes, Bogota, Colombia\nC. Avila , D.A. Barbosa Trujillo, A. Cabrera , C. Florez , J. Fraga\n\nUniversidad de Antioquia, Medellin, Colombia\nJ. Mejia Guisao , F. Ramirez , M. Rodriguez , J.D. Ruiz Alvarez\n\nUniversity of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval\nArchitecture, Split, Croatia\nD. Giljanovic , N. Godinovic , D. Lelas , I. Puljak\n\nUniversity of Split, Faculty of Science, Split, Croatia\nZ. Antunovic, M. Kovac , T. Sculac\n\nInstitute Rudjer Boskovic, Zagreb, Croatia\nP. Bargassa , V. Brigljevic , B.K. Chitroda , D. Ferencek , S. Mishra , M. Roguljic ,\nA. Starodumov12 , T. Susa\n\nUniversity of Cyprus, Nicosia, Cyprus\nA. Attikis , K. Christoforou , S. Konstantinou , J. Mousa , C. Nicolaou, F. Ptochos ,\nP.A. Razis , H. Rykaczewski, H. Saka , A. Stepennov\n\nCharles University, Prague, Czech Republic\nM. Finger12 , M. Finger Jr.12 , A. Kveton\n\nEscuela Politecnica Nacional, Quito, Ecuador\nE. Ayala\n\nUniversidad San Francisco de Quito, Quito, Ecuador\n\nhttps://orcid.org/0000-0002-1647-0360\nhttps://orcid.org/0000-0003-2954-9315\nhttps://orcid.org/0009-0007-2757-4054\nhttps://orcid.org/0000-0002-6833-8521\nhttps://orcid.org/0000-0002-6719-5397\nhttps://orcid.org/0000-0001-8209-4343\nhttps://orcid.org/0000-0002-6909-774X\nhttps://orcid.org/0000-0002-2459-1824\nhttps://orcid.org/0000-0002-2629-5420\nhttps://orcid.org/0000-0001-8672-8227\nhttps://orcid.org/0000-0003-0489-9669\nhttps://orcid.org/0000-0001-5911-4051\nhttps://orcid.org/0000-0002-1844-1504\nhttps://orcid.org/0000-0002-0124-6999\nhttps://orcid.org/0000-0002-2896-1386\nhttps://orcid.org/0000-0002-1173-0696\nhttps://orcid.org/0000-0001-5846-3655\nhttps://orcid.org/0000-0003-1181-1426\nhttps://orcid.org/0000-0003-2006-3490\nhttps://orcid.org/0000-0003-1293-4153\nhttps://orcid.org/0000-0002-3103-1083\nhttps://orcid.org/0000-0001-8843-5209\nhttps://orcid.org/0000-0001-8365-7726\nhttps://orcid.org/0000-0002-8953-1232\nhttps://orcid.org/0000-0003-1299-1879\nhttps://orcid.org/0000-0002-1912-0374\nhttps://orcid.org/0000-0003-2340-836X\nhttps://orcid.org/0000-0001-9565-4186\nhttps://orcid.org/0000-0002-6339-8154\nhttps://orcid.org/0000-0002-8290-0517\nhttps://orcid.org/0000-0002-0630-481X\nhttps://orcid.org/0000-0003-4409-4574\nhttps://orcid.org/0000-0002-9013-1199\nhttps://orcid.org/0000-0002-7860-3958\nhttps://orcid.org/0000-0002-6999-3931\nhttps://orcid.org/0000-0001-8324-3291\nhttps://orcid.org/0000-0002-2631-6770\nhttps://orcid.org/0000-0001-7205-2318\nhttps://orcid.org/0000-0002-2548-6567\nhttps://orcid.org/0000-0002-4554-2554\nhttps://orcid.org/0000-0003-1812-3474\nhttps://orcid.org/0000-0002-7421-0313\nhttps://orcid.org/0000-0001-9628-9336\nhttps://orcid.org/0000-0002-5610-2693\nhttps://orcid.org/0000-0002-0486-6296\nhttps://orcid.org/0000-0002-3222-0249\nhttps://orcid.org/0000-0002-5137-8543\nhttps://orcid.org/0000-0002-1153-816X\nhttps://orcid.org/0000-0002-7178-0484\nhttps://orcid.org/0000-0002-9480-213X\nhttps://orcid.org/0000-0002-3306-0363\nhttps://orcid.org/0009-0005-6792-6881\nhttps://orcid.org/0000-0002-4674-9450\nhttps://orcid.org/0000-0002-8269-5760\nhttps://orcid.org/0000-0001-7387-3812\nhttps://orcid.org/0000-0002-2391-4599\nhttps://orcid.org/0000-0002-9578-4105\nhttps://orcid.org/0000-0001-8612-3332\nhttps://orcid.org/0000-0001-5847-0062\nhttps://orcid.org/0000-0002-0220-8441\nhttps://orcid.org/0000-0001-9116-1202\nhttps://orcid.org/0000-0002-3510-4833\nhttps://orcid.org/0000-0001-5311-3007\nhttps://orcid.org/0000-0001-9570-9255\nhttps://orcid.org/0000-0001-7430-2552\nhttps://orcid.org/0000-0002-4443-3794\nhttps://orcid.org/0000-0003-2205-1100\nhttps://orcid.org/0000-0003-0408-7636\nhttps://orcid.org/0000-0002-2978-2718\nhttps://orcid.org/0000-0002-3432-3452\nhttps://orcid.org/0000-0002-4855-0162\nhttps://orcid.org/0000-0001-7616-2573\nhttps://orcid.org/0000-0001-7747-6582\nhttps://orcid.org/0000-0002-7828-9970\nhttps://orcid.org/0000-0003-3155-2484\nhttps://orcid.org/0000-0001-8197-1914\nhttps://orcid.org/0000-0002-0363-9198\n\n\n23\n\nE. Carrera Jarrin\n\nAcademy of Scientific Research and Technology of the Arab Republic of Egypt, Egyptian\nNetwork of High Energy Physics, Cairo, Egypt\nY. Assran13,14, S. Elgammal14\n\nCenter for High Energy Physics (CHEP-FU), Fayoum University, El-Fayoum, Egypt\nM. Abdullah Al-Mashad , M.A. Mahmoud\n\nNational Institute of Chemical Physics and Biophysics, Tallinn, Estonia\nS. Bhowmik , R.K. Dewanjee , K. Ehataht , M. Kadastik, T. Lange , S. Nandan ,\nC. Nielsen , J. Pata , M. Raidal , L. Tani , C. Veelken\n\nDepartment of Physics, University of Helsinki, Helsinki, Finland\nP. Eerola , H. Kirschenmann , K. Osterberg , M. Voutilainen\n\nHelsinki Institute of Physics, Helsinki, Finland\nS. Bharthuar , E. Brücken , F. Garcia , J. Havukainen , M.S. Kim , R. Kinnunen,\nT. Lampén , K. Lassila-Perini , S. Lehti , T. Lindén , M. Lotti, L. Martikainen ,\nM. Myllymäki , M.m. Rantanen , H. Siikonen , E. Tuominen , J. Tuominiemi\n\nLappeenranta-Lahti University of Technology, Lappeenranta, Finland\nP. Luukka , H. Petrow , T. Tuuva†\n\nIRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France\nC. Amendola , M. Besancon , F. Couderc , M. Dejardin , D. Denegri, J.L. Faure,\nF. Ferri , S. Ganjour , P. Gras , G. Hamel de Monchenault , V. Lohezic , J. Malcles ,\nJ. Rander, A. Rosowsky , M.Ö. Sahin , A. Savoy-Navarro15 , P. Simkina , M. Titov\n\nLaboratoire Leprince-Ringuet, CNRS/IN2P3, Ecole Polytechnique, Institut Polytechnique\nde Paris, Palaiseau, France\nC. Baldenegro Barrera , F. Beaudette , A. Buchot Perraguin , P. Busson , A. Cappati ,\nC. Charlot , F. Damas , O. Davignon , B. Diab , G. Falmagne , B.A. Fontana San-\ntos Alves , S. Ghosh , R. Granier de Cassagnac , A. Hakimi , B. Harikrishnan ,\nG. Liu , J. Motta , M. Nguyen , C. Ochando , L. Portales , R. Salerno , U. Sarkar ,\nJ.B. Sauvan , Y. Sirois , A. Tarabini , E. Vernazza , A. Zabi , A. Zghiche\n\nUniversité de Strasbourg, CNRS, IPHC UMR 7178, Strasbourg, France\nJ.-L. Agram16 , J. Andrea , D. Apparu , D. Bloch , G. Bourgatte , J.-M. Brom ,\nE.C. Chabert , C. Collard , D. Darej, U. Goerlach , C. Grimault, A.-C. Le Bihan ,\nP. Van Hove\n\nInstitut de Physique des 2 Infinis de Lyon (IP2I ), Villeurbanne, France\nS. Beauceron , B. Blancon , G. Boudoul , A. Carle, N. Chanon , J. Choi ,\nD. Contardo , P. Depasse , C. Dozen17 , H. El Mamouni, J. Fay , S. Gascon ,\nM. Gouzevitch , G. Grenier , B. Ille , I.B. Laktineh, M. Lethuillier , L. Mirabito, S. Perries,\nM. Vander Donckt , P. Verdier , S. Viret\n\nGeorgian Technical University, Tbilisi, Georgia\nI. Lomidze , T. Toriashvili18 , Z. Tsamalaidze12\n\nRWTH Aachen University, I. Physikalisches Institut, Aachen, Germany\nV. Botta , L. Feld , K. Klein , M. Lipinski , D. Meuser , A. Pauls , N. Röwert ,\nM. Teroerde\n\nRWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany\n\nhttps://orcid.org/0000-0002-0857-8507\nhttps://orcid.org/0000-0002-7322-3374\nhttps://orcid.org/0000-0001-8692-5458\nhttps://orcid.org/0000-0003-1260-973X\nhttps://orcid.org/0000-0001-6645-6244\nhttps://orcid.org/0000-0002-2387-4777\nhttps://orcid.org/0000-0001-6242-7331\nhttps://orcid.org/0000-0002-9380-8919\nhttps://orcid.org/0000-0002-3532-8132\nhttps://orcid.org/0000-0002-5191-5759\nhttps://orcid.org/0000-0001-7040-9491\nhttps://orcid.org/0000-0002-6552-7255\nhttps://orcid.org/0000-0002-3364-916X\nhttps://orcid.org/0000-0002-3244-0591\nhttps://orcid.org/0000-0001-7369-2536\nhttps://orcid.org/0000-0003-4807-0414\nhttps://orcid.org/0000-0002-5200-6477\nhttps://orcid.org/0000-0001-5871-9622\nhttps://orcid.org/0000-0001-6066-8756\nhttps://orcid.org/0000-0002-4023-7964\nhttps://orcid.org/0000-0003-2898-6900\nhttps://orcid.org/0000-0003-0392-8691\nhttps://orcid.org/0000-0002-8398-4249\nhttps://orcid.org/0000-0002-5502-1795\nhttps://orcid.org/0000-0003-1370-5598\nhttps://orcid.org/0009-0002-4847-8882\nhttps://orcid.org/0000-0003-1609-3515\nhttps://orcid.org/0000-0003-0510-3810\nhttps://orcid.org/0000-0002-6764-0016\nhttps://orcid.org/0000-0003-2039-5874\nhttps://orcid.org/0000-0002-7073-7767\nhttps://orcid.org/0000-0003-0386-8633\nhttps://orcid.org/0000-0003-2340-4641\nhttps://orcid.org/0000-0002-1133-5485\nhttps://orcid.org/0000-0002-4359-836X\nhttps://orcid.org/0000-0003-3278-3671\nhttps://orcid.org/0000-0003-2040-4099\nhttps://orcid.org/0009-0008-2784-615X\nhttps://orcid.org/0000-0002-9860-101X\nhttps://orcid.org/0000-0003-3090-9744\nhttps://orcid.org/0000-0002-3932-5967\nhttps://orcid.org/0000-0002-3872-3592\nhttps://orcid.org/0009-0008-7976-851X\nhttps://orcid.org/0000-0002-5388-5565\nhttps://orcid.org/0000-0001-7803-6650\nhttps://orcid.org/0000-0001-6402-4050\nhttps://orcid.org/0000-0002-9481-5168\nhttps://orcid.org/0000-0002-9813-372X\nhttps://orcid.org/0000-0002-1119-6614\nhttps://orcid.org/0000-0002-6033-8885\nhttps://orcid.org/0000-0002-1194-8556\nhttps://orcid.org/0000-0002-8597-647X\nhttps://orcid.org/0000-0001-6027-4511\nhttps://orcid.org/0000-0003-4386-0564\nhttps://orcid.org/0000-0002-4087-8155\nhttps://orcid.org/0000-0001-6793-4359\nhttps://orcid.org/0000-0001-8710-992X\nhttps://orcid.org/0000-0002-6669-1698\nhttps://orcid.org/0000-0002-6762-3937\nhttps://orcid.org/0000-0001-9752-0624\nhttps://orcid.org/0009-0006-5692-5688\nhttps://orcid.org/0000-0002-1275-7292\nhttps://orcid.org/0009-0008-2093-8131\nhttps://orcid.org/0000-0003-0174-4020\nhttps://orcid.org/0000-0001-7002-0937\nhttps://orcid.org/0000-0003-0985-913X\nhttps://orcid.org/0000-0001-7305-7102\nhttps://orcid.org/0000-0002-3836-1173\nhttps://orcid.org/0000-0002-9860-9185\nhttps://orcid.org/0000-0003-3735-2707\nhttps://orcid.org/0000-0002-9892-4601\nhttps://orcid.org/0000-0001-5187-3571\nhttps://orcid.org/0000-0001-5381-4807\nhttps://orcid.org/0000-0001-7098-5317\nhttps://orcid.org/0000-0003-4957-2782\nhttps://orcid.org/0000-0002-7214-0673\nhttps://orcid.org/0000-0002-1178-1450\nhttps://orcid.org/0000-0001-7476-0158\nhttps://orcid.org/0000-0002-8298-7560\nhttps://orcid.org/0009-0004-1837-0496\nhttps://orcid.org/0000-0002-4535-5273\nhttps://orcid.org/0009-0005-7044-8104\nhttps://orcid.org/0000-0003-0249-3622\nhttps://orcid.org/0000-0003-2797-7690\nhttps://orcid.org/0000-0002-5230-8387\nhttps://orcid.org/0000-0001-8955-1666\nhttps://orcid.org/0000-0002-8545-0187\nhttps://orcid.org/0000-0002-2431-3381\nhttps://orcid.org/0000-0002-8036-9267\nhttps://orcid.org/0000-0001-9022-1509\nhttps://orcid.org/0009-0002-9897-8439\nhttps://orcid.org/0000-0002-2939-5646\nhttps://orcid.org/0000-0002-6024-0992\nhttps://orcid.org/0000-0001-6768-7466\nhttps://orcid.org/0000-0001-7556-2743\nhttps://orcid.org/0000-0002-4301-634X\nhttps://orcid.org/0000-0001-5790-1780\nhttps://orcid.org/0000-0002-7204-1624\nhttps://orcid.org/0000-0002-5524-880X\nhttps://orcid.org/0000-0002-1976-5877\nhttps://orcid.org/0000-0002-8679-3878\nhttps://orcid.org/0000-0001-6185-2045\nhttps://orcid.org/0000-0002-9253-8611\nhttps://orcid.org/0000-0003-3090-2948\nhttps://orcid.org/0009-0002-3901-2765\nhttps://orcid.org/0000-0003-1655-6874\nhttps://orcid.org/0000-0001-5377-3558\nhttps://orcid.org/0000-0003-1661-9513\nhttps://orcid.org/0000-0001-9813-8646\nhttps://orcid.org/0000-0002-1546-7880\nhttps://orcid.org/0000-0002-6839-0063\nhttps://orcid.org/0000-0002-2722-7526\nhttps://orcid.org/0000-0002-8117-5376\nhttps://orcid.org/0000-0002-4745-5470\nhttps://orcid.org/0000-0002-5892-1377\n\n\n24\n\nS. Diekmann , A. Dodonova , N. Eich , D. Eliseev , M. Erdmann , P. Fackeldey ,\nB. Fischer , T. Hebbeker , K. Hoepfner , F. Ivone , M.y. Lee , L. Mastrolorenzo,\nM. Merschmeyer , A. Meyer , S. Mondal , S. Mukherjee , D. Noll , A. Novak ,\nF. Nowotny, A. Pozdnyakov , Y. Rath, W. Redjeb , F. Rehm, H. Reithler , A. Schmidt ,\nS.C. Schuler, A. Sharma , A. Stein , F. Torres Da Silva De Araujo19 , L. Vigilante,\nS. Wiedenbeck , S. Zaleski\n\nRWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany\nC. Dziwok , G. Flügge , W. Haj Ahmad20 , O. Hlushchenko, T. Kress , A. Nowack ,\nO. Pooth , A. Stahl , T. Ziemons , A. Zotz\n\nDeutsches Elektronen-Synchrotron, Hamburg, Germany\nH. Aarup Petersen , M. Aldaya Martin , J. Alimena , P. Asmuss, S. Baxter ,\nM. Bayatmakou , H. Becerril Gonzalez , O. Behnke , S. Bhattacharya , F. Blekman21 ,\nK. Borras22 , D. Brunner , A. Campbell , A. Cardini , C. Cheng, F. Colombina, S. Con-\nsuegra Rodrı́guez , G. Correia Silva , M. De Silva , G. Eckerlin, D. Eckstein , L.I. Es-\ntevez Banos , O. Filatov , E. Gallo21 , A. Geiser , A. Giraldi , G. Greau, A. Grohsjean ,\nV. Guglielmi , M. Guthoff , A. Jafari23 , N.Z. Jomhari , B. Kaech , M. Kasemann ,\nH. Kaveh , C. Kleinwort , R. Kogler , M. Komm , D. Krücker , W. Lange,\nD. Leyva Pernia , K. Lipka24 , W. Lohmann25 , R. Mankel , I.-A. Melzer-Pellmann ,\nM. Mendizabal Morentin , J. Metwally, A.B. Meyer , G. Milella , M. Mormile ,\nA. Mussgiller , A. Nürnberg , Y. Otarid, D. Pérez Adán , E. Ranken , A. Raspereza ,\nB. Ribeiro Lopes , J. Rübenach, A. Saggio , M. Savitskyi , M. Scham26,22 , V. Scheurer,\nS. Schnake22 , P. Schütze , C. Schwanenberger21 , M. Shchedrolosiev , R.E. Sosa Ri-\ncardo , D. Stafford, N. Tonon† , F. Vazzoler , A. Ventura Barroso , R. Walsh ,\nQ. Wang , Y. Wen , K. Wichmann, L. Wiens22 , C. Wissing , S. Wuchterl , Y. Yang ,\nA. Zimermmane Castro Santos\n\nUniversity of Hamburg, Hamburg, Germany\nA. Albrecht , S. Albrecht , M. Antonello , S. Bein , L. Benato , M. Bonanomi ,\nP. Connor , K. De Leo , M. Eich, K. El Morabit , A. Fröhlich, C. Garbers ,\nE. Garutti , M. Hajheidari, J. Haller , A. Hinzmann , H.R. Jabusch , G. Kasieczka ,\nP. Keicher, R. Klanner , W. Korcari , T. Kramer , V. Kutzner , F. Labe , J. Lange ,\nA. Lobanov , C. Matthies , A. Mehta , L. Moureaux , M. Mrowietz, A. Nigamova ,\nY. Nissan, A. Paasch , K.J. Pena Rodriguez , T. Quadfasel , M. Rieger , D. Savoiu ,\nJ. Schindler , P. Schleper , M. Schröder , J. Schwandt , M. Sommerhalder , H. Stadie ,\nG. Steinbrück , A. Tews, M. Wolf\n\nKarlsruher Institut fuer Technologie, Karlsruhe, Germany\nS. Brommer , M. Burkart, E. Butz , T. Chwalek , A. Dierlamm , A. Droll, N. Falter-\nmann , M. Giffels , J.O. Gosewisch, A. Gottmann , F. Hartmann27 , M. Horzela ,\nU. Husemann , M. Klute , R. Koppenhöfer , M. Link, A. Lintuluoto , S. Maier ,\nS. Mitra , Th. Müller , M. Neukum, M. Oh , G. Quast , K. Rabbertz , I. Shvetsov ,\nH.J. Simonis , N. Trevisani , R. Ulrich , J. van der Linden , R.F. Von Cube ,\nM. Wassmer , S. Wieland , R. Wolf , S. Wunsch, X. Zuo\n\nInstitute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi,\nGreece\nG. Anagnostou, P. Assiouras , G. Daskalakis , A. Kyriakis, A. Stakia\n\nNational and Kapodistrian University of Athens, Athens, Greece\nM. Diamantopoulou, D. Karasavvas, P. Kontaxakis , A. Manousakis-Katsikakis , A. Pana-\n\nhttps://orcid.org/0009-0004-8867-0881\nhttps://orcid.org/0000-0002-5115-8487\nhttps://orcid.org/0000-0001-9494-4317\nhttps://orcid.org/0000-0001-5844-8156\nhttps://orcid.org/0000-0002-1653-1303\nhttps://orcid.org/0000-0003-4932-7162\nhttps://orcid.org/0000-0002-3900-3482\nhttps://orcid.org/0000-0002-9736-266X\nhttps://orcid.org/0000-0002-2008-8148\nhttps://orcid.org/0000-0002-2388-5548\nhttps://orcid.org/0000-0002-4430-1695\nhttps://orcid.org/0000-0003-2081-7141\nhttps://orcid.org/0000-0001-9598-6623\nhttps://orcid.org/0000-0003-0153-7590\nhttps://orcid.org/0000-0001-6341-9982\nhttps://orcid.org/0000-0002-0176-2360\nhttps://orcid.org/0000-0002-0389-5896\nhttps://orcid.org/0000-0003-3478-9081\nhttps://orcid.org/0000-0001-9794-8292\nhttps://orcid.org/0000-0003-4409-702X\nhttps://orcid.org/0000-0003-2711-8984\nhttps://orcid.org/0000-0002-5295-1460\nhttps://orcid.org/0000-0003-0713-811X\nhttps://orcid.org/0000-0002-4785-3057\nhttps://orcid.org/0000-0002-4692-9304\nhttps://orcid.org/0000-0001-9806-0244\nhttps://orcid.org/0000-0003-3681-9272\nhttps://orcid.org/0000-0003-1491-0446\nhttps://orcid.org/0000-0002-2702-8201\nhttps://orcid.org/0000-0002-3522-5926\nhttps://orcid.org/0000-0001-6445-6160\nhttps://orcid.org/0000-0002-8369-7506\nhttps://orcid.org/0000-0003-1697-2130\nhttps://orcid.org/0000-0002-1320-1712\nhttps://orcid.org/0009-0005-6482-7466\nhttps://orcid.org/0000-0003-1533-0945\nhttps://orcid.org/0000-0001-6030-3191\nhttps://orcid.org/0009-0008-4191-6716\nhttps://orcid.org/0009-0002-9905-0667\nhttps://orcid.org/0000-0001-5387-712X\nhttps://orcid.org/0000-0002-4238-0991\nhttps://orcid.org/0000-0002-3197-0048\nhttps://orcid.org/0000-0002-7366-7098\nhttps://orcid.org/0000-0003-1111-249X\nhttps://orcid.org/0000-0001-9518-0435\nhttps://orcid.org/0000-0003-4439-5748\nhttps://orcid.org/0000-0003-1803-0999\nhttps://orcid.org/0000-0002-1383-1837\nhttps://orcid.org/0000-0001-6232-3591\nhttps://orcid.org/0000-0002-5804-6226\nhttps://orcid.org/0000-0002-7366-6562\nhttps://orcid.org/0000-0001-6195-3102\nhttps://orcid.org/0000-0001-9850-6170\nhttps://orcid.org/0000-0001-7200-5175\nhttps://orcid.org/0000-0003-0355-102X\nhttps://orcid.org/0000-0003-4423-2631\nhttps://orcid.org/0000-0003-0748-8494\nhttps://orcid.org/0000-0003-3240-7393\nhttps://orcid.org/0000-0002-3974-589X\nhttps://orcid.org/0000-0001-7327-1870\nhttps://orcid.org/0000-0001-9127-7408\nhttps://orcid.org/0000-0002-1194-2306\nhttps://orcid.org/0000-0002-0429-2448\nhttps://orcid.org/0000-0002-3273-5859\nhttps://orcid.org/0000-0002-9017-9504\nhttps://orcid.org/0000-0002-5336-4399\nhttps://orcid.org/0000-0002-7669-4294\nhttps://orcid.org/0000-0003-1610-8844\nhttps://orcid.org/0009-0009-8755-3698\nhttps://orcid.org/0000-0002-8427-3748\nhttps://orcid.org/0000-0002-8705-0857\nhttps://orcid.org/0000-0003-2375-1563\nhttps://orcid.org/0000-0001-7707-919X\nhttps://orcid.org/0000-0002-6506-5177\nhttps://orcid.org/0000-0001-8532-2356\nhttps://orcid.org/0000-0002-2047-951X\nhttps://orcid.org/0000-0003-0456-7250\nhttps://orcid.org/0000-0002-8331-8166\nhttps://orcid.org/0000-0002-7876-3134\nhttps://orcid.org/0000-0003-3416-0726\nhttps://orcid.org/0000-0001-7472-5029\nhttps://orcid.org/0000-0003-2167-498X\nhttps://orcid.org/0000-0003-0823-447X\nhttps://orcid.org/0000-0002-7385-3317\nhttps://orcid.org/0000-0002-9952-9267\nhttps://orcid.org/0000-0001-9494-2151\nhttps://orcid.org/0000-0003-3409-6584\nhttps://orcid.org/0000-0003-4802-6990\nhttps://orcid.org/0000-0001-6699-6662\nhttps://orcid.org/0000-0003-3510-2093\nhttps://orcid.org/0000-0002-2240-6699\nhttps://orcid.org/0000-0003-4301-2688\nhttps://orcid.org/0000-0001-8111-9318\nhttps://orcid.org/0000-0003-3233-6636\nhttps://orcid.org/0000-0002-3872-4114\nhttps://orcid.org/0000-0003-1014-8677\nhttps://orcid.org/0000-0002-8724-9604\nhttps://orcid.org/0000-0002-4423-4461\nhttps://orcid.org/0000-0002-5090-8004\nhttps://orcid.org/0000-0001-9955-9258\nhttps://orcid.org/0009-0009-3430-0558\nhttps://orcid.org/0000-0001-9302-3102\nhttps://orcid.org/0000-0001-6004-6180\nhttps://orcid.org/0000-0002-5960-6803\nhttps://orcid.org/0000-0001-9094-482X\nhttps://orcid.org/0000-0001-9387-7407\nhttps://orcid.org/0000-0001-5135-7489\nhttps://orcid.org/0000-0003-3629-6264\nhttps://orcid.org/0000-0003-2500-1061\nhttps://orcid.org/0000-0002-8908-409X\nhttps://orcid.org/0000-0001-5886-220X\nhttps://orcid.org/0000-0001-5094-2256\nhttps://orcid.org/0000-0003-0634-5539\nhttps://orcid.org/0000-0001-9347-7657\nhttps://orcid.org/0000-0002-2633-4696\nhttps://orcid.org/0000-0003-2444-1014\nhttps://orcid.org/0000-0003-3457-2755\nhttps://orcid.org/0000-0002-7004-9227\nhttps://orcid.org/0000-0001-8017-5502\nhttps://orcid.org/0000-0002-7004-0214\nhttps://orcid.org/0000-0003-1985-3807\nhttps://orcid.org/0000-0002-1870-9443\nhttps://orcid.org/0000-0001-7513-6330\nhttps://orcid.org/0000-0002-5376-0877\nhttps://orcid.org/0000-0001-7379-4540\nhttps://orcid.org/0000-0002-0433-4484\nhttps://orcid.org/0000-0002-2310-9266\nhttps://orcid.org/0000-0002-8522-8500\nhttps://orcid.org/0000-0002-2208-5178\nhttps://orcid.org/0000-0002-2877-9744\nhttps://orcid.org/0000-0003-2360-351X\nhttps://orcid.org/0000-0003-0797-2606\nhttps://orcid.org/0000-0001-6794-7475\nhttps://orcid.org/0009-0006-6551-0660\nhttps://orcid.org/0000-0001-5628-6827\nhttps://orcid.org/0000-0001-8058-9828\nhttps://orcid.org/0000-0002-0052-597X\nhttps://orcid.org/0000-0001-5746-7371\nhttps://orcid.org/0000-0002-0513-8119\nhttps://orcid.org/0000-0002-8355-2761\nhttps://orcid.org/0000-0003-3002-2430\nhttps://orcid.org/0000-0001-8988-2035\nhttps://orcid.org/0000-0002-2403-5801\nhttps://orcid.org/0000-0002-8009-3723\nhttps://orcid.org/0000-0001-7804-9902\nhttps://orcid.org/0000-0001-6506-3107\nhttps://orcid.org/0000-0003-0193-3032\nhttps://orcid.org/0000-0001-6696-349X\nhttps://orcid.org/0000-0001-8989-8387\nhttps://orcid.org/0000-0002-3190-7962\nhttps://orcid.org/0000-0002-6198-8388\nhttps://orcid.org/0000-0002-0869-5631\nhttps://orcid.org/0000-0002-6256-5715\nhttps://orcid.org/0000-0002-0726-1452\nhttps://orcid.org/0000-0001-9828-9778\nhttps://orcid.org/0000-0002-3060-2278\nhttps://orcid.org/0000-0003-4337-0098\nhttps://orcid.org/0000-0003-2618-9203\nhttps://orcid.org/0000-0002-4021-4260\nhttps://orcid.org/0000-0001-7040-9846\nhttps://orcid.org/0000-0002-7069-9019\nhttps://orcid.org/0000-0002-7467-2980\nhttps://orcid.org/0000-0002-5223-9342\nhttps://orcid.org/0000-0002-2535-402X\nhttps://orcid.org/0000-0002-7174-781X\nhttps://orcid.org/0000-0002-6237-5209\nhttps://orcid.org/0000-0002-0408-2811\nhttps://orcid.org/0000-0003-3887-5358\nhttps://orcid.org/0000-0001-9456-383X\nhttps://orcid.org/0000-0002-0029-493X\nhttps://orcid.org/0000-0002-5152-9006\nhttps://orcid.org/0000-0001-6070-7698\nhttps://orcid.org/0000-0001-6277-7171\nhttps://orcid.org/0000-0002-4860-5979\nhttps://orcid.org/0000-0002-0530-1182\n\n\n25\n\ngiotou, I. Papavergou , N. Saoulidou , K. Theofilatos , E. Tziaferi , K. Vellidis ,\nI. Zisopoulos\n\nNational Technical University of Athens, Athens, Greece\nG. Bakas , T. Chatzistavrou, G. Karapostoli , K. Kousouris , I. Papakrivopoulos ,\nG. Tsipolitis, A. Zacharopoulou\n\nUniversity of Ioánnina, Ioánnina, Greece\nK. Adamidis, I. Bestintzanos, I. Evangelou , C. Foudas, P. Gianneios , C. Kamtsikis,\nP. Katsoulis, P. Kokkas , P.G. Kosmoglou Kioseoglou , N. Manthos , I. Papadopoulos ,\nJ. Strologas\n\nMTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University,\nBudapest, Hungary\nM. Csanád , K. Farkas , M.M.A. Gadallah28 , P. Major , K. Mandal , G. Pásztor ,\nA.J. Rádl29 , O. Surányi , G.I. Veres\n\nWigner Research Centre for Physics, Budapest, Hungary\nM. Bartók30 , C. Hajdu , D. Horvath31,32 , F. Sikler , V. Veszpremi\n\nInstitute of Nuclear Research ATOMKI, Debrecen, Hungary\nG. Bencze, N. Beni , S. Czellar, J. Karancsi30 , J. Molnar, Z. Szillasi, D. Teyssier\n\nInstitute of Physics, University of Debrecen, Debrecen, Hungary\nP. Raics, B. Ujvari33 , G. Zilizi\n\nKaroly Robert Campus, MATE Institute of Technology, Gyongyos, Hungary\nT. Csorgo29 , F. Nemes29 , T. Novak\n\nPanjab University, Chandigarh, India\nJ. Babbar , S. Bansal , S.B. Beri, V. Bhatnagar , G. Chaudhary , S. Chauhan ,\nN. Dhingra34 , R. Gupta, A. Kaur , A. Kaur , H. Kaur , M. Kaur , S. Kumar ,\nP. Kumari , M. Meena , K. Sandeep , T. Sheokand, J.B. Singh35 , A. Singla\n\nUniversity of Delhi, Delhi, India\nA. Ahmed , A. Bhardwaj , A. Chhetri , B.C. Choudhary , A. Kumar , M. Naimud-\ndin , K. Ranjan , S. Saumya\n\nSaha Institute of Nuclear Physics, HBNI, Kolkata, India\nS. Baradia , S. Barman36 , S. Bhattacharya , D. Bhowmik, S. Dutta , S. Dutta,\nB. Gomber37 , M. Maity36, P. Palit , G. Saha , B. Sahu37 , S. Sarkar\n\nIndian Institute of Technology Madras, Madras, India\nP.K. Behera , S.C. Behera , S. Chatterjee , P. Kalbhor , J.R. Komaragiri38 ,\nD. Kumar38 , A. Muhammad , L. Panwar38 , R. Pradhan , P.R. Pujahari , N.R. Saha ,\nA. Sharma , A.K. Sikdar , S. Verma\n\nBhabha Atomic Research Centre, Mumbai, India\nK. Naskar39\n\nTata Institute of Fundamental Research-A, Mumbai, India\nT. Aziz, I. Das , S. Dugad, M. Kumar , G.B. Mohanty , P. Suryadevara\n\nTata Institute of Fundamental Research-B, Mumbai, India\nS. Banerjee , M. Guchait , S. Karmakar , S. Kumar , G. Majumder , K. Mazumdar ,\nS. Mukherjee , A. Thachayath\n\nhttps://orcid.org/0000-0002-7992-2686\nhttps://orcid.org/0000-0001-6958-4196\nhttps://orcid.org/0000-0001-8448-883X\nhttps://orcid.org/0000-0003-4958-0408\nhttps://orcid.org/0000-0001-5680-8357\nhttps://orcid.org/0000-0001-5212-4353\nhttps://orcid.org/0000-0003-0287-1937\nhttps://orcid.org/0000-0002-4280-2541\nhttps://orcid.org/0000-0002-6360-0869\nhttps://orcid.org/0000-0002-8440-0487\nhttps://orcid.org/0000-0002-5903-5481\nhttps://orcid.org/0009-0003-7233-0738\nhttps://orcid.org/0009-0009-3752-6253\nhttps://orcid.org/0000-0002-7440-4396\nhttps://orcid.org/0000-0003-3247-8909\nhttps://orcid.org/0000-0002-9937-3063\nhttps://orcid.org/0000-0002-2225-7160\nhttps://orcid.org/0000-0002-3154-6925\nhttps://orcid.org/0000-0003-1740-6974\nhttps://orcid.org/0000-0002-8305-6661\nhttps://orcid.org/0000-0002-5476-0414\nhttps://orcid.org/0000-0002-3966-7182\nhttps://orcid.org/0000-0003-0707-9762\nhttps://orcid.org/0000-0001-8810-0388\nhttps://orcid.org/0000-0002-4684-495X\nhttps://orcid.org/0000-0002-5440-4356\nhttps://orcid.org/0000-0002-4440-2701\nhttps://orcid.org/0000-0002-7193-800X\nhttps://orcid.org/0000-0003-0091-477X\nhttps://orcid.org/0000-0001-9608-3901\nhttps://orcid.org/0000-0001-9783-0315\nhttps://orcid.org/0000-0002-3185-7889\nhttps://orcid.org/0000-0003-0802-7665\nhttps://orcid.org/0000-0002-5259-7983\nhttps://orcid.org/0000-0003-0498-4265\nhttps://orcid.org/0000-0002-0480-0000\nhttps://orcid.org/0000-0002-9110-9663\nhttps://orcid.org/0000-0002-1451-6484\nhttps://orcid.org/0000-0001-6253-4356\nhttps://orcid.org/0000-0002-4080-4156\nhttps://orcid.org/0000-0003-1992-0336\nhttps://orcid.org/0000-0002-8392-9610\nhttps://orcid.org/0000-0003-0168-3336\nhttps://orcid.org/0000-0001-6974-4129\nhttps://orcid.org/0000-0002-7200-6204\nhttps://orcid.org/0000-0002-1640-9180\nhttps://orcid.org/0000-0003-3609-4777\nhttps://orcid.org/0000-0002-8659-7092\nhttps://orcid.org/0000-0002-3440-2767\nhttps://orcid.org/0000-0001-9212-9108\nhttps://orcid.org/0000-0002-6623-8586\nhttps://orcid.org/0000-0003-4536-3967\nhttps://orcid.org/0000-0002-3220-3668\nhttps://orcid.org/0000-0001-9029-2462\nhttps://orcid.org/0000-0003-2550-139X\nhttps://orcid.org/0000-0002-4500-8853\nhttps://orcid.org/0000-0002-7544-3258\nhttps://orcid.org/0000-0001-7495-1923\nhttps://orcid.org/0000-0001-5029-1887\nhttps://orcid.org/0000-0003-3407-4094\nhttps://orcid.org/0000-0003-4542-386X\nhttps://orcid.org/0000-0002-5540-3750\nhttps://orcid.org/0000-0001-7842-9518\nhttps://orcid.org/0000-0001-9860-7262\nhttps://orcid.org/0000-0001-8891-1674\nhttps://orcid.org/0000-0002-8110-4957\nhttps://orcid.org/0000-0001-9650-8121\nhttps://orcid.org/0000-0002-4446-0258\nhttps://orcid.org/0000-0002-1948-029X\nhttps://orcid.org/0000-0002-6125-1941\nhttps://orcid.org/0000-0002-8073-5140\nhttps://orcid.org/0000-0002-1527-2266\nhttps://orcid.org/0000-0002-0798-2727\nhttps://orcid.org/0000-0003-0185-9872\nhttps://orcid.org/0000-0002-5892-3743\nhttps://orcid.org/0000-0002-9344-6655\nhttps://orcid.org/0000-0002-6636-5331\nhttps://orcid.org/0000-0002-7535-7149\nhttps://orcid.org/0000-0003-2461-4907\nhttps://orcid.org/0000-0001-7000-6510\nhttps://orcid.org/0000-0002-0994-7212\nhttps://orcid.org/0000-0002-7954-7898\nhttps://orcid.org/0000-0002-0688-923X\nhttps://orcid.org/0000-0002-5437-5217\nhttps://orcid.org/0000-0003-1163-6955\nhttps://orcid.org/0000-0003-0638-4378\nhttps://orcid.org/0000-0002-5437-2067\nhttps://orcid.org/0000-0003-0312-057X\nhttps://orcid.org/0000-0001-6850-7666\nhttps://orcid.org/0000-0002-7953-4683\nhttps://orcid.org/0009-0004-0928-7922\nhttps://orcid.org/0000-0001-9715-5663\nhttps://orcid.org/0000-0002-2405-915X\nhttps://orcid.org/0000-0002-3815-5222\nhttps://orcid.org/0000-0003-3136-1653\nhttps://orcid.org/0000-0003-3122-0594\nhttps://orcid.org/0000-0001-6545-0350\n\n\n26\n\nNational Institute of Science Education and Research, An OCC of Homi Bhabha National\nInstitute, Bhubaneswar, Odisha, India\nS. Bahinipati40 , A.K. Das, C. Kar , P. Mal , T. Mishra , V.K. Muraleedha-\nran Nair Bindhu41 , A. Nayak41 , P. Saha , S.K. Swain, S. Varghese , D. Vats41\n\nIndian Institute of Science Education and Research (IISER), Pune, India\nA. Alpana , S. Dube , B. Kansal , A. Laha , S. Pandey , A. Rastogi , S. Sharma\n\nIsfahan University of Technology, Isfahan, Iran\nH. Bakhshiansohi42,43 , E. Khazaie43 , M. Zeinali44\n\nInstitute for Research in Fundamental Sciences (IPM), Tehran, Iran\nS. Chenarani45 , S.M. Etesami , M. Khakzad , M. Mohammadi Najafabadi\n\nUniversity College Dublin, Dublin, Ireland\nM. Grunewald\n\nINFN Sezione di Baria, Università di Barib, Politecnico di Baric, Bari, Italy\nM. Abbresciaa,b , R. Alya,b ,46 , C. Arutaa,b , A. Colaleoa , D. Creanzaa,c ,\nL. Cristellaa,b , B. D‘ Anzia,b , N. De Filippisa,c , M. De Palmaa,b , A. Di Florioa,b ,\nW. Elmetenaweea,b , F. Erricoa,b , L. Fiorea , G. Iasellia ,c , G. Maggia ,c , M. Maggia ,\nI. Margjekaa,b , V. Mastrapasquaa,b , S. Mya,b , S. Nuzzoa ,b , A. Pellecchiaa,b ,\nA. Pompilia,b , G. Pugliesea,c , R. Radognaa , D. Ramosa , A. Ranieria ,\nG. Selvaggia,b , L. Silvestrisa , F.M. Simonea,b , Ü. Sözbilira , A. Stamerraa ,\nR. Vendittia , P. Verwilligena\n\nINFN Sezione di Bolognaa, Università di Bolognab, Bologna, Italy\nG. Abbiendia , C. Battilanaa,b , D. Bonacorsia,b , L. Borgonovia , L. Brigliadoria,\nR. Campaninia ,b , P. Capiluppia,b , A. Castroa,b , F.R. Cavalloa , M. Cuffiania,b ,\nG.M. Dallavallea , T. Diotalevia,b , F. Fabbria , A. Fanfania,b , D. Fasanellaa,b ,\nP. Giacomellia , L. Giommia,b , C. Grandia , L. Guiduccia,b , S. Lo Meoa,47 ,\nL. Lunertia,b , S. Marcellinia , G. Masettia , F.L. Navarriaa,b , A. Perrottaa ,\nF. Primaveraa,b , A.M. Rossia,b , T. Rovellia,b , G.P. Sirolia,b\n\nINFN Sezione di Cataniaa, Università di Cataniab, Catania, Italy\nS. Costaa,b ,48 , A. Di Mattiaa , R. Potenzaa,b, A. Tricomia,b ,48 , C. Tuvea,b\n\nINFN Sezione di Firenzea, Università di Firenzeb, Firenze, Italy\nG. Barbaglia , G. Bardellia,b , B. Camaiania,b , A. Cassesea , R. Ceccarellia,b ,\nV. Ciullia,b , C. Civininia , R. D’Alessandroa ,b , E. Focardia,b , G. Latinoa,b ,\nP. Lenzia,b , M. Lizzoa,b , M. Meschinia , S. Paolettia , G. Sguazzonia , L. Viliania\n\nINFN Laboratori Nazionali di Frascati, Frascati, Italy\nL. Benussi , S. Bianco , S. Meola49 , D. Piccolo\n\nINFN Sezione di Genovaa, Università di Genovab, Genova, Italy\nM. Bozzoa,b , P. Chatagnona , F. Ferroa , E. Robuttia , S. Tosia,b\n\nINFN Sezione di Milano-Bicoccaa, Università di Milano-Bicoccab, Milano, Italy\nA. Benagliaa , G. Boldrinia , F. Brivioa,b , F. Cetorellia,b , F. De Guioa,b ,\nM.E. Dinardoa,b , P. Dinia , S. Gennaia , A. Ghezzia,b , P. Govonia,b , L. Guzzia,b ,\nM.T. Lucchinia,b , M. Malbertia , S. Malvezzia , A. Massironia , D. Menascea ,\nL. Moronia , M. Paganonia,b , D. Pedrinia , B.S. Pinolinia, S. Ragazzia,b , N. Redaellia ,\nT. Tabarelli de Fatisa,b , D. Zuoloa,b\n\nhttps://orcid.org/0000-0002-3744-5332\nhttps://orcid.org/0000-0002-6407-6974\nhttps://orcid.org/0000-0002-0870-8420\nhttps://orcid.org/0000-0002-2121-3932\nhttps://orcid.org/0000-0003-4671-815X\nhttps://orcid.org/0000-0002-7716-4981\nhttps://orcid.org/0000-0002-7013-8094\nhttps://orcid.org/0009-0000-1318-8266\nhttps://orcid.org/0009-0007-8224-4664\nhttps://orcid.org/0000-0003-3294-2345\nhttps://orcid.org/0000-0002-5145-3777\nhttps://orcid.org/0000-0002-6604-1011\nhttps://orcid.org/0000-0001-9440-7028\nhttps://orcid.org/0000-0003-0440-6019\nhttps://orcid.org/0000-0003-1245-6710\nhttps://orcid.org/0000-0001-6886-0726\nhttps://orcid.org/0000-0001-5741-3357\nhttps://orcid.org/0000-0001-9810-7743\nhttps://orcid.org/0000-0001-8367-6257\nhttps://orcid.org/0000-0002-1425-076X\nhttps://orcid.org/0000-0001-6501-4137\nhttps://orcid.org/0000-0002-2212-5715\nhttps://orcid.org/0000-0001-6131-5987\nhttps://orcid.org/0000-0002-5754-0388\nhttps://orcid.org/0000-0001-8727-7544\nhttps://orcid.org/0000-0001-6808-1335\nhttps://orcid.org/0000-0001-9524-3264\nhttps://orcid.org/0000-0002-0711-6319\nhttps://orcid.org/0000-0001-6153-3044\nhttps://orcid.org/0000-0002-4279-1221\nhttps://orcid.org/0000-0002-9361-3142\nhttps://orcid.org/0000-0002-0625-6811\nhttps://orcid.org/0000-0001-8240-1913\nhttps://orcid.org/0000-0003-3719-8041\nhttps://orcid.org/0000-0001-7069-0252\nhttps://orcid.org/0000-0001-8199-370X\nhttps://orcid.org/0000-0002-9470-1320\nhttps://orcid.org/0000-0003-2546-5341\nhttps://orcid.org/0000-0001-5391-7689\nhttps://orcid.org/0000-0002-8431-3922\nhttps://orcid.org/0000-0002-3198-3025\nhttps://orcid.org/0000-0002-9082-5924\nhttps://orcid.org/0000-0002-9938-2680\nhttps://orcid.org/0000-0003-1089-6317\nhttps://orcid.org/0000-0003-3279-6114\nhttps://orcid.org/0000-0003-1291-4005\nhttps://orcid.org/0000-0001-5460-2638\nhttps://orcid.org/0000-0002-1094-5038\nhttps://orcid.org/0000-0002-7165-1017\nhttps://orcid.org/0000-0001-7912-4062\nhttps://orcid.org/0000-0003-0093-6741\nhttps://orcid.org/0000-0002-8985-4891\nhttps://orcid.org/0000-0002-1924-983X\nhttps://orcid.org/0000-0001-6833-3758\nhttps://orcid.org/0000-0003-1434-1968\nhttps://orcid.org/0000-0001-6925-8649\nhttps://orcid.org/0000-0002-9285-8631\nhttps://orcid.org/0000-0003-4499-7562\nhttps://orcid.org/0000-0002-3753-3068\nhttps://orcid.org/0000-0002-0835-9574\nhttps://orcid.org/0000-0001-8679-4443\nhttps://orcid.org/0000-0002-2744-0597\nhttps://orcid.org/0000-0003-4485-1897\nhttps://orcid.org/0000-0003-2527-0456\nhttps://orcid.org/0000-0002-0326-7515\nhttps://orcid.org/0000-0003-2510-5039\nhttps://orcid.org/0000-0002-8614-0420\nhttps://orcid.org/0000-0003-0780-8785\nhttps://orcid.org/0000-0002-8446-9660\nhttps://orcid.org/0000-0003-2256-4117\nhttps://orcid.org/0000-0002-2926-2691\nhttps://orcid.org/0000-0002-6368-7220\nhttps://orcid.org/0000-0003-3539-4313\nhttps://orcid.org/0000-0001-5998-3070\nhttps://orcid.org/0000-0002-6013-8293\nhttps://orcid.org/0000-0003-3249-9208\nhttps://orcid.org/0000-0002-8932-0283\nhttps://orcid.org/0000-0002-1233-8100\nhttps://orcid.org/0000-0002-6377-800X\nhttps://orcid.org/0000-0001-7961-4889\nhttps://orcid.org/0000-0002-7996-7139\nhttps://orcid.org/0000-0001-6253-8656\nhttps://orcid.org/0000-0002-5973-1305\nhttps://orcid.org/0000-0002-9746-4842\nhttps://orcid.org/0000-0002-3528-4125\nhttps://orcid.org/0000-0001-9919-0569\nhttps://orcid.org/0000-0002-9964-015X\nhttps://orcid.org/0000-0002-5071-5501\nhttps://orcid.org/0000-0003-0739-3153\nhttps://orcid.org/0000-0002-1738-8676\nhttps://orcid.org/0000-0002-4662-3305\nhttps://orcid.org/0000-0002-6396-622X\nhttps://orcid.org/0000-0003-3010-4516\nhttps://orcid.org/0000-0003-3232-9380\nhttps://orcid.org/0000-0003-1947-3396\nhttps://orcid.org/0000-0002-4952-3799\nhttps://orcid.org/0000-0001-7997-0306\nhttps://orcid.org/0000-0002-3763-5267\nhttps://orcid.org/0000-0002-4098-3502\nhttps://orcid.org/0000-0002-6927-8807\nhttps://orcid.org/0000-0001-7297-2624\nhttps://orcid.org/0000-0002-9161-3990\nhttps://orcid.org/0000-0003-3592-9509\nhttps://orcid.org/0000-0002-0791-3350\nhttps://orcid.org/0000-0002-1909-6343\nhttps://orcid.org/0000-0002-2363-8889\nhttps://orcid.org/0000-0002-8300-4124\nhttps://orcid.org/0000-0002-8233-7277\nhttps://orcid.org/0000-0001-5404-543X\nhttps://orcid.org/0000-0002-1715-0457\nhttps://orcid.org/0000-0002-4705-9582\nhttps://orcid.org/0000-0002-7663-0805\nhttps://orcid.org/0000-0001-9038-4500\nhttps://orcid.org/0000-0002-7275-9193\nhttps://orcid.org/0000-0003-1124-8450\nhttps://orcid.org/0000-0001-5490-605X\nhttps://orcid.org/0000-0001-9523-6451\nhttps://orcid.org/0000-0002-3061-1553\nhttps://orcid.org/0000-0001-5927-8865\nhttps://orcid.org/0000-0002-8575-7250\nhttps://orcid.org/0000-0001-7375-4899\nhttps://orcid.org/0000-0001-5269-8517\nhttps://orcid.org/0000-0002-8184-7953\nhttps://orcid.org/0000-0002-0227-1301\nhttps://orcid.org/0000-0002-3086-8260\nhttps://orcid.org/0000-0002-7497-7450\nhttps://orcid.org/0000-0001-6794-8419\nhttps://orcid.org/0000-0002-0218-49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Sezione di Napolia, Università di Napoli ’Federico II’b, Napoli, Italy; Università della\nBasilicatac, Potenza, Italy; Università G. Marconid, Roma, Italy\nS. Buontempoa , A. Cagnottaa,b , F. Carnevalia,b, N. Cavalloa,c , A. De Iorioa,b ,\nF. Fabozzia,c , A.O.M. Iorioa,b , L. Listaa,b,50 , P. Paoluccia,27 , B. Rossia ,\nC. Sciaccaa,b\n\nINFN Sezione di Padovaa, Università di Padovab, Padova, Italy; Università di Trentoc,\nTrento, Italy\nP. Azzia , N. Bacchettaa,51 , D. Biselloa ,b , P. Bortignona , A. Bragagnoloa,b ,\nR. Carlina,b , P. Checchiaa , T. Dorigoa , U. Gasparinia,b , G. Grossoa, L. Layera,52,\nE. Lusiania , M. Margonia,b , A.T. Meneguzzoa,b , J. Pazzinia,b , P. Ronchesea,b ,\nR. Rossina ,b , M. Sgaravattoa , F. Simonettoa,b , G. Stronga , M. Tosia,b , H. Yarara,b,\nM. Zanettia,b , P. Zottoa,b , A. Zucchettaa,b , G. Zumerlea,b\n\nINFN Sezione di Paviaa, Università di Paviab, Pavia, Italy\nS. Abu Zeida,53 , C. Aimèa,b , A. Braghieria , S. Calzaferria ,b , D. Fiorinaa,b ,\nP. Montagnaa ,b , V. Rea , C. Riccardia,b , P. Salvinia , I. Vaia,b , P. Vituloa,b\n\nINFN Sezione di Perugiaa, Università di Perugiab, Perugia, Italy\nP. Asenova,54 , G.M. Bileia , D. Ciangottinia,b , L. Fanòa,b , M. Magherinia,b ,\nG. Mantovania,b, V. Mariania,b , M. Menichellia , F. Moscatellia,54 , A. Piccinellia,b ,\nM. Presillaa,b , A. Rossia,b , A. Santocchiaa ,b , D. Spigaa , T. Tedeschia,b\n\nINFN Sezione di Pisaa, Università di Pisab, Scuola Normale Superiore di Pisac, Pisa, Italy;\nUniversità di Sienad, Siena, Italy\nP. Azzurria , G. Bagliesia , V. Bertacchia,c , R. Bhattacharyaa , L. Bianchinia,b ,\nT. Boccalia , E. Bossinia,b , D. Bruschinia ,c , R. Castaldia , M.A. Cioccia,b ,\nV. D’Amantea,d , R. Dell’Orsoa , S. Donatoa , A. Giassia , F. Ligabuea,c ,\nD. Matos Figueiredoa , A. Messineoa,b , M. Musicha,b , F. Pallaa , S. Paroliaa ,\nG. Ramirez-Sancheza,c , A. Rizzia,b , G. Rolandia,c , S. Roy Chowdhurya , T. Sarkara ,\nA. Scribanoa , P. Spagnoloa , R. Tenchinia , G. Tonellia,b , N. Turinia,d , A. Venturia ,\nP.G. Verdinia\n\nINFN Sezione di Romaa, Sapienza Università di Romab, Roma, Italy\nP. Barriaa , M. Campanaa,b , F. Cavallaria , D. Del Rea ,b , E. Di Marcoa ,\nM. Diemoza , E. Longoa,b , P. Meridiania , G. Organtinia,b , F. Pandolfia ,\nR. Paramattia,b , C. Quarantaa,b , S. Rahatloua,b , C. Rovellia , F. Santanastasioa,b ,\nL. Soffia , R. Tramontanoa,b\n\nINFN Sezione di Torinoa, Università di Torinob, Torino, Italy; Università del Piemonte\nOrientalec, Novara, Italy\nN. Amapanea ,b , R. Arcidiaconoa,c , S. Argiroa,b , M. Arneodoa,c , N. Bartosika ,\nR. Bellana,b , A. Belloraa,b , C. Biinoa , N. Cartigliaa , M. Costaa,b , R. Covarellia,b ,\nN. Demariaa , L. Fincoa , M. Grippoa,b , B. Kiania,b , F. Leggera , F. Luongoa,b ,\nC. Mariottia , S. Masellia , A. Meccaa,b , E. Migliorea,b , M. Montenoa ,\nR. Mulargiaa , M.M. Obertinoa,b , G. Ortonaa , L. Pachera,b , N. Pastronea ,\nM. Pelliccionia , M. Ruspaa,c , K. Shchelinaa , F. Sivieroa,b , V. Solaa,b , A. Solanoa,b ,\nD. Soldia,b , A. Staianoa , C. Tarriconea,b , M. Tornagoa,b , D. Trocinoa ,\nG. Umoreta,b , A. Vagnerinia,b , E. Vlasova,b\n\nINFN Sezione di Triestea, Università di Triesteb, Trieste, Italy\nS. Belfortea , V. Candelisea,b , M. Casarsaa , F. Cossuttia , G. Della Riccaa,b ,\nG. Sorrentinoa,b\n\nhttps://orcid.org/0000-0001-9526-556X\nhttps://orcid.org/0000-0002-8801-9894\nhttps://orcid.org/0000-0003-1327-9058\nhttps://orcid.org/0000-0002-9258-1345\nhttps://orcid.org/0000-0001-9821-4151\nhttps://orcid.org/0000-0002-3798-1135\nhttps://orcid.org/0000-0001-6471-5492\nhttps://orcid.org/0000-0002-8773-4781\nhttps://orcid.org/0000-0002-0807-8772\nhttps://orcid.org/0000-0002-8412-4072\nhttps://orcid.org/0000-0002-3129-828X\nhttps://orcid.org/0000-0002-2205-5737\nhttps://orcid.org/0000-0002-2359-8477\nhttps://orcid.org/0000-0002-5360-1454\nhttps://orcid.org/0000-0003-3474-2099\nhttps://orcid.org/0000-0001-7915-1650\nhttps://orcid.org/0000-0002-8312-1531\nhttps://orcid.org/0000-0002-1659-8727\nhttps://orcid.org/0000-0002-7253-2669\nhttps://orcid.org/0000-0001-8791-7978\nhttps://orcid.org/0000-0003-1797-4330\nhttps://orcid.org/0000-0002-5861-8140\nhttps://orcid.org/0000-0002-1118-6205\nhttps://orcid.org/0000-0001-7002-2051\nhttps://orcid.org/0000-0003-3466-7500\nhttps://orcid.org/0000-0001-8091-8345\nhttps://orcid.org/0000-0002-8279-2464\nhttps://orcid.org/0000-0002-4640-6108\nhttps://orcid.org/0000-0003-4050-1769\nhttps://orcid.org/0000-0003-4281-4582\nhttps://orcid.org/0000-0003-3953-5996\nhttps://orcid.org/0000-0003-0380-1172\nhttps://orcid.org/0000-0003-3075-2679\nhttps://orcid.org/0000-0002-0820-0483\nhttps://orcid.org/0000-0003-0449-4717\nhttps://orcid.org/0000-0002-9606-5604\nhttps://orcid.org/0000-0002-1162-2505\nhttps://orcid.org/0000-0002-7104-257X\nhttps://orcid.org/0000-0001-9647-9420\nhttps://orcid.org/0000-0003-0697-3420\nhttps://orcid.org/0000-0003-0165-3962\nhttps://orcid.org/0000-0001-9207-7256\nhttps://orcid.org/0000-0003-0037-5032\nhttps://orcid.org/0000-0001-9247-7778\nhttps://orcid.org/0000-0003-2379-9903\nhttps://orcid.org/0000-0002-4159-9123\nhttps://orcid.org/0000-0002-0843-4108\nhttps://orcid.org/0000-0002-9007-629X\nhttps://orcid.org/0000-0003-4108-3925\nhttps://orcid.org/0000-0001-7108-8116\nhttps://orcid.org/0000-0002-9004-735X\nhttps://orcid.org/0000-0002-7676-3106\nhttps://orcid.org/0000-0003-0386-0527\nhttps://orcid.org/0000-0003-2808-7315\nhttps://orcid.org/0000-0002-2031-2955\nhttps://orcid.org/0000-0002-9770-2249\nhttps://orcid.org/0000-0002-2991-6384\nhttps://orcid.org/0000-0002-7125-2905\nhttps://orcid.org/0000-0002-1717-5654\nhttps://orcid.org/0000-0003-4298-1620\nhttps://orcid.org/0000-0001-9971-1176\nhttps://orcid.org/0000-0002-7575-8639\nhttps://orcid.org/0000-0002-6598-6865\nhttps://orcid.org/0000-0002-9930-9299\nhttps://orcid.org/0000-0002-2303-2588\nhttps://orcid.org/0000-0001-7248-2967\nhttps://orcid.org/0000-0003-0146-845X\nhttps://orcid.org/0000-0003-0002-5462\nhttps://orcid.org/0000-0002-7342-2592\nhttps://orcid.org/0000-0003-1414-9343\nhttps://orcid.org/0000-0001-7646-4977\nhttps://orcid.org/0000-0001-9428-2296\nhttps://orcid.org/0000-0002-1549-7107\nhttps://orcid.org/0000-0003-2514-6930\nhttps://orcid.org/0000-0001-7551-5613\nhttps://orcid.org/0000-0001-7938-5684\nhttps://orcid.org/0000-0002-6361-438X\nhttps://orcid.org/0000-0002-9566-2490\nhttps://orcid.org/0000-0001-7804-5514\nhttps://orcid.org/0000-0002-4543-2718\nhttps://orcid.org/0000-0002-0635-274X\nhttps://orcid.org/0000-0001-5742-5593\nhttps://orcid.org/0000-0003-0582-4167\nhttps://orcid.org/0000-0002-4338-6332\nhttps://orcid.org/0000-0001-7962-5203\nhttps://orcid.org/0000-0003-2574-4383\nhttps://orcid.org/0000-0003-2606-9156\nhttps://orcid.org/0000-0002-9395-5230\nhttps://orcid.org/0000-0002-0249-4142\nhttps://orcid.org/0000-0002-0042-9507\nhttps://orcid.org/0000-0002-3924-7380\nhttps://orcid.org/0000-0001-5425-723X\nhttps://orcid.org/0000-0002-1061-3877\nhttps://orcid.org/0000-0003-0870-5796\nhttps://orcid.org/0000-0002-5920-2438\nhttps://orcid.org/0000-0002-3810-8530\nhttps://orcid.org/0000-0001-6238-6787\nhttps://orcid.org/0000-0002-8480-2259\nhttps://orcid.org/0000-0002-3229-0781\nhttps://orcid.org/0000-0001-8713-3874\nhttps://orcid.org/0000-0002-0080-9550\nhttps://orcid.org/0000-0002-0042-6891\nhttps://orcid.org/0000-0001-9794-3360\nhttps://orcid.org/0000-0003-2173-7530\nhttps://orcid.org/0000-0003-2505-8359\nhttps://orcid.org/0000-0003-2532-9876\nhttps://orcid.org/0000-0001-5979-5299\nhttps://orcid.org/0000-0001-9449-2509\nhttps://orcid.org/0000-0001-5904-142X\nhttps://orcid.org/0000-0003-2150-3750\nhttps://orcid.org/0000-0002-7790-7132\nhttps://orcid.org/0000-0002-7196-2237\nhttps://orcid.org/0000-0002-2539-2376\nhttps://orcid.org/0000-0002-2753-5473\nhttps://orcid.org/0000-0002-1397-7246\nhttps://orcid.org/0000-0002-0548-9189\nhttps://orcid.org/0000-0003-0156-0790\nhttps://orcid.org/0000-0003-1216-5235\nhttps://orcid.org/0000-0003-0743-9465\nhttps://orcid.org/0000-0002-2630-5465\nhttps://orcid.org/0000-0003-0770-269X\nhttps://orcid.org/0000-0002-1202-7652\nhttps://orcid.org/0000-0003-1400-0709\nhttps://orcid.org/0000-0003-2743-4119\nhttps://orcid.org/0000-0002-6864-3294\nhttps://orcid.org/0000-0001-9871-7859\nhttps://orcid.org/0000-0003-2209-2527\nhttps://orcid.org/0000-0002-2271-5192\nhttps://orcid.org/0000-0002-3521-6333\nhttps://orcid.org/0000-0003-2437-013X\nhttps://orcid.org/0000-0002-8781-8192\nhttps://orcid.org/0000-0001-8411-2971\nhttps://orcid.org/0000-0003-1288-4838\nhttps://orcid.org/0000-0001-7291-1979\nhttps://orcid.org/0000-0003-4728-6678\nhttps://orcid.org/0000-0002-7655-3475\nhttps://orcid.org/0000-0003-3742-0693\nhttps://orcid.org/0000-0002-4427-4076\nhttps://orcid.org/0000-0001-6288-951X\nhttps://orcid.org/0000-0002-2971-8214\nhttps://orcid.org/0000-0001-9059-4831\nhttps://orcid.org/0000-0003-1803-624X\nhttps://orcid.org/0000-0001-6233-0513\nhttps://orcid.org/0000-0001-6768-1056\nhttps://orcid.org/0000-0002-2830-5872\nhttps://orcid.org/0000-0002-6674-7874\nhttps://orcid.org/0000-0001-8730-5031\nhttps://orcid.org/0000-0002-8628-2090\nhttps://orcid.org/0000-0001-8443-4460\nhttps://orcid.org/0000-0002-3641-5983\nhttps://orcid.org/0000-0002-1353-8964\nhttps://orcid.org/0000-0001-5672-214X\nhttps://orcid.org/0000-0003-2831-6982\nhttps://orcid.org/0000-0002-2253-819X\n\n\n28\n\nKyungpook National University, Daegu, Korea\nS. Dogra , C. Huh , B. Kim , D.H. Kim , G.N. Kim , J. Kim, J. Lee , S.W. Lee ,\nC.S. Moon , Y.D. Oh , S.I. Pak , M.S. Ryu , S. Sekmen , Y.C. Yang\n\nChonnam National University, Institute for Universe and Elementary Particles, Kwangju,\nKorea\nH. Kim , D.H. Moon\n\nHanyang University, Seoul, Korea\nE. Asilar , T.J. Kim , J. Park\n\nKorea University, Seoul, Korea\nS. Choi , S. Han, B. Hong , K. Lee, K.S. Lee , J. Lim, J. Park, S.K. Park, J. Yoo\n\nKyung Hee University, Department of Physics, Seoul, Korea\nJ. Goh\n\nSejong University, Seoul, Korea\nH. S. Kim , Y. Kim, S. Lee\n\nSeoul National University, Seoul, Korea\nJ. Almond, J.H. Bhyun, J. Choi , S. Jeon , J. Kim , J.S. Kim, S. Ko , H. Kwon , H. Lee ,\nS. Lee, B.H. Oh , S.B. Oh , H. Seo , U.K. Yang, I. Yoon\n\nUniversity of Seoul, Seoul, Korea\nW. Jang , D.Y. Kang, Y. Kang , D. Kim , S. Kim , B. Ko, J.S.H. Lee , Y. Lee , J.A. Merlin,\nI.C. Park , Y. Roh, D. Song, Watson, I.J. , S. Yang\n\nYonsei University, Department of Physics, Seoul, Korea\nS. Ha , H.D. Yoo\n\nSungkyunkwan University, Suwon, Korea\nM. Choi , M.R. Kim , H. Lee, Y. Lee , I. Yu\n\nCollege of Engineering and Technology, American University of the Middle East (AUM),\nDasman, Kuwait\nT. Beyrouthy, Y. Maghrbi\n\nRiga Technical University, Riga, Latvia\nK. Dreimanis , G. Pikurs, A. Potrebko , M. Seidel , V. Veckalns55\n\nVilnius University, Vilnius, Lithuania\nM. Ambrozas , A. Juodagalvis , A. Rinkevicius , G. Tamulaitis\n\nNational Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia\nN. Bin Norjoharuddeen , S.Y. Hoh56 , I. Yusuff56 , Z. Zolkapli\n\nUniversidad de Sonora (UNISON), Hermosillo, Mexico\nJ.F. Benitez , A. Castaneda Hernandez , H.A. Encinas Acosta, L.G. Gallegos Marı́ñez,\nM. León Coello , J.A. Murillo Quijada , A. Sehrawat , L. Valencia Palomo\n\nCentro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico\nG. Ayala , H. Castilla-Valdez , I. Heredia-De La Cruz57 , R. Lopez-Fernandez ,\nC.A. Mondragon Herrera, D.A. Perez Navarro , A. Sánchez Hernández\n\nUniversidad Iberoamericana, Mexico City, Mexico\nC. Oropeza Barrera , F. Vazquez Valencia\n\nhttps://orcid.org/0000-0002-0812-0758\nhttps://orcid.org/0000-0002-8513-2824\nhttps://orcid.org/0000-0002-9539-6815\nhttps://orcid.org/0000-0002-9023-6847\nhttps://orcid.org/0000-0002-3482-9082\nhttps://orcid.org/0000-0002-5351-7201\nhttps://orcid.org/0000-0002-1028-3468\nhttps://orcid.org/0000-0001-8229-7829\nhttps://orcid.org/0000-0002-7219-9931\nhttps://orcid.org/0000-0002-1447-3533\nhttps://orcid.org/0000-0002-1855-180X\nhttps://orcid.org/0000-0003-1726-5681\nhttps://orcid.org/0000-0003-1009-4621\nhttps://orcid.org/0000-0001-8019-9387\nhttps://orcid.org/0000-0002-5628-9187\nhttps://orcid.org/0000-0001-5680-599X\nhttps://orcid.org/0000-0001-8336-2434\nhttps://orcid.org/0000-0002-4683-6669\nhttps://orcid.org/0000-0001-6225-9876\nhttps://orcid.org/0000-0002-2259-9929\nhttps://orcid.org/0000-0002-3680-7039\nhttps://orcid.org/0000-0003-0463-3043\nhttps://orcid.org/0000-0002-1129-2083\nhttps://orcid.org/0000-0002-6543-9191\nhttps://orcid.org/0000-0002-2483-5104\nhttps://orcid.org/0000-0003-1208-6940\nhttps://orcid.org/0000-0001-9876-6642\nhttps://orcid.org/0000-0003-4377-9969\nhttps://orcid.org/0009-0002-5165-5018\nhttps://orcid.org/0000-0002-1138-3700\nhttps://orcid.org/0000-0002-9539-7789\nhttps://orcid.org/0000-0003-0710-4956\nhttps://orcid.org/0000-0002-3932-0605\nhttps://orcid.org/0000-0002-3491-8026\nhttps://orcid.org/0000-0002-1571-9072\nhttps://orcid.org/0000-0001-6079-3434\nhttps://orcid.org/0000-0002-8336-9182\nhttps://orcid.org/0000-0002-8015-7379\nhttps://orcid.org/0000-0002-2153-1519\nhttps://orcid.org/0000-0001-5572-5947\nhttps://orcid.org/0000-0003-4510-6776\nhttps://orcid.org/0000-0003-2141-3413\nhttps://orcid.org/0000-0001-6905-6553\nhttps://orcid.org/0000-0003-2538-1551\nhttps://orcid.org/0000-0002-3892-3500\nhttps://orcid.org/0000-0002-4811-626X\nhttps://orcid.org/0000-0002-2289-2527\nhttps://orcid.org/0000-0001-6954-9964\nhttps://orcid.org/0000-0003-1567-5548\nhttps://orcid.org/0000-0002-4960-7458\nhttps://orcid.org/0000-0003-0972-5641\nhttps://orcid.org/0000-0002-3776-8270\nhttps://orcid.org/0000-0003-3550-6151\nhttps://orcid.org/0000-0003-3676-9711\nhttps://orcid.org/0000-0003-2449-0158\nhttps://orcid.org/0000-0002-1501-3328\nhttps://orcid.org/0000-0002-7510-255X\nhttps://orcid.org/0000-0002-2913-9634\nhttps://orcid.org/0000-0002-8818-7476\nhttps://orcid.org/0000-0003-3233-5123\nhttps://orcid.org/0000-0003-2786-0732\nhttps://orcid.org/0000-0002-2633-6712\nhttps://orcid.org/0000-0003-4766-1546\nhttps://orcid.org/0000-0002-3761-911X\nhttps://orcid.org/0000-0003-4933-2092\nhttps://orcid.org/0000-0002-6816-7814\nhttps://orcid.org/0000-0002-8736-440X\nhttps://orcid.org/0000-0002-8294-8692\nhttps://orcid.org/0009-0005-9590-9958\nhttps://orcid.org/0000-0002-8133-6467\nhttps://orcid.org/0000-0002-2389-4831\nhttps://orcid.org/0000-0001-9280-4150\nhttps://orcid.org/0000-0001-9548-0358\nhttps://orcid.org/0000-0001-9724-0016\nhttps://orcid.org/0000-0001-6379-3982\n\n\n29\n\nBenemerita Universidad Autonoma de Puebla, Puebla, Mexico\nI. Pedraza , H.A. Salazar Ibarguen , C. Uribe Estrada\n\nUniversity of Montenegro, Podgorica, Montenegro\nI. Bubanja, J. Mijuskovic58, N. Raicevic\n\nNational Centre for Physics, Quaid-I-Azam University, Islamabad, Pakistan\nA. Ahmad , M.I. Asghar, A. Awais , M.I.M. Awan, M. Gul , H.R. Hoorani , W.A. Khan\n\nAGH University of Science and Technology Faculty of Computer Science, Electronics and\nTelecommunications, Krakow, Poland\nV. Avati, L. Grzanka , M. Malawski\n\nNational Centre for Nuclear Research, Swierk, Poland\nH. Bialkowska , M. Bluj , B. Boimska , M. Górski , M. Kazana , M. Szleper ,\nP. Zalewski\n\nInstitute of Experimental Physics, Faculty of Physics, University of Warsaw, Warsaw, Poland\nK. Bunkowski , K. Doroba , A. Kalinowski , M. Konecki , J. Krolikowski\n\nLaboratório de Instrumentação e Fı́sica Experimental de Partı́culas, Lisboa, Portugal\nM. Araujo , D. Bastos , A. Boletti , P. Faccioli , M. Gallinaro , J. Hollar ,\nN. Leonardo , T. Niknejad , M. Pisano , J. Seixas , J. Varela\n\nFaculty of Physics, University of Belgrade, Belgrade, Serbia\nP. Adzic59 , P. Milenovic\n\nVINCA Institute of Nuclear Sciences, University of Belgrade, Belgrade, Serbia\nM. Dordevic , J. Milosevic\n\nCentro de Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT),\nMadrid, Spain\nM. Aguilar-Benitez, J. Alcaraz Maestre , M. Barrio Luna, Cristina F. Bedoya , M. Cepeda ,\nM. Cerrada , N. Colino , B. De La Cruz , A. Delgado Peris , D. Fernández Del Val ,\nJ.P. Fernández Ramos , J. Flix , M.C. Fouz , O. Gonzalez Lopez , S. Goy Lopez ,\nJ.M. Hernandez , M.I. Josa , J. León Holgado , D. Moran , C. Perez Dengra , A. Pérez-\nCalero Yzquierdo , J. Puerta Pelayo , I. Redondo , D.D. Redondo Ferrero , L. Romero,\nS. Sánchez Navas , J. Sastre , L. Urda Gómez , J. Vazquez Escobar , C. Willmott\n\nUniversidad Autónoma de Madrid, Madrid, Spain\nJ.F. de Trocóniz\n\nUniversidad de Oviedo, Instituto Universitario de Ciencias y Tecnologı́as Espaciales de\nAsturias (ICTEA), Oviedo, Spain\nB. Alvarez Gonzalez , J. Cuevas , J. Fernandez Menendez , S. Folgueras , I. Gonza-\nlez Caballero , J.R. González Fernández , E. Palencia Cortezon , C. Ramón Álvarez ,\nV. Rodrı́guez Bouza , A. Soto Rodrı́guez , A. Trapote , C. Vico Villalba\n\nInstituto de Fı́sica de Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain\nJ.A. Brochero Cifuentes , I.J. Cabrillo , A. Calderon , J. Duarte Campderros , M. Fernan-\ndez , C. Fernandez Madrazo , G. Gomez , C. Lasaosa Garcı́a , C. Martinez Rivero ,\nP. Martinez Ruiz del Arbol , F. Matorras , P. Matorras Cuevas , J. Piedra Gomez ,\nC. Prieels, L. Scodellaro , I. Vila , J.M. Vizan Garcia\n\nUniversity of Colombo, Colombo, Sri Lanka\nM.K. Jayananda , B. Kailasapathy60 , D.U.J. Sonnadara , D.D.C. Wickramarathna\n\nhttps://orcid.org/0000-0002-2669-4659\nhttps://orcid.org/0000-0003-4556-7302\nhttps://orcid.org/0000-0002-2425-7340\nhttps://orcid.org/0000-0002-2386-2290\nhttps://orcid.org/0000-0002-4770-1897\nhttps://orcid.org/0000-0003-3563-257X\nhttps://orcid.org/0000-0002-5704-1896\nhttps://orcid.org/0000-0002-0088-5043\nhttps://orcid.org/0000-0003-0488-0941\nhttps://orcid.org/0000-0002-3599-854X\nhttps://orcid.org/0000-0001-6005-0243\nhttps://orcid.org/0000-0002-5956-6258\nhttps://orcid.org/0000-0003-1229-1442\nhttps://orcid.org/0000-0002-4200-1541\nhttps://orcid.org/0000-0003-2146-187X\nhttps://orcid.org/0000-0002-7821-3036\nhttps://orcid.org/0000-0002-1697-004X\nhttps://orcid.org/0000-0003-4429-2888\nhttps://orcid.org/0000-0001-6371-9336\nhttps://orcid.org/0000-0002-7818-2364\nhttps://orcid.org/0000-0002-1280-5493\nhttps://orcid.org/0000-0001-9482-4841\nhttps://orcid.org/0000-0002-3055-0236\nhttps://orcid.org/0000-0002-8152-3756\nhttps://orcid.org/0000-0002-7032-2481\nhttps://orcid.org/0000-0003-3288-7737\nhttps://orcid.org/0000-0003-1849-6692\nhttps://orcid.org/0000-0003-1261-2277\nhttps://orcid.org/0000-0002-8664-0134\nhttps://orcid.org/0000-0002-9746-4594\nhttps://orcid.org/0000-0003-3276-9482\nhttps://orcid.org/0000-0002-0264-7217\nhttps://orcid.org/0000-0002-7531-0842\nhttps://orcid.org/0000-0003-2613-3146\nhttps://orcid.org/0000-0002-5862-7397\nhttps://orcid.org/0000-0001-7132-3550\nhttps://orcid.org/0000-0002-8407-3236\nhttps://orcid.org/0000-0001-8486-4604\nhttps://orcid.org/0000-0003-0914-7474\nhttps://orcid.org/0000-0001-8057-9152\nhttps://orcid.org/0000-0002-6076-4083\nhttps://orcid.org/0000-0003-0112-1691\nhttps://orcid.org/0000-0002-3656-0259\nhttps://orcid.org/0000-0001-9057-5614\nhttps://orcid.org/0000-0002-8511-7958\nhttps://orcid.org/0000-0003-2346-1590\nhttps://orcid.org/0000-0002-0122-313X\nhttps://orcid.org/0000-0003-2688-8047\nhttps://orcid.org/0000-0003-2950-976X\nhttps://orcid.org/0000-0002-4532-6464\nhttps://orcid.org/0000-0001-6508-5090\nhttps://orcid.org/0000-0001-6436-7547\nhttps://orcid.org/0000-0002-4985-6964\nhttps://orcid.org/0000-0002-4156-6460\nhttps://orcid.org/0000-0002-1941-9333\nhttps://orcid.org/0000-0003-2821-4249\nhttps://orcid.org/0000-0003-3036-7965\nhttps://orcid.org/0000-0001-7390-1457\nhttps://orcid.org/0000-0003-3737-4121\nhttps://orcid.org/0000-0002-3463-0559\nhttps://orcid.org/0000-0001-6129-9059\nhttps://orcid.org/0000-0002-1654-2846\nhttps://orcid.org/0000-0002-7865-5010\nhttps://orcid.org/0000-0002-7533-2283\nhttps://orcid.org/0000-0002-0798-9806\nhttps://orcid.org/0000-0001-7767-4810\nhttps://orcid.org/0000-0001-5080-0821\nhttps://orcid.org/0000-0002-5213-3708\nhttps://orcid.org/0000-0001-7191-1125\nhttps://orcid.org/0000-0002-8087-3199\nhttps://orcid.org/0000-0002-4825-8188\nhttps://orcid.org/0000-0001-8264-0287\nhttps://orcid.org/0000-0003-1175-0002\nhttps://orcid.org/0000-0002-7225-7310\nhttps://orcid.org/0000-0002-2993-8663\nhttps://orcid.org/0000-0002-4030-2551\nhttps://orcid.org/0000-0002-1905-1874\nhttps://orcid.org/0000-0003-2093-7856\nhttps://orcid.org/0000-0002-0367-4022\nhttps://orcid.org/0000-0002-7205-2040\nhttps://orcid.org/0000-0003-0687-5214\nhttps://orcid.org/0000-0002-4824-1087\nhttps://orcid.org/0000-0001-9748-4336\nhttps://orcid.org/0000-0002-1077-6553\nhttps://orcid.org/0000-0003-2726-7111\nhttps://orcid.org/0000-0002-3224-956X\nhttps://orcid.org/0000-0002-7737-5121\nhttps://orcid.org/0000-0003-4295-5668\nhttps://orcid.org/0000-0001-7481-7273\nhttps://orcid.org/0000-0002-9157-1700\nhttps://orcid.org/0000-0002-4974-8330\nhttps://orcid.org/0000-0002-6797-7209\nhttps://orcid.org/0000-0002-6823-8854\nhttps://orcid.org/0000-0002-7577-310X\nhttps://orcid.org/0000-0003-2424-1303\nhttps://orcid.org/0000-0001-7862-2537\nhttps://orcid.org/0000-0002-6941-8478\n\n\n30\n\nUniversity of Ruhuna, Department of Physics, Matara, Sri Lanka\nW.G.D. Dharmaratna , K. Liyanage , N. Perera , N. Wickramage\n\nCERN, European Organization for Nuclear Research, Geneva, Switzerland\nD. Abbaneo , E. Auffray , G. Auzinger , J. Baechler, P. Baillon†, D. Barney ,\nA. Bermúdez Martı́nez , M. Bianco , B. Bilin , A.A. Bin Anuar , A. Bocci , E. Bron-\ndolin , C. Caillol , T. Camporesi , G. Cerminara , N. Chernyavskaya , S.S. Chhibra ,\nS. Choudhury, M. Cipriani , D. d’Enterria , A. Dabrowski , A. David , A. De Roeck ,\nM.M. Defranchis , M. Deile , M. Dobson , M. Dünser , N. Dupont, F. Fallavollita61,\nA. Florent , L. Forthomme , G. Franzoni , W. Funk , S. Ghosh62 , S. Giani, D. Gigi,\nK. Gill , F. Glege , L. Gouskos , E. Govorkova , M. Haranko , J. Hegeman ,\nV. Innocente , T. James , P. Janot , J. Kaspar , J. Kieseler , N. Kratochwil , S. Laurila ,\nP. Lecoq , E. Leutgeb , C. Lourenço , B. Maier , L. Malgeri , M. Mannelli ,\nA.C. Marini , F. Meijers , S. Mersi , E. Meschi , F. Moortgat , M. Mulders ,\nS. Orfanelli, L. Orsini, F. Pantaleo , E. Perez, M. Peruzzi , A. Petrilli , G. Petrucciani ,\nA. Pfeiffer , M. Pierini , D. Piparo , M. Pitt , H. Qu , T. Quast, D. Rabady ,\nA. Racz, G. Reales Gutiérrez, M. Rovere , H. Sakulin , J. Salfeld-Nebgen , S. Scarfi ,\nM. Selvaggi , A. Sharma , P. Silva , P. Sphicas63 , A.G. Stahl Leiton , S. Summers ,\nK. Tatar , D. Treille , P. Tropea , A. Tsirou, D. Walter , J. Wanczyk64 , K.A. Wozniak ,\nW.D. Zeuner\n\nPaul Scherrer Institut, Villigen, Switzerland\nT. Bevilacqua65 , L. Caminada65 , A. Ebrahimi , W. Erdmann , R. Horisberger ,\nQ. Ingram , H.C. Kaestli , D. Kotlinski , C. Lange , M. Missiroli65 , L. Noehte65 ,\nT. Rohe\n\nETH Zurich - Institute for Particle Physics and Astrophysics (IPA), Zurich, Switzerland\nT.K. Aarrestad , K. Androsov64 , M. Backhaus , A. Calandri , K. Datta , A. De Cosa ,\nG. Dissertori , M. Dittmar, M. Donegà , F. Eble , M. Galli , K. Gedia , F. Glessgen ,\nT.A. Gómez Espinosa , C. Grab , D. Hits , W. Lustermann , A.-M. Lyon ,\nR.A. Manzoni , L. Marchese , C. Martin Perez , A. Mascellani64 , F. Nessi-Tedaldi ,\nJ. Niedziela , F. Pauss , V. Perovic , S. Pigazzini , M.G. Ratti , M. Reichmann ,\nC. Reissel , T. Reitenspiess , B. Ristic , F. Riti , D. Ruini, D.A. Sanz Becerra ,\nR. Seidita , J. Steggemann64 , D. Valsecchi , R. Wallny\n\nUniversität Zürich, Zurich, Switzerland\nC. Amsler66 , P. Bärtschi , C. Botta , D. Brzhechko, M.F. Canelli , K. Cormier ,\nA. De Wit , R. Del Burgo, J.K. Heikkilä , M. Huwiler , W. Jin , A. Jofre-\nhei , B. Kilminster , S. Leontsinis , S.P. Liechti , A. Macchiolo , P. Meiring ,\nV.M. Mikuni , U. Molinatti , I. Neutelings , A. Reimers , P. Robmann, S. Sanchez Cruz ,\nK. Schweiger , M. Senger , Y. Takahashi\n\nNational Central University, Chung-Li, Taiwan\nC. Adloff67, C.M. Kuo, W. Lin, P.K. Rout , P.C. Tiwari38 , S.S. Yu\n\nNational Taiwan University (NTU), Taipei, Taiwan\nL. Ceard, Y. Chao , K.F. Chen , P.s. Chen, H. Cheng , W.-S. Hou , R. Khurana, G. Kole ,\nY.y. Li , R.-S. Lu , E. Paganis , A. Psallidas, A. Steen , H.y. Wu, E. Yazgan\n\nChulalongkorn University, Faculty of Science, Department of Physics, Bangkok, Thailand\nC. Asawatangtrakuldee , N. Srimanobhas , V. Wachirapusitanand\n\nÇukurova University, Physics Department, Science and Art Faculty, Adana, Turkey\n\nhttps://orcid.org/0000-0002-6366-837X\nhttps://orcid.org/0000-0002-3792-7665\nhttps://orcid.org/0000-0002-4747-9106\nhttps://orcid.org/0000-0001-7760-3537\nhttps://orcid.org/0000-0001-9416-1742\nhttps://orcid.org/0000-0001-8540-1097\nhttps://orcid.org/0000-0001-7077-8262\nhttps://orcid.org/0000-0002-4927-4921\nhttps://orcid.org/0000-0001-8822-4727\nhttps://orcid.org/0000-0002-8336-3282\nhttps://orcid.org/0000-0003-1439-7128\nhttps://orcid.org/0000-0002-2988-9830\nhttps://orcid.org/0000-0002-6515-5666\nhttps://orcid.org/0000-0001-5420-586X\nhttps://orcid.org/0000-0002-5642-3040\nhttps://orcid.org/0000-0001-5066-1876\nhttps://orcid.org/0000-0002-2897-5753\nhttps://orcid.org/0000-0002-2264-2229\nhttps://orcid.org/0000-0002-1643-1388\nhttps://orcid.org/0000-0002-0151-4439\nhttps://orcid.org/0000-0002-5754-4303\nhttps://orcid.org/0000-0003-2570-9676\nhttps://orcid.org/0000-0001-5854-7699\nhttps://orcid.org/0000-0002-9228-5271\nhttps://orcid.org/0000-0001-9573-3714\nhttps://orcid.org/0000-0001-5085-7270\nhttps://orcid.org/0009-0007-5021-3230\nhttps://orcid.org/0000-0002-8502-2297\nhttps://orcid.org/0000-0001-6544-3679\nhttps://orcid.org/0000-0002-3302-336X\nhttps://orcid.org/0000-0001-9179-4253\nhttps://orcid.org/0000-0003-0422-6739\nhttps://orcid.org/0000-0001-6717-0803\nhttps://orcid.org/0009-0001-9331-5145\nhttps://orcid.org/0000-0002-4526-2149\nhttps://orcid.org/0000-0002-9547-7471\nhttps://orcid.org/0000-0003-1920-6618\nhttps://orcid.org/0000-0002-9376-9235\nhttps://orcid.org/0000-0002-2938-2263\nhttps://orcid.org/0000-0003-3209-2088\nhttps://orcid.org/0000-0002-3727-0202\nhttps://orcid.org/0000-0001-7339-4272\nhttps://orcid.org/0000-0001-5639-2267\nhttps://orcid.org/0000-0003-1644-7678\nhttps://orcid.org/0000-0001-5297-1878\nhttps://orcid.org/0000-0001-7507-8636\nhttps://orcid.org/0000-0002-3198-0115\nhttps://orcid.org/0000-0003-4838-3306\nhttps://orcid.org/0000-0003-0885-6711\nhttps://orcid.org/0000-0001-5270-7540\nhttps://orcid.org/0000-0002-0113-7389\nhttps://orcid.org/0000-0003-3748-8946\nhttps://orcid.org/0000-0003-2351-0487\nhttps://orcid.org/0000-0002-6530-3657\nhttps://orcid.org/0000-0003-2155-6692\nhttps://orcid.org/0000-0003-4502-6151\nhttps://orcid.org/0000-0001-7199-0046\nhttps://orcid.org/0000-0001-7432-6634\nhttps://orcid.org/0000-0003-3266-4357\nhttps://orcid.org/0000-0002-0416-696X\nhttps://orcid.org/0000-0003-0887-1882\nhttps://orcid.org/0000-0003-0889-4726\nhttps://orcid.org/0000-0001-5328-448X\nhttps://orcid.org/0000-0003-1939-4268\nhttps://orcid.org/0009-0006-6958-3111\nhttps://orcid.org/0000-0003-2461-5985\nhttps://orcid.org/0000-0002-0250-8655\nhttps://orcid.org/0000-0001-9239-0605\nhttps://orcid.org/0000-0001-8048-1622\nhttps://orcid.org/0000-0003-2181-7258\nhttps://orcid.org/0000-0003-3879-5622\nhttps://orcid.org/0009-0006-8689-3576\nhttps://orcid.org/0000-0002-5144-9655\nhttps://orcid.org/0000-0002-9860-1650\nhttps://orcid.org/0000-0002-5725-041X\nhttps://orcid.org/0000-0002-5456-5977\nhttps://orcid.org/0000-0002-5397-252X\nhttps://orcid.org/0000-0003-4244-2061\nhttps://orcid.org/0000-0002-6448-0168\nhttps://orcid.org/0009-0005-5952-9843\nhttps://orcid.org/0000-0003-1899-2266\nhttps://orcid.org/0000-0001-8584-9705\nhttps://orcid.org/0000-0002-8562-1863\nhttps://orcid.org/0000-0002-4395-1581\nhttps://orcid.org/0000-0001-9791-2353\nhttps://orcid.org/0000-0001-5677-6033\nhttps://orcid.org/0000-0003-4472-867X\nhttps://orcid.org/0000-0001-9964-249X\nhttps://orcid.org/0000-0002-5594-1321\nhttps://orcid.org/0000-0002-9576-055X\nhttps://orcid.org/0000-0003-1979-7331\nhttps://orcid.org/0000-0001-5333-4918\nhttps://orcid.org/0000-0002-3632-3157\nhttps://orcid.org/0000-0002-1780-1344\nhttps://orcid.org/0000-0001-6125-7203\nhttps://orcid.org/0009-0005-6188-7754\nhttps://orcid.org/0000-0002-7671-243X\nhttps://orcid.org/0000-0003-2694-6542\nhttps://orcid.org/0000-0002-5888-2304\nhttps://orcid.org/0000-0001-7774-0099\nhttps://orcid.org/0000-0002-6674-0015\nhttps://orcid.org/0000-0003-2533-2856\nhttps://orcid.org/0000-0002-4549-2569\nhttps://orcid.org/0000-0001-9830-0412\nhttps://orcid.org/0009-0002-0638-3447\nhttps://orcid.org/0000-0002-9408-4756\nhttps://orcid.org/0009-0006-0914-7684\nhttps://orcid.org/0000-0001-5309-1960\nhttps://orcid.org/0000-0002-9443-7769\nhttps://orcid.org/0000-0002-6182-3380\nhttps://orcid.org/0000-0002-3135-6427\nhttps://orcid.org/0000-0003-4970-2217\nhttps://orcid.org/0009-0004-1393-6577\nhttps://orcid.org/0000-0002-7584-5038\nhttps://orcid.org/0000-0001-6627-8716\nhttps://orcid.org/0000-0003-1581-6152\nhttps://orcid.org/0000-0001-6362-5356\nhttps://orcid.org/0000-0002-4721-7966\nhttps://orcid.org/0000-0002-9514-0799\nhttps://orcid.org/0000-0002-3752-4639\nhttps://orcid.org/0009-0002-8559-0531\nhttps://orcid.org/0000-0002-8046-4344\nhttps://orcid.org/0000-0003-1777-7855\nhttps://orcid.org/0000-0002-6220-5496\nhttps://orcid.org/0000-0001-7080-1119\nhttps://orcid.org/0000-0002-2249-0835\nhttps://orcid.org/0000-0002-8610-1130\nhttps://orcid.org/0000-0002-1466-9077\nhttps://orcid.org/0000-0002-6610-4019\nhttps://orcid.org/0000-0002-3533-6191\nhttps://orcid.org/0000-0003-4420-5510\nhttps://orcid.org/0000-0001-8587-8266\nhttps://orcid.org/0000-0001-8038-1613\nhttps://orcid.org/0000-0002-7695-501X\nhttps://orcid.org/0000-0002-8842-6027\nhttps://orcid.org/0000-0002-8072-795X\nhttps://orcid.org/0000-0001-6361-2117\nhttps://orcid.org/0000-0001-7873-3579\nhttps://orcid.org/0000-0002-5291-1661\nhttps://orcid.org/0000-0002-0538-1469\nhttps://orcid.org/0000-0002-9806-5907\nhttps://orcid.org/0009-0009-8976-7702\nhttps://orcid.org/0000-0002-8992-5426\nhttps://orcid.org/0000-0002-6657-0407\nhttps://orcid.org/0000-0002-7561-6091\nhttps://orcid.org/0000-0002-1192-1628\nhttps://orcid.org/0000-0003-0199-6957\nhttps://orcid.org/0009-0001-9480-4039\nhttps://orcid.org/0000-0002-1579-2421\nhttps://orcid.org/0000-0002-9235-3406\nhttps://orcid.org/0009-0002-6473-1403\nhttps://orcid.org/0000-0002-9438-2059\nhttps://orcid.org/0000-0002-9991-195X\nhttps://orcid.org/0000-0002-5846-3919\nhttps://orcid.org/0000-0002-1992-5711\nhttps://orcid.org/0000-0001-5184-2265\nhttps://orcid.org/0000-0001-8149-6180\nhttps://orcid.org/0000-0002-3667-3843\nhttps://orcid.org/0000-0002-6011-8516\nhttps://orcid.org/0000-0002-5976-318X\nhttps://orcid.org/0000-0003-1304-3782\nhttps://orcid.org/0000-0001-6456-7178\nhttps://orcid.org/0000-0002-4260-5118\nhttps://orcid.org/0000-0002-3285-1497\nhttps://orcid.org/0000-0003-3598-556X\nhttps://orcid.org/0000-0001-6828-1695\nhttps://orcid.org/0000-0002-1950-8993\nhttps://orcid.org/0009-0006-4366-3463\nhttps://orcid.org/0000-0001-5732-7950\nhttps://orcid.org/0000-0003-2234-7219\nhttps://orcid.org/0000-0003-3563-2959\nhttps://orcid.org/0000-0001-8251-5160\n\n\n31\n\nD. Agyel , F. Boran , Z.S. Demiroglu , F. Dolek , I. Dumanoglu68 , E. Eskut ,\nY. Guler69 , E. Gurpinar Guler69 , C. Isik , O. Kara, A. Kayis Topaksu , U. Kiminsu ,\nG. Onengut , K. Ozdemir70 , A. Polatoz , B. Tali71 , U.G. Tok , S. Turkcapar ,\nE. Uslan , I.S. Zorbakir\n\nMiddle East Technical University, Physics Department, Ankara, Turkey\nG. Karapinar72, K. Ocalan73 , M. Yalvac74\n\nBogazici University, Istanbul, Turkey\nB. Akgun , I.O. Atakisi , E. Gülmez , M. Kaya75 , O. Kaya76 , S. Tekten77\n\nIstanbul Technical University, Istanbul, Turkey\nA. Cakir , K. Cankocak68 , Y. Komurcu , S. Sen78\n\nIstanbul University, Istanbul, Turkey\nO. Aydilek , S. Cerci71 , V. Epshteyn , B. Hacisahinoglu , I. Hos79 , B. Isildak80 ,\nB. Kaynak , S. Ozkorucuklu , C. Simsek , D. Sunar Cerci71\n\nInstitute for Scintillation Materials of National Academy of Science of Ukraine, Kharkiv,\nUkraine\nB. Grynyov\n\nNational Science Centre, Kharkiv Institute of Physics and Technology, Kharkiv, Ukraine\nL. Levchuk\n\nUniversity of Bristol, Bristol, United Kingdom\nD. Anthony , J.J. Brooke , A. Bundock , E. Clement , D. Cussans , H. Flacher ,\nM. Glowacki, J. Goldstein , H.F. Heath , L. Kreczko , B. Krikler , S. Paramesvaran ,\nS. Seif El Nasr-Storey, V.J. Smith , N. Stylianou81 , K. Walkingshaw Pass, R. White\n\nRutherford Appleton Laboratory, Didcot, United Kingdom\nA.H. Ball, K.W. Bell , A. Belyaev82 , C. Brew , R.M. Brown , D.J.A. Cockerill ,\nC. Cooke , K.V. Ellis, K. Harder , S. Harper , M.-L. Holmberg83 , Sh. Jain , J. Linacre ,\nK. Manolopoulos, D.M. Newbold , E. Olaiya, D. Petyt , T. Reis , G. Salvi , T. Schuh,\nC.H. Shepherd-Themistocleous , I.R. Tomalin, T. Williams\n\nImperial College, London, United Kingdom\nR. Bainbridge , P. Bloch , S. Bonomally, J. Borg , C.E. Brown , O. Buchmuller,\nV. Cacchio, C.A. Carrillo Montoya , V. Cepaitis , G.S. Chahal84 , D. Colling , J.S. Dancu,\nP. Dauncey , G. Davies , J. Davies, M. Della Negra , S. Fayer, G. Fedi , G. Hall ,\nM.H. Hassanshahi , A. Howard, G. Iles , J. Langford , L. Lyons , A.-M. Magnan ,\nS. Malik, A. Martelli , M. Mieskolainen , D.G. Monk , J. Nash85 , M. Pesaresi,\nB.C. Radburn-Smith , A. Richards, A. Rose , E. Scott , C. Seez , R. Shukla ,\nA. Tapper , K. Uchida , G.P. Uttley , L.H. Vage, T. Virdee27 , M. Vojinovic ,\nN. Wardle , S.N. Webb , D. Winterbottom\n\nBrunel University, Uxbridge, United Kingdom\nK. Coldham, J.E. Cole , A. Khan, P. Kyberd , I.D. Reid\n\nBaylor University, Waco, Texas, USA\nS. Abdullin , A. Brinkerhoff , B. Caraway , J. Dittmann , K. Hatakeyama , A.R. Kanu-\nganti , B. McMaster , M. Saunders , S. Sawant , C. Sutantawibul , M. Toms ,\nJ. Wilson\n\nCatholic University of America, Washington, DC, USA\n\nhttps://orcid.org/0000-0002-1797-8844\nhttps://orcid.org/0000-0002-3611-390X\nhttps://orcid.org/0000-0001-7977-7127\nhttps://orcid.org/0000-0001-7092-5517\nhttps://orcid.org/0000-0002-0039-5503\nhttps://orcid.org/0000-0001-8328-3314\nhttps://orcid.org/0000-0001-7598-5252\nhttps://orcid.org/0000-0002-6172-0285\nhttps://orcid.org/0000-0002-7977-0811\nhttps://orcid.org/0000-0002-3169-4573\nhttps://orcid.org/0000-0001-6940-7800\nhttps://orcid.org/0000-0002-6274-4254\nhttps://orcid.org/0000-0002-0103-1488\nhttps://orcid.org/0000-0001-9516-0821\nhttps://orcid.org/0000-0002-7447-5602\nhttps://orcid.org/0000-0002-3039-021X\nhttps://orcid.org/0000-0003-2608-0494\nhttps://orcid.org/0000-0002-2472-0526\nhttps://orcid.org/0000-0002-5962-2221\nhttps://orcid.org/0000-0002-8419-1400\nhttps://orcid.org/0000-0003-4915-9162\nhttps://orcid.org/0000-0001-8888-3562\nhttps://orcid.org/0000-0002-9231-7464\nhttps://orcid.org/0000-0002-6353-518X\nhttps://orcid.org/0000-0003-2890-4493\nhttps://orcid.org/0000-0002-8485-3822\nhttps://orcid.org/0000-0002-9624-5525\nhttps://orcid.org/0000-0002-8627-7689\nhttps://orcid.org/0000-0002-3829-3481\nhttps://orcid.org/0000-0002-7084-030X\nhttps://orcid.org/0000-0001-7325-1087\nhttps://orcid.org/0000-0002-2567-6766\nhttps://orcid.org/0000-0002-8702-6152\nhttps://orcid.org/0000-0002-8863-6374\nhttps://orcid.org/0000-0002-2646-1230\nhttps://orcid.org/0000-0002-7678-1101\nhttps://orcid.org/0000-0002-0283-5234\nhttps://orcid.org/0000-0003-3857-2496\nhttps://orcid.org/0000-0001-5153-9266\nhttps://orcid.org/0000-0002-7359-8635\nhttps://orcid.org/0000-0002-5412-4688\nhttps://orcid.org/0000-0002-3299-9985\nhttps://orcid.org/0000-0001-5889-7410\nhttps://orcid.org/0000-0002-5016-8886\nhttps://orcid.org/0000-0003-2529-0684\nhttps://orcid.org/0000-0002-2916-6456\nhttps://orcid.org/0000-0003-3412-4004\nhttps://orcid.org/0000-0001-8192-0826\nhttps://orcid.org/0000-0002-5371-941X\nhttps://orcid.org/0000-0003-1591-6014\nhttps://orcid.org/0000-0001-6576-9740\nhttps://orcid.org/0000-0003-2341-8330\nhttps://orcid.org/0000-0001-9712-0030\nhttps://orcid.org/0000-0003-4748-8296\nhttps://orcid.org/0000-0003-4543-2547\nhttps://orcid.org/0000-0002-0113-6829\nhttps://orcid.org/0000-0001-5793-526X\nhttps://orcid.org/0000-0002-2294-5860\nhttps://orcid.org/0000-0002-1733-4408\nhttps://orcid.org/0000-0001-6595-8365\nhttps://orcid.org/0000-0002-6728-0153\nhttps://orcid.org/0000-0003-2427-5765\nhttps://orcid.org/0000-0003-3730-4895\nhttps://orcid.org/0000-0002-2965-6973\nhttps://orcid.org/0000-0001-5637-2653\nhttps://orcid.org/0000-0002-9473-5985\nhttps://orcid.org/0000-0003-1770-5309\nhttps://orcid.org/0000-0001-7555-652X\nhttps://orcid.org/0000-0002-9015-9634\nhttps://orcid.org/0000-0002-2369-4469\nhttps://orcid.org/0000-0003-3703-6624\nhttps://orcid.org/0000-0002-2787-1063\nhttps://orcid.org/0000-0003-0551-6949\nhttps://orcid.org/0000-0002-8724-4678\nhttps://orcid.org/0000-0001-9157-4832\nhttps://orcid.org/0000-0001-6716-979X\nhttps://orcid.org/0000-0002-7716-7621\nhttps://orcid.org/0000-0002-7766-6615\nhttps://orcid.org/0000-0002-6245-6535\nhttps://orcid.org/0000-0002-4809-4056\nhttps://orcid.org/0000-0003-0320-4407\nhttps://orcid.org/0000-0001-9959-4977\nhttps://orcid.org/0000-0001-6839-9466\nhttps://orcid.org/0000-0001-8668-5001\nhttps://orcid.org/0000-0001-6497-8081\nhttps://orcid.org/0000-0001-9101-2573\nhttps://orcid.org/0000-0002-6299-8385\nhttps://orcid.org/0000-0001-6634-4517\nhttps://orcid.org/0000-0002-1219-5859\nhttps://orcid.org/0000-0002-3931-4379\nhttps://orcid.org/0000-0001-7945-9188\nhttps://orcid.org/0000-0002-4266-1646\nhttps://orcid.org/0000-0003-3530-2255\nhttps://orcid.org/0000-0001-8893-7401\nhttps://orcid.org/0000-0002-8377-1999\nhttps://orcid.org/0000-0003-0607-6519\nhttps://orcid.org/0000-0003-1488-9675\nhttps://orcid.org/0000-0002-9773-550X\nhttps://orcid.org/0000-0003-0352-6836\nhttps://orcid.org/0000-0002-1637-5494\nhttps://orcid.org/0000-0001-5670-5497\nhttps://orcid.org/0000-0003-4543-864X\nhttps://orcid.org/0000-0003-0742-2276\nhttps://orcid.org/0009-0002-6248-6467\nhttps://orcid.org/0000-0001-7429-2198\nhttps://orcid.org/0000-0001-8665-2808\nhttps://orcid.org/0000-0003-1344-3356\nhttps://orcid.org/0000-0003-4749-8814\nhttps://orcid.org/0000-0001-5638-7599\nhttps://orcid.org/0000-0002-7353-7090\nhttps://orcid.org/0000-0002-9235-779X\nhttps://orcid.org/0000-0003-4885-6935\nhttps://orcid.org/0000-0002-4819-7995\nhttps://orcid.org/0000-0002-6088-2020\nhttps://orcid.org/0000-0002-1911-3158\nhttps://orcid.org/0000-0002-6012-2451\nhttps://orcid.org/0000-0002-0789-1200\nhttps://orcid.org/0000-0002-4494-0446\nhttps://orcid.org/0000-0003-1572-9075\nhttps://orcid.org/0000-0002-1981-7753\nhttps://orcid.org/0000-0003-0600-0151\nhttps://orcid.org/0000-0002-7703-3973\nhttps://orcid.org/0000-0002-5672-7394\n\n\n32\n\nR. Bartek , A. Dominguez , C. Huerta Escamilla, A.E. Simsek , R. Uniyal , A.M. Var-\ngas Hernandez\n\nThe University of Alabama, Tuscaloosa, Alabama, USA\nR. Chudasama , S.I. Cooper , D. Di Croce , S.V. Gleyzer , C.U. Perez , P. Rumerio86 ,\nE. Usai , C. West\n\nBoston University, Boston, Massachusetts, USA\nA. Akpinar , A. Albert , D. Arcaro , C. Cosby , Z. Demiragli , C. Erice ,\nE. Fontanesi , D. Gastler , S. May , J. Rohlf , K. Salyer , D. Sperka , D. Spitzbart ,\nI. Suarez , A. Tsatsos , S. Yuan\n\nBrown University, Providence, Rhode Island, USA\nG. Benelli , X. Coubez22, D. Cutts , M. Hadley , U. Heintz , J.M. Hogan87 , T. Kwon ,\nG. Landsberg , K.T. Lau , D. Li , J. Luo , M. Narain , N. Pervan , S. Sagir88 ,\nF. Simpson , W.Y. Wong, X. Yan , D. Yu , W. Zhang\n\nUniversity of California, Davis, Davis, California, USA\nS. Abbott , J. Bonilla , C. Brainerd , R. Breedon , M. Calderon De La Barca Sanchez ,\nM. Chertok , J. Conway , P.T. Cox , R. Erbacher , G. Haza , F. Jensen , O. Kukral ,\nG. Mocellin , M. Mulhearn , D. Pellett , B. Regnery , W. Wei, Y. Yao , F. Zhang\n\nUniversity of California, Los Angeles, California, USA\nM. Bachtis , R. Cousins , A. Datta , J. Hauser , M. Ignatenko , M.A. Iqbal , T. Lam ,\nE. Manca , W.A. Nash , D. Saltzberg , B. Stone , V. Valuev\n\nUniversity of California, Riverside, Riverside, California, USA\nR. Clare , J.W. Gary , M. Gordon, G. Hanson , O.R. Long , N. Manganelli , W. Si ,\nS. Wimpenny\n\nUniversity of California, San Diego, La Jolla, California, USA\nJ.G. Branson, S. Cittolin, S. Cooperstein , D. Diaz , J. Duarte , R. Gerosa , L. Giannini ,\nJ. Guiang , R. Kansal , V. Krutelyov , R. Lee , J. Letts , M. Masciovecchio ,\nF. Mokhtar , M. Pieri , M. Quinnan , B.V. Sathia Narayanan , V. Sharma , M. Tadel ,\nE. Vourliotis , F. Würthwein , Y. Xiang , A. Yagil\n\nUniversity of California, Santa Barbara - Department of Physics, Santa Barbara, California,\nUSA\nL. Brennan, C. Campagnari , M. Citron , G. Collura , A. Dorsett , J. Incandela ,\nM. Kilpatrick , J. Kim , A.J. Li , P. Masterson , H. Mei , M. Oshiro , J. Richman ,\nU. Sarica , R. Schmitz , F. Setti , J. Sheplock , P. Siddireddy, D. Stuart , S. Wang\n\nCalifornia Institute of Technology, Pasadena, California, USA\nA. Bornheim , O. Cerri, A. Latorre, J.M. Lawhorn , J. Mao , H.B. Newman ,\nT. Q. Nguyen , M. Spiropulu , J.R. Vlimant , C. Wang , S. Xie , R.Y. Zhu\n\nCarnegie Mellon University, Pittsburgh, Pennsylvania, USA\nJ. Alison , S. An , M.B. Andrews , P. Bryant , V. Dutta , T. Ferguson , A. Harilal ,\nC. Liu , T. Mudholkar , S. Murthy , M. Paulini , A. Roberts , A. Sanchez , W. Terrill\n\nUniversity of Colorado Boulder, Boulder, Colorado, USA\nJ.P. Cumalat , W.T. Ford , A. Hassani , G. Karathanasis , E. MacDonald, F. Marini ,\nA. Perloff , C. Savard , N. Schonbeck , K. Stenson , K.A. Ulmer , S.R. Wagner ,\nN. Zipper\n\nhttps://orcid.org/0000-0002-1686-2882\nhttps://orcid.org/0000-0002-7420-5493\nhttps://orcid.org/0000-0002-9074-2256\nhttps://orcid.org/0000-0001-7345-6293\nhttps://orcid.org/0000-0002-8911-7197\nhttps://orcid.org/0009-0007-8848-6146\nhttps://orcid.org/0000-0002-4618-0313\nhttps://orcid.org/0000-0002-1122-7919\nhttps://orcid.org/0000-0002-6222-8102\nhttps://orcid.org/0000-0002-6861-2674\nhttps://orcid.org/0000-0002-1702-5541\nhttps://orcid.org/0000-0001-9323-2107\nhttps://orcid.org/0000-0003-4460-2241\nhttps://orcid.org/0000-0001-7510-6617\nhttps://orcid.org/0000-0003-2369-9507\nhttps://orcid.org/0000-0001-9457-8302\nhttps://orcid.org/0000-0003-0352-6561\nhttps://orcid.org/0000-0001-8521-737X\nhttps://orcid.org/0000-0002-6469-3200\nhttps://orcid.org/0000-0002-0662-5904\nhttps://orcid.org/0009-0000-7307-6311\nhttps://orcid.org/0000-0002-6351-6122\nhttps://orcid.org/0000-0001-6423-9799\nhttps://orcid.org/0000-0002-6957-1077\nhttps://orcid.org/0000-0002-4624-2019\nhttps://orcid.org/0000-0003-2025-2742\nhttps://orcid.org/0000-0002-5374-6995\nhttps://orcid.org/0000-0001-8310-8911\nhttps://orcid.org/0000-0002-2029-024X\nhttps://orcid.org/0000-0003-4461-8905\nhttps://orcid.org/0000-0003-1041-7099\nhttps://orcid.org/0000-0002-7068-4327\nhttps://orcid.org/0000-0002-7590-3058\nhttps://orcid.org/0000-0002-8604-3452\nhttps://orcid.org/0000-0001-9594-6277\nhttps://orcid.org/0000-0002-4184-9380\nhttps://orcid.org/0000-0003-1371-8575\nhttps://orcid.org/0000-0003-0890-8948\nhttps://orcid.org/0000-0002-4108-8681\nhttps://orcid.org/0000-0002-7857-7403\nhttps://orcid.org/0000-0002-8153-8464\nhttps://orcid.org/0000-0002-2614-5860\nhttps://orcid.org/0000-0001-8944-9629\nhttps://orcid.org/0000-0002-6426-0560\nhttps://orcid.org/0000-0001-5921-5231\nhttps://orcid.org/0000-0002-7791-894X\nhttps://orcid.org/0000-0002-6982-6121\nhttps://orcid.org/0000-0002-9552-1006\nhttps://orcid.org/0000-0001-5314-7581\nhttps://orcid.org/0000-0001-9835-4349\nhttps://orcid.org/0000-0002-2729-6273\nhttps://orcid.org/0000-0003-2719-5779\nhttps://orcid.org/0000-0003-1218-2828\nhttps://orcid.org/0000-0001-7170-8944\nhttps://orcid.org/0009-0001-1326-3956\nhttps://orcid.org/0000-0003-3769-9081\nhttps://orcid.org/0009-0007-3858-6659\nhttps://orcid.org/0000-0002-1531-3478\nhttps://orcid.org/0000-0003-1145-6436\nhttps://orcid.org/0009-0000-0389-8571\nhttps://orcid.org/0000-0003-1539-923X\nhttps://orcid.org/0000-0002-5990-4245\nhttps://orcid.org/0000-0002-6158-2468\nhttps://orcid.org/0000-0003-3110-0701\nhttps://orcid.org/0000-0002-5963-0467\nhttps://orcid.org/0000-0003-2695-7719\nhttps://orcid.org/0000-0002-9781-4873\nhttps://orcid.org/0000-0001-8258-5863\nhttps://orcid.org/0000-0001-8664-1949\nhttps://orcid.org/0000-0002-0862-7348\nhttps://orcid.org/0000-0001-8946-655X\nhttps://orcid.org/0009-0004-3633-8967\nhttps://orcid.org/0000-0003-0658-9146\nhttps://orcid.org/0000-0002-9397-5231\nhttps://orcid.org/0000-0002-0783-6703\nhttps://orcid.org/0000-0003-3293-5305\nhttps://orcid.org/0000-0003-0175-5731\nhttps://orcid.org/0000-0002-7273-4009\nhttps://orcid.org/0000-0002-2180-7634\nhttps://orcid.org/0000-0002-3398-4531\nhttps://orcid.org/0000-0002-5879-6326\nhttps://orcid.org/0000-0003-0505-4908\nhttps://orcid.org/0000-0003-0262-3132\nhttps://orcid.org/0000-0001-6834-1176\nhttps://orcid.org/0000-0002-5076-7096\nhttps://orcid.org/0000-0001-8359-3734\nhttps://orcid.org/0000-0002-5621-7706\nhttps://orcid.org/0000-0002-2155-8260\nhttps://orcid.org/0000-0003-2445-1060\nhttps://orcid.org/0000-0002-1386-0232\nhttps://orcid.org/0009-0000-4634-0797\nhttps://orcid.org/0000-0002-0156-1251\nhttps://orcid.org/0000-0002-8200-9425\nhttps://orcid.org/0000-0003-2533-3402\nhttps://orcid.org/0000-0003-3303-6301\nhttps://orcid.org/0000-0003-2902-5597\nhttps://orcid.org/0000-0003-2076-5126\nhttps://orcid.org/0000-0003-1736-8795\nhttps://orcid.org/0000-0001-8800-0045\nhttps://orcid.org/0000-0002-2270-0492\nhttps://orcid.org/0000-0001-5912-6124\nhttps://orcid.org/0000-0003-4112-7457\nhttps://orcid.org/0000-0002-6108-4004\nhttps://orcid.org/0000-0002-8978-8177\nhttps://orcid.org/0000-0001-6250-8465\nhttps://orcid.org/0000-0002-4160-1844\nhttps://orcid.org/0000-0001-5349-3011\nhttps://orcid.org/0000-0001-9850-2030\nhttps://orcid.org/0000-0002-2602-0566\nhttps://orcid.org/0000-0002-2072-6082\nhttps://orcid.org/0000-0002-3895-717X\nhttps://orcid.org/0000-0002-6890-7624\nhttps://orcid.org/0000-0002-9838-8327\nhttps://orcid.org/0000-0002-2200-7516\nhttps://orcid.org/0000-0002-5189-146X\nhttps://orcid.org/0000-0002-1557-4424\nhttps://orcid.org/0000-0003-2328-677X\nhttps://orcid.org/0000-0001-9800-7822\nhttps://orcid.org/0000-0002-8752-1946\nhttps://orcid.org/0000-0002-4965-0747\nhttps://orcid.org/0000-0001-7887-1728\nhttps://orcid.org/0000-0002-0128-0871\nhttps://orcid.org/0000-0002-8597-9259\nhttps://orcid.org/0009-0002-8988-9987\nhttps://orcid.org/0000-0003-0964-1480\nhttps://orcid.org/0000-0003-3954-5131\nhttps://orcid.org/0000-0001-8172-7081\nhttps://orcid.org/0000-0002-9705-101X\nhttps://orcid.org/0000-0002-0117-7196\nhttps://orcid.org/0000-0003-2509-5731\nhttps://orcid.org/0000-0003-3091-7461\nhttps://orcid.org/0000-0003-0843-1641\nhttps://orcid.org/0000-0002-9740-1622\nhttps://orcid.org/0000-0001-5537-4518\nhttps://orcid.org/0000-0001-8145-6322\nhttps://orcid.org/0000-0001-5958-829X\nhttps://orcid.org/0000-0001-5822-3731\nhttps://orcid.org/0000-0001-9625-1987\nhttps://orcid.org/0000-0002-3100-7294\nhttps://orcid.org/0000-0002-9352-8140\nhttps://orcid.org/0000-0002-1277-9168\nhttps://orcid.org/0000-0002-6714-5787\nhttps://orcid.org/0000-0002-5139-0550\nhttps://orcid.org/0000-0002-5431-6989\nhttps://orcid.org/0000-0002-2078-8419\nhttps://orcid.org/0000-0002-6032-5857\nhttps://orcid.org/0000-0001-8703-6943\nhttps://orcid.org/0009-0008-4322-7682\nhttps://orcid.org/0000-0001-5115-5828\nhttps://orcid.org/0000-0002-2374-6433\nhttps://orcid.org/0000-0001-5230-0396\nhttps://orcid.org/0009-0000-7507-0570\nhttps://orcid.org/0009-0008-3430-7269\nhttps://orcid.org/0000-0003-4888-205X\nhttps://orcid.org/0000-0001-6875-9177\nhttps://orcid.org/0000-0002-9269-5772\nhttps://orcid.org/0000-0002-4805-8020\n\n\n33\n\nCornell University, Ithaca, New York, USA\nJ. Alexander , S. Bright-Thonney , X. Chen , D.J. Cranshaw , J. Fan , X. Fan ,\nD. Gadkari , S. Hogan , J. Monroy , J.R. Patterson , J. Reichert , M. Reid , A. Ryd ,\nJ. Thom , P. Wittich , R. Zou\n\nFermi National Accelerator Laboratory, Batavia, Illinois, USA\nM. Albrow , M. Alyari , G. Apollinari , A. Apresyan , L.A.T. Bauerdick , D. Berry ,\nJ. Berryhill , P.C. Bhat , K. Burkett , J.N. Butler , A. Canepa , G.B. Cerati ,\nH.W.K. Cheung , F. Chlebana , K.F. Di Petrillo , J. Dickinson , I. Dutta , V.D. Elvira ,\nY. Feng , J. Freeman , A. Gandrakota , Z. Gecse , L. Gray , D. Green, S. Grünendahl ,\nD. Guerrero , O. Gutsche , R.M. Harris , R. Heller , T.C. Herwig , J. Hirschauer ,\nL. Horyn , B. Jayatilaka , S. Jindariani , M. Johnson , U. Joshi , T. Klijnsma ,\nB. Klima , K.H.M. Kwok , S. Lammel , D. Lincoln , R. Lipton , T. Liu , C. Madrid ,\nK. Maeshima , C. Mantilla , D. Mason , P. McBride , P. Merkel , S. Mrenna ,\nS. Nahn , J. Ngadiuba , D. Noonan , S. Norberg, V. Papadimitriou , N. Pastika ,\nK. Pedro , C. Pena89 , F. Ravera , A. Reinsvold Hall90 , L. Ristori , E. Sexton-\nKennedy , N. Smith , A. Soha , L. Spiegel , J. Strait , L. Taylor , S. Tkaczyk ,\nN.V. Tran , L. Uplegger , E.W. Vaandering , I. Zoi\n\nUniversity of Florida, Gainesville, Florida, USA\nP. Avery , D. Bourilkov , L. Cadamuro , P. Chang , V. Cherepanov , R.D. Field,\nE. Koenig , M. Kolosova , J. Konigsberg , A. Korytov , E. Kuznetsova91 , K.H. Lo,\nK. Matchev , N. Menendez , G. Mitselmakher , A. Muthirakalayil Madhu , N. Rawal ,\nD. Rosenzweig , S. Rosenzweig , K. Shi , J. Wang , Z. Wu\n\nFlorida State University, Tallahassee, Florida, USA\nT. Adams , A. Askew , N. Bower , R. Habibullah , V. Hagopian , T. Kolberg ,\nG. Martinez, H. Prosper , O. Viazlo , M. Wulansatiti , R. Yohay , J. Zhang\n\nFlorida Institute of Technology, Melbourne, Florida, USA\nM.M. Baarmand , S. Butalla , T. Elkafrawy53 , M. Hohlmann , R. Kumar Verma ,\nM. Rahmani, F. Yumiceva\n\nUniversity of Illinois at Chicago (UIC), Chicago, Illinois, USA\nM.R. Adams , R. Cavanaugh , S. Dittmer , O. Evdokimov , C.E. Gerber , D.J. Hof-\nman , D. S. Lemos , A.H. Merrit , C. Mills , G. Oh , T. Roy , S. Rudrabhatla ,\nM.B. Tonjes , N. Varelas , X. Wang , Z. Ye , J. Yoo\n\nThe University of Iowa, Iowa City, Iowa, USA\nM. Alhusseini , K. Dilsiz92 , L. Emediato , G. Karaman , O.K. Köseyan , J.-P. Merlo,\nA. Mestvirishvili93 , J. Nachtman , O. Neogi, H. Ogul94 , Y. Onel , A. Penzo , C. Snyder,\nE. Tiras95\n\nJohns Hopkins University, Baltimore, Maryland, USA\nO. Amram , B. Blumenfeld , L. Corcodilos , J. Davis , A.V. Gritsan , S. Kyriacou ,\nP. Maksimovic , J. Roskes , S. Sekhar , M. Swartz , T.Á. Vámi\n\nThe University of Kansas, Lawrence, Kansas, USA\nA. Abreu , L.F. Alcerro Alcerro , J. Anguiano , P. Baringer , A. Bean , Z. Flowers ,\nJ. King , G. Krintiras , M. Lazarovits , C. Le Mahieu , C. Lindsey, J. Marquez ,\nN. Minafra , M. Murray , M. Nickel , C. Rogan , C. Royon , R. Salvatico ,\nS. Sanders , C. Smith , Q. Wang , G. Wilson\n\nKansas State University, Manhattan, Kansas, USA\n\nhttps://orcid.org/0000-0002-2046-342X\nhttps://orcid.org/0000-0003-1889-7824\nhttps://orcid.org/0000-0002-8157-1328\nhttps://orcid.org/0000-0002-7498-2129\nhttps://orcid.org/0009-0003-3728-9960\nhttps://orcid.org/0000-0003-2067-0127\nhttps://orcid.org/0000-0002-6625-8085\nhttps://orcid.org/0000-0003-3657-2281\nhttps://orcid.org/0000-0002-7394-4710\nhttps://orcid.org/0000-0002-3815-3649\nhttps://orcid.org/0000-0003-2110-8021\nhttps://orcid.org/0000-0001-7706-1416\nhttps://orcid.org/0000-0001-5849-1912\nhttps://orcid.org/0000-0002-4870-8468\nhttps://orcid.org/0000-0002-7401-2181\nhttps://orcid.org/0000-0002-0542-1264\nhttps://orcid.org/0000-0001-7329-4925\nhttps://orcid.org/0000-0001-9268-3360\nhttps://orcid.org/0000-0002-5212-5396\nhttps://orcid.org/0000-0002-6186-0130\nhttps://orcid.org/0000-0002-7170-9012\nhttps://orcid.org/0000-0002-5383-8320\nhttps://orcid.org/0000-0002-8124-3033\nhttps://orcid.org/0000-0003-3370-9246\nhttps://orcid.org/0000-0002-2284-4744\nhttps://orcid.org/0000-0002-0745-8618\nhttps://orcid.org/0000-0003-4045-3998\nhttps://orcid.org/0000-0003-3548-0262\nhttps://orcid.org/0000-0001-6389-9357\nhttps://orcid.org/0000-0002-8762-8559\nhttps://orcid.org/0000-0001-8001-4602\nhttps://orcid.org/0000-0001-5450-5328\nhttps://orcid.org/0000-0003-0953-4503\nhttps://orcid.org/0000-0003-4446-4395\nhttps://orcid.org/0000-0003-2812-338X\nhttps://orcid.org/0000-0002-3415-5671\nhttps://orcid.org/0000-0003-4860-3233\nhttps://orcid.org/0009-0009-6561-3418\nhttps://orcid.org/0000-0002-6408-4288\nhttps://orcid.org/0000-0002-4857-0294\nhttps://orcid.org/0000-0001-5552-5400\nhttps://orcid.org/0000-0002-8015-9622\nhttps://orcid.org/0000-0003-1461-3425\nhttps://orcid.org/0000-0002-7368-6723\nhttps://orcid.org/0000-0002-4280-6382\nhttps://orcid.org/0000-0002-8244-0805\nhttps://orcid.org/0000-0002-9512-4932\nhttps://orcid.org/0000-0001-7912-5612\nhttps://orcid.org/0009-0000-7046-6533\nhttps://orcid.org/0000-0001-7757-8458\nhttps://orcid.org/0000-0001-8375-0760\nhttps://orcid.org/0000-0003-1675-6040\nhttps://orcid.org/0000-0002-3691-7625\nhttps://orcid.org/0000-0002-8693-6146\nhttps://orcid.org/0000-0003-0027-635X\nhttps://orcid.org/0000-0002-0599-7407\nhttps://orcid.org/0000-0002-6665-7289\nhttps://orcid.org/0009-0007-6522-5605\nhttps://orcid.org/0000-0003-3301-2246\nhttps://orcid.org/0009-0000-2822-897X\nhttps://orcid.org/0000-0002-0177-5903\nhttps://orcid.org/0000-0002-0074-5390\nhttps://orcid.org/0000-0001-6159-7750\nhttps://orcid.org/0000-0003-4727-5442\nhttps://orcid.org/0000-0001-8731-160X\nhttps://orcid.org/0000-0002-8949-0178\nhttps://orcid.org/0000-0002-0055-2935\nhttps://orcid.org/0000-0002-3932-3769\nhttps://orcid.org/0000-0002-0690-7186\nhttps://orcid.org/0009-0006-0993-6245\nhttps://orcid.org/0000-0003-2260-9151\nhttps://orcid.org/0000-0002-4500-7930\nhttps://orcid.org/0000-0003-3632-0287\nhttps://orcid.org/0000-0003-1653-8553\nhttps://orcid.org/0000-0003-1950-2492\nhttps://orcid.org/0000-0001-9171-1980\nhttps://orcid.org/0000-0002-0324-3054\nhttps://orcid.org/0000-0002-5968-1192\nhttps://orcid.org/0000-0001-9672-1328\nhttps://orcid.org/0000-0002-7233-8348\nhttps://orcid.org/0000-0002-6584-2538\nhttps://orcid.org/0000-0001-7642-5185\nhttps://orcid.org/0000-0002-8440-6854\nhttps://orcid.org/0000-0002-9202-803X\nhttps://orcid.org/0000-0003-3207-6950\nhttps://orcid.org/0000-0002-5738-9446\nhttps://orcid.org/0000-0003-0609-627X\nhttps://orcid.org/0000-0003-0260-4935\nhttps://orcid.org/0000-0001-8789-610X\nhttps://orcid.org/0000-0002-2095-6320\nhttps://orcid.org/0000-0002-6748-4850\nhttps://orcid.org/0000-0002-0884-7922\nhttps://orcid.org/0000-0002-5838-2158\nhttps://orcid.org/0000-0001-6850-8765\nhttps://orcid.org/0000-0001-9239-3398\nhttps://orcid.org/0000-0002-5510-8305\nhttps://orcid.org/0000-0003-4182-9096\nhttps://orcid.org/0000-0002-3295-3194\nhttps://orcid.org/0000-0001-5745-3658\nhttps://orcid.org/0000-0003-1209-3032\nhttps://orcid.org/0000-0002-7734-3170\nhttps://orcid.org/0000-0002-3687-5189\nhttps://orcid.org/0000-0002-5613-1507\nhttps://orcid.org/0000-0002-2475-0055\nhttps://orcid.org/0000-0003-3879-4873\nhttps://orcid.org/0000-0003-2165-9501\nhttps://orcid.org/0000-0001-8049-5143\nhttps://orcid.org/0000-0002-7172-1396\nhttps://orcid.org/0000-0001-8775-0696\nhttps://orcid.org/0000-0002-3161-8300\nhttps://orcid.org/0000-0002-3791-1989\nhttps://orcid.org/0000-0002-0211-6109\nhttps://orcid.org/0000-0002-4077-2713\nhttps://orcid.org/0000-0002-2957-0301\nhttps://orcid.org/0000-0001-6794-3079\nhttps://orcid.org/0000-0002-0124-9065\nhttps://orcid.org/0000-0002-9792-8619\nhttps://orcid.org/0000-0003-3423-9581\nhttps://orcid.org/0000-0001-9930-6445\nhttps://orcid.org/0000-0003-4578-9319\nhttps://orcid.org/0000-0002-8264-156X\nhttps://orcid.org/0000-0003-2436-5074\nhttps://orcid.org/0000-0001-8493-3737\nhttps://orcid.org/0000-0001-7169-3420\nhttps://orcid.org/0000-0002-5359-9614\nhttps://orcid.org/0000-0002-1250-8931\nhttps://orcid.org/0000-0002-8116-9021\nhttps://orcid.org/0000-0002-2449-3845\nhttps://orcid.org/0000-0003-1982-8978\nhttps://orcid.org/0000-0003-3922-6464\nhttps://orcid.org/0000-0001-8035-4818\nhttps://orcid.org/0000-0003-0744-1063\nhttps://orcid.org/0000-0001-7299-7653\nhttps://orcid.org/0000-0002-7366-4225\nhttps://orcid.org/0000-0002-2617-9315\nhttps://orcid.org/0000-0002-9397-5514\nhttps://orcid.org/0000-0003-2792-8493\nhttps://orcid.org/0000-0001-6091-6772\nhttps://orcid.org/0000-0002-3826-1332\nhttps://orcid.org/0000-0002-9239-470X\nhttps://orcid.org/0000-0003-0138-3368\nhttps://orcid.org/0000-0002-3021-5032\nhttps://orcid.org/0000-0001-8739-9648\nhttps://orcid.org/0000-0001-9040-3468\nhttps://orcid.org/0000-0002-8591-5247\nhttps://orcid.org/0000-0003-3951-3420\nhttps://orcid.org/0000-0002-5121-2893\nhttps://orcid.org/0000-0002-8141-7769\nhttps://orcid.org/0000-0003-3436-047X\nhttps://orcid.org/0000-0002-5628-7464\nhttps://orcid.org/0000-0002-3765-3123\nhttps://orcid.org/0000-0003-1150-1735\nhttps://orcid.org/0000-0001-6751-3108\nhttps://orcid.org/0000-0001-6488-6195\nhttps://orcid.org/0000-0002-3545-7970\nhttps://orcid.org/0000-0002-9254-4368\nhttps://orcid.org/0000-0002-2358-2168\nhttps://orcid.org/0000-0001-8761-0490\nhttps://orcid.org/0000-0002-8307-7518\nhttps://orcid.org/0000-0002-0286-5070\nhttps://orcid.org/0000-0002-0959-9211\nhttps://orcid.org/0000-0002-9000-2215\nhttps://orcid.org/0000-0001-5770-5077\nhttps://orcid.org/0000-0002-7349-350X\nhttps://orcid.org/0000-0002-3691-8388\nhttps://orcid.org/0000-0001-5967-8674\nhttps://orcid.org/0000-0001-8314-2052\nhttps://orcid.org/0000-0001-9652-9854\nhttps://orcid.org/0000-0002-0380-7577\nhttps://orcid.org/0000-0002-5565-3119\nhttps://orcid.org/0000-0001-5924-1130\nhttps://orcid.org/0000-0003-3887-4048\nhttps://orcid.org/0000-0003-4002-1888\nhttps://orcid.org/0000-0001-7219-4818\nhttps://orcid.org/0000-0003-0419-1329\nhttps://orcid.org/0000-0002-4166-4503\nhttps://orcid.org/0000-0002-7672-9709\nhttps://orcid.org/0000-0002-2751-0567\nhttps://orcid.org/0000-0002-9491-6022\nhttps://orcid.org/0000-0003-0505-0528\nhttps://orcid.org/0000-0003-3804-3244\nhttps://orcid.org/0000-0003-0917-4763\n\n\n34\n\nB. Allmond , S. Duric, A. Ivanov , K. Kaadze , A. Kalogeropoulos , D. Kim,\nY. Maravin , T. Mitchell, A. Modak, K. Nam, D. Roy\n\nLawrence Livermore National Laboratory, Livermore, California, USA\nF. Rebassoo , D. Wright\n\nUniversity of Maryland, College Park, Maryland, USA\nE. Adams , A. Baden , O. Baron, A. Belloni , A. Bethani , Y.m. Chen , S.C. Eno ,\nN.J. Hadley , S. Jabeen , R.G. Kellogg , T. Koeth , Y. Lai , S. Lascio , A.C. Mignerey ,\nS. Nabili , C. Palmer , C. Papageorgakis , L. Wang , K. Wong\n\nMassachusetts Institute of Technology, Cambridge, Massachusetts, USA\nJ. Bendavid , W. Busza , I.A. Cali , Y. Chen , M. D’Alfonso , J. Eysermans ,\nC. Freer , G. Gomez-Ceballos , M. Goncharov, P. Harris, D. Kovalskyi , J. Krupa , Y.-\nJ. Lee , K. Long , C. Mironov , C. Paus , D. Rankin , C. Roland , G. Roland ,\nZ. Shi , G.S.F. Stephans , J. Wang, Z. Wang , B. Wyslouch , T. J. Yang\n\nUniversity of Minnesota, Minneapolis, Minnesota, USA\nR.M. Chatterjee, B. Crossman , J. Hiltbrand , B.M. Joshi , C. Kapsiak , M. Krohn ,\nY. Kubota , D. Mahon , J. Mans , M. Revering , R. Rusack , R. Saradhy ,\nN. Schroeder , N. Strobbe , M.A. Wadud\n\nUniversity of Mississippi, Oxford, Mississippi, USA\nL.M. Cremaldi\n\nUniversity of Nebraska-Lincoln, Lincoln, Nebraska, USA\nK. Bloom , M. Bryson, D.R. Claes , C. Fangmeier , F. Golf , C. Joo , I. Kravchenko ,\nI. Reed , J.E. Siado , G.R. Snow†, W. Tabb , A. Wightman , F. Yan , A.G. Zecchinelli\n\nState University of New York at Buffalo, Buffalo, New York, USA\nG. Agarwal , H. Bandyopadhyay , L. Hay , I. Iashvili , A. Kharchilava , C. McLean ,\nM. Morris , D. Nguyen , J. Pekkanen , S. Rappoccio , H. Rejeb Sfar, A. Williams\n\nNortheastern University, Boston, Massachusetts, USA\nG. Alverson , E. Barberis , Y. Haddad , Y. Han , A. Krishna , J. Li , J. Lidrych ,\nG. Madigan , B. Marzocchi , D.M. Morse , V. Nguyen , T. Orimoto , A. Parker ,\nL. Skinnari , A. Tishelman-Charny , T. Wamorkar , B. Wang , A. Wisecarver ,\nD. Wood\n\nNorthwestern University, Evanston, Illinois, USA\nS. Bhattacharya , J. Bueghly, Z. Chen , A. Gilbert , K.A. Hahn , Y. Liu , N. Odell ,\nM.H. Schmitt , M. Velasco\n\nUniversity of Notre Dame, Notre Dame, Indiana, USA\nR. Band , R. Bucci, M. Cremonesi, A. Das , R. Goldouzian , M. Hildreth ,\nK. Hurtado Anampa , C. Jessop , K. Lannon , J. Lawrence , N. Loukas , L. Lutton ,\nJ. Mariano, N. Marinelli, I. Mcalister, T. McCauley , C. Mcgrady , K. Mohrman ,\nC. Moore , Y. Musienko12 , R. Ruchti , A. Townsend , M. Wayne , H. Yockey,\nM. Zarucki , L. Zygala\n\nThe Ohio State University, Columbus, Ohio, USA\nB. Bylsma, M. Carrigan , L.S. Durkin , C. Hill , M. Joyce , A. Lesauvage ,\nM. Nunez Ornelas , K. Wei, B.L. Winer , B. R. Yates\n\nPrinceton University, Princeton, New Jersey, USA\n\nhttps://orcid.org/0000-0002-5593-7736\nhttps://orcid.org/0000-0002-9270-5643\nhttps://orcid.org/0000-0003-0571-163X\nhttps://orcid.org/0000-0003-3444-0314\nhttps://orcid.org/0000-0002-9449-0666\nhttps://orcid.org/0000-0002-8659-7762\nhttps://orcid.org/0000-0001-8934-9329\nhttps://orcid.org/0000-0002-3586-3354\nhttps://orcid.org/0000-0003-2809-2683\nhttps://orcid.org/0000-0002-6159-3861\nhttps://orcid.org/0000-0002-1727-656X\nhttps://orcid.org/0000-0002-8150-7043\nhttps://orcid.org/0000-0002-5795-4783\nhttps://orcid.org/0000-0003-4282-2515\nhttps://orcid.org/0000-0002-1209-6471\nhttps://orcid.org/0000-0002-0155-7383\nhttps://orcid.org/0000-0001-9235-521X\nhttps://orcid.org/0000-0002-0082-0514\nhttps://orcid.org/0000-0002-7795-8693\nhttps://orcid.org/0000-0001-8579-5874\nhttps://orcid.org/0000-0001-5164-6969\nhttps://orcid.org/0000-0002-6893-1018\nhttps://orcid.org/0000-0002-5801-5737\nhttps://orcid.org/0000-0003-4548-0346\nhttps://orcid.org/0000-0003-3443-0626\nhttps://orcid.org/0000-0002-9698-1354\nhttps://orcid.org/0000-0002-7907-1789\nhttps://orcid.org/0000-0002-3831-9071\nhttps://orcid.org/0000-0002-2822-3375\nhttps://orcid.org/0000-0003-2582-6469\nhttps://orcid.org/0000-0002-7409-7904\nhttps://orcid.org/0000-0001-6483-7123\nhttps://orcid.org/0000-0002-7967-4635\nhttps://orcid.org/0000-0003-1683-9460\nhttps://orcid.org/0000-0002-6923-293X\nhttps://orcid.org/0000-0003-0785-7552\nhttps://orcid.org/0000-0003-2593-7767\nhttps://orcid.org/0000-0003-0664-1653\nhttps://orcid.org/0000-0002-8599-2437\nhttps://orcid.org/0000-0002-6047-4211\nhttps://orcid.org/0000-0001-8411-9620\nhttps://orcid.org/0000-0002-7312-5854\nhttps://orcid.org/0000-0001-8983-2169\nhttps://orcid.org/0000-0001-5498-8825\nhttps://orcid.org/0000-0003-3106-4894\nhttps://orcid.org/0000-0002-3074-3767\nhttps://orcid.org/0000-0003-3681-0649\nhttps://orcid.org/0000-0003-4317-4660\nhttps://orcid.org/0000-0002-2700-5085\nhttps://orcid.org/0000-0003-1691-5937\nhttps://orcid.org/0000-0002-4723-0968\nhttps://orcid.org/0009-0008-7743-5316\nhttps://orcid.org/0000-0002-1711-2506\nhttps://orcid.org/0000-0001-6146-4827\nhttps://orcid.org/0000-0002-2640-5941\nhttps://orcid.org/0000-0003-2840-1087\nhttps://orcid.org/0000-0001-5051-0293\nhttps://orcid.org/0000-0002-7633-749X\nhttps://orcid.org/0000-0001-8720-293X\nhttps://orcid.org/0000-0002-8336-6141\nhttps://orcid.org/0000-0001-8835-8282\nhttps://orcid.org/0000-0002-0653-0761\nhttps://orcid.org/0000-0001-5550-7827\nhttps://orcid.org/0000-0002-4272-8900\nhttps://orcid.org/0000-0003-4198-8919\nhttps://orcid.org/0000-0002-5998-8047\nhttps://orcid.org/0000-0003-3567-9351\nhttps://orcid.org/0000-0002-5661-4330\nhttps://orcid.org/0000-0003-0068-0395\nhttps://orcid.org/0000-0002-1823-8856\nhttps://orcid.org/0000-0002-9757-470X\nhttps://orcid.org/0000-0002-9542-4847\nhttps://orcid.org/0000-0001-6651-5320\nhttps://orcid.org/0000-0002-4042-0785\nhttps://orcid.org/0000-0001-8986-278X\nhttps://orcid.org/0000-0002-2593-5297\nhttps://orcid.org/0000-0001-9726-4915\nhttps://orcid.org/0000-0002-7086-7641\nhttps://orcid.org/0000-0003-1948-5901\nhttps://orcid.org/0000-0002-3913-0326\nhttps://orcid.org/0000-0002-7450-4805\nhttps://orcid.org/0000-0002-2830-6488\nhttps://orcid.org/0000-0002-5185-8504\nhttps://orcid.org/0000-0002-6681-7668\nhttps://orcid.org/0000-0002-5449-2560\nhttps://orcid.org/0000-0003-4055-6532\nhttps://orcid.org/0000-0001-6651-1178\nhttps://orcid.org/0000-0002-6417-5913\nhttps://orcid.org/0000-0003-4916-7752\nhttps://orcid.org/0000-0002-3510-6505\nhttps://orcid.org/0000-0002-4319-818X\nhttps://orcid.org/0000-0001-5245-2074\nhttps://orcid.org/0000-0003-1439-0196\nhttps://orcid.org/0000-0001-8796-5865\nhttps://orcid.org/0000-0001-6687-6214\nhttps://orcid.org/0000-0003-3163-2169\nhttps://orcid.org/0000-0003-1278-9208\nhttps://orcid.org/0000-0002-8388-3341\nhttps://orcid.org/0000-0002-9421-3335\nhttps://orcid.org/0000-0002-2019-6755\nhttps://orcid.org/0000-0002-7332-5098\nhttps://orcid.org/0000-0001-5551-5456\nhttps://orcid.org/0000-0003-0796-2475\nhttps://orcid.org/0009-0004-1608-2001\nhttps://orcid.org/0000-0002-6477-801X\nhttps://orcid.org/0000-0002-0526-6161\nhttps://orcid.org/0000-0003-4521-6086\nhttps://orcid.org/0000-0001-7560-5790\nhttps://orcid.org/0000-0001-7892-1676\nhttps://orcid.org/0000-0002-5588-1760\nhttps://orcid.org/0000-0001-7155-0665\nhttps://orcid.org/0000-0003-0814-3578\nhttps://orcid.org/0000-0003-4873-0523\nhttps://orcid.org/0000-0001-9115-9698\nhttps://orcid.org/0000-0002-0295-249X\nhttps://orcid.org/0000-0002-4454-3934\nhttps://orcid.org/0000-0002-9779-3566\nhttps://orcid.org/0000-0002-6885-3611\nhttps://orcid.org/0000-0002-9706-0098\nhttps://orcid.org/0000-0001-6326-7210\nhttps://orcid.org/0000-0003-0049-6918\nhttps://orcid.org/0000-0002-3212-4505\nhttps://orcid.org/0000-0001-6589-8286\nhttps://orcid.org/0000-0002-8821-2045\nhttps://orcid.org/0009-0007-2940-0496\nhttps://orcid.org/0000-0002-8140-4183\nhttps://orcid.org/0009-0006-3545-1938\nhttps://orcid.org/0000-0002-3151-1386\nhttps://orcid.org/0000-0002-3696-689X\nhttps://orcid.org/0000-0001-8204-6157\nhttps://orcid.org/0000-0003-1510-5772\nhttps://orcid.org/0000-0001-9665-7282\nhttps://orcid.org/0000-0003-0538-5854\nhttps://orcid.org/0000-0002-0477-1051\nhttps://orcid.org/0000-0003-0059-0779\nhttps://orcid.org/0000-0003-1112-5880\nhttps://orcid.org/0000-0003-3437-7845\nhttps://orcid.org/0000-0003-2663-7379\nhttps://orcid.org/0000-0001-9980-4698\nhttps://orcid.org/0000-0001-7366-1318\n\n\n35\n\nF.M. Addesa , H. Bouchamaoui , P. Das , G. Dezoort , P. Elmer , A. Frankenthal ,\nB. Greenberg , N. Haubrich , S. Higginbotham , G. Kopp , S. Kwan , D. Lange ,\nA. Loeliger , D. Marlow , I. Ojalvo , J. Olsen , D. Stickland , C. Tully\n\nUniversity of Puerto Rico, Mayaguez, Puerto Rico, USA\nS. Malik\n\nPurdue University, West Lafayette, Indiana, USA\nA.S. Bakshi , V.E. Barnes , R. Chawla , S. Das , L. Gutay, M. Jones , A.W. Jung ,\nD. Kondratyev , A.M. Koshy, M. Liu , G. Negro , N. Neumeister , G. Paspalaki ,\nS. Piperov , A. Purohit , J.F. Schulte , M. Stojanovic15 , J. Thieman , A. K. Virdi ,\nF. Wang , R. Xiao , W. Xie\n\nPurdue University Northwest, Hammond, Indiana, USA\nJ. Dolen , N. Parashar\n\nRice University, Houston, Texas, USA\nD. Acosta , A. Baty , T. Carnahan , S. Dildick , K.M. Ecklund , P.J. Fernández Man-\nteca , S. Freed, P. Gardner, F.J.M. Geurts , A. Kumar , W. Li , B.P. Padley , R. Redjimi,\nJ. Rotter , S. Yang , E. Yigitbasi , Y. Zhang\n\nUniversity of Rochester, Rochester, New York, USA\nA. Bodek , P. de Barbaro , R. Demina , J.L. Dulemba , C. Fallon, A. Garcia-\nBellido , O. Hindrichs , A. Khukhunaishvili , P. Parygin , E. Popova , R. Taus ,\nG.P. Van Onsem\n\nThe Rockefeller University, New York, New York, USA\nK. Goulianos\n\nRutgers, The State University of New Jersey, Piscataway, New Jersey, USA\nB. Chiarito, J.P. Chou , Y. Gershtein , E. Halkiadakis , A. Hart , M. Heindl ,\nD. Jaroslawski , O. Karacheban25 , I. Laflotte , A. Lath , R. Montalvo, K. Nash,\nM. Osherson , H. Routray , S. Salur , S. Schnetzer, S. Somalwar , R. Stone ,\nS.A. Thayil , S. Thomas, H. Wang\n\nUniversity of Tennessee, Knoxville, Tennessee, USA\nH. Acharya, A.G. Delannoy , S. Fiorendi , T. Holmes , E. Nibigira , S. Spanier\n\nTexas A&M University, College Station, Texas, USA\nM. Ahmad , O. Bouhali96 , M. Dalchenko , A. Delgado , R. Eusebi , J. Gilmore ,\nT. Huang , T. Kamon97 , H. Kim , S. Luo , S. Malhotra, R. Mueller , D. Overton ,\nD. Rathjens , A. Safonov\n\nTexas Tech University, Lubbock, Texas, USA\nN. Akchurin , J. Damgov , V. Hegde , K. Lamichhane , S.W. Lee , T. Mengke,\nS. Muthumuni , T. Peltola , I. Volobouev , A. Whitbeck\n\nVanderbilt University, Nashville, Tennessee, USA\nE. Appelt , S. Greene, A. Gurrola , W. Johns , R. Kunnawalkam Elayavalli , A. Melo ,\nF. Romeo , P. Sheldon , S. Tuo , J. Velkovska , J. Viinikainen\n\nUniversity of Virginia, Charlottesville, Virginia, USA\nB. Cardwell , B. Cox , G. Cummings , J. Hakala , R. Hirosky , A. Ledovskoy ,\nA. Li , C. Neu , C.E. Perez Lara\n\nWayne State University, Detroit, Michigan, USA\n\nhttps://orcid.org/0000-0003-0484-5804\nhttps://orcid.org/0000-0002-9776-1935\nhttps://orcid.org/0000-0002-9770-1377\nhttps://orcid.org/0000-0002-5890-0445\nhttps://orcid.org/0000-0001-6830-3356\nhttps://orcid.org/0000-0002-2583-5982\nhttps://orcid.org/0000-0002-4922-1934\nhttps://orcid.org/0000-0002-7625-8169\nhttps://orcid.org/0000-0002-4436-5461\nhttps://orcid.org/0000-0001-8160-0208\nhttps://orcid.org/0000-0002-5308-7707\nhttps://orcid.org/0000-0002-9086-5184\nhttps://orcid.org/0000-0002-5017-1487\nhttps://orcid.org/0000-0002-6395-1079\nhttps://orcid.org/0000-0003-1455-6272\nhttps://orcid.org/0000-0002-9361-5762\nhttps://orcid.org/0000-0003-4702-8820\nhttps://orcid.org/0000-0001-6771-2174\nhttps://orcid.org/0000-0002-6356-2655\nhttps://orcid.org/0000-0002-2857-6883\nhttps://orcid.org/0000-0001-6939-3445\nhttps://orcid.org/0000-0003-4802-6819\nhttps://orcid.org/0000-0001-6701-9265\nhttps://orcid.org/0000-0002-9951-4583\nhttps://orcid.org/0000-0003-3068-3212\nhttps://orcid.org/0000-0002-7874-2480\nhttps://orcid.org/0000-0001-9012-395X\nhttps://orcid.org/0000-0002-1418-2154\nhttps://orcid.org/0000-0003-2356-1700\nhttps://orcid.org/0000-0001-6815-1065\nhttps://orcid.org/0000-0002-9266-7819\nhttps://orcid.org/0000-0003-0881-612X\nhttps://orcid.org/0000-0003-4421-680X\nhttps://orcid.org/0000-0002-1542-0855\nhttps://orcid.org/0000-0001-7684-6588\nhttps://orcid.org/0000-0002-0866-8932\nhttps://orcid.org/0000-0002-8313-0809\nhttps://orcid.org/0000-0001-7292-8527\nhttps://orcid.org/0000-0003-1430-9191\nhttps://orcid.org/0000-0003-1141-3823\nhttps://orcid.org/0009-0009-1717-0413\nhttps://orcid.org/0000-0001-5367-1738\nhttps://orcid.org/0000-0001-5310-3466\nhttps://orcid.org/0000-0001-7492-3201\nhttps://orcid.org/0000-0003-0554-4755\nhttps://orcid.org/0000-0002-6976-4637\nhttps://orcid.org/0000-0003-2566-7496\nhttps://orcid.org/0000-0003-2856-9090\nhttps://orcid.org/0000-0002-5180-6595\nhttps://orcid.org/0000-0003-4136-3409\nhttps://orcid.org/0000-0002-3572-5701\nhttps://orcid.org/0009-0009-4040-7407\nhttps://orcid.org/0000-0002-2075-8631\nhttps://orcid.org/0000-0002-9595-2623\nhttps://orcid.org/0000-0002-6812-761X\nhttps://orcid.org/0000-0003-0409-0341\nhttps://orcid.org/0000-0002-5508-1827\nhttps://orcid.org/0000-0002-7852-167X\nhttps://orcid.org/0000-0002-9842-7015\nhttps://orcid.org/0000-0002-1407-1972\nhttps://orcid.org/0000-0001-7640-5264\nhttps://orcid.org/0000-0002-3834-1316\nhttps://orcid.org/0000-0001-6743-3781\nhttps://orcid.org/0000-0001-7556-8969\nhttps://orcid.org/0000-0002-5168-2932\nhttps://orcid.org/0000-0002-1664-2337\nhttps://orcid.org/0000-0002-6230-9535\nhttps://orcid.org/0000-0001-6315-905X\nhttps://orcid.org/0000-0002-4871-5449\nhttps://orcid.org/0000-0002-3584-7856\nhttps://orcid.org/0000-0003-2349-6582\nhttps://orcid.org/0000-0002-2831-463X\nhttps://orcid.org/0000-0003-2497-1242\nhttps://orcid.org/0000-0002-2785-3762\nhttps://orcid.org/0000-0002-7366-8090\nhttps://orcid.org/0000-0003-0228-9760\nhttps://orcid.org/0000-0002-9760-9976\nhttps://orcid.org/0000-0002-9694-4625\nhttps://orcid.org/0000-0002-4995-9285\nhttps://orcid.org/0000-0002-8856-7401\nhttps://orcid.org/0000-0001-6229-695X\nhttps://orcid.org/0000-0002-1469-0335\nhttps://orcid.org/0000-0002-3027-0752\nhttps://orcid.org/0000-0003-1252-6213\nhttps://orcid.org/0000-0003-3273-9419\nhttps://orcid.org/0000-0002-3959-5174\nhttps://orcid.org/0000-0001-5821-291X\nhttps://orcid.org/0000-0002-7049-4646\nhttps://orcid.org/0000-0001-9933-995X\nhttps://orcid.org/0000-0001-7139-7322\nhttps://orcid.org/0000-0002-0137-136X\nhttps://orcid.org/0000-0003-3453-7204\nhttps://orcid.org/0000-0003-3322-6287\nhttps://orcid.org/0000-0001-9911-0143\nhttps://orcid.org/0000-0002-0793-5664\nhttps://orcid.org/0000-0001-5565-7868\nhttps://orcid.org/0000-0003-4986-1728\nhttps://orcid.org/0000-0003-3122-4245\nhttps://orcid.org/0000-0002-6723-6689\nhttps://orcid.org/0009-0009-0648-8151\nhttps://orcid.org/0000-0002-8420-1488\nhttps://orcid.org/0000-0001-9497-5471\nhttps://orcid.org/0000-0002-6127-4350\nhttps://orcid.org/0000-0003-3863-2567\nhttps://orcid.org/0000-0003-4952-2873\nhttps://orcid.org/0000-0003-0152-7683\nhttps://orcid.org/0000-0002-3388-8339\nhttps://orcid.org/0000-0003-0432-6895\nhttps://orcid.org/0000-0002-4732-4008\nhttps://orcid.org/0000-0002-2087-6128\nhttps://orcid.org/0000-0003-4224-5164\nhttps://orcid.org/0000-0003-3389-4584\nhttps://orcid.org/0000-0002-2793-4052\nhttps://orcid.org/0000-0001-5291-8903\nhttps://orcid.org/0000-0002-9202-1516\nhttps://orcid.org/0000-0003-3473-8858\nhttps://orcid.org/0000-0002-1297-6065\nhttps://orcid.org/0000-0003-1550-5223\nhttps://orcid.org/0000-0001-6142-0429\nhttps://orcid.org/0000-0003-1423-5241\nhttps://orcid.org/0000-0003-2530-4265\nhttps://orcid.org/0000-0001-5553-0891\nhttps://orcid.org/0000-0003-3752-4759\nhttps://orcid.org/0000-0002-8045-7806\nhttps://orcid.org/0000-0001-9586-3316\nhttps://orcid.org/0000-0003-0304-6330\nhttps://orcid.org/0000-0003-4861-0943\nhttps://orcid.org/0000-0002-4547-116X\nhttps://orcid.org/0000-0003-3644-8627\nhttps://orcid.org/0000-0003-0199-8864\n\n\n36\n\nP.E. Karchin\n\nUniversity of Wisconsin - Madison, Madison, Wisconsin, USA\nA. Aravind, S. Banerjee , K. Black , T. Bose , S. Dasu , I. De Bruyn , P. Everaerts ,\nC. Galloni, H. He , M. Herndon , A. Herve , C.K. Koraka , A. Lanaro, R. Loveless ,\nJ. Madhusudanan Sreekala , A. Mallampalli , A. Mohammadi , S. Mondal, G. Parida ,\nD. Pinna, A. Savin, V. Shang , V. Sharma , W.H. Smith , D. Teague, H.F. Tsoi ,\nW. Vetens , A. Warden\n\nAuthors affiliated with an institute or an international laboratory covered by a cooperation\nagreement with CERN\nS. Afanasiev , V. Andreev , Yu. Andreev , T. Aushev , M. Azarkin , A. Babaev ,\nA. Belyaev , V. Blinov98, E. Boos , V. Borshch , D. Budkouski , V. Bunichev ,\nM. Chadeeva98 , V. Chekhovsky, M. Danilov98 , A. Dermenev , T. Dimova98 ,\nI. Dremin , M. Dubinin89 , L. Dudko , A. Ershov , G. Gavrilov , V. Gavrilov ,\nS. Gninenko , V. Golovtcov , N. Golubev , I. Golutvin , I. Gorbunov , Y. Ivanov ,\nV. Kachanov , L. Kardapoltsev98 , V. Karjavine , A. Karneyeu , V. Kim98 , M. Ki-\nrakosyan, D. Kirpichnikov , M. Kirsanov , V. Klyukhin , O. Kodolova99 , D. Konstanti-\nnov , V. Korenkov , A. Kozyrev98 , N. Krasnikov , A. Lanev , P. Levchenko100 ,\nA. Litomin, N. Lychkovskaya , V. Makarenko , A. Malakhov , V. Matveev98,101 ,\nV. Murzin , A. Nikitenko102,99 , S. Obraztsov , I. Ovtin98 , V. Palichik , V. Perelygin ,\nM. Perfilov, S. Petrushanko , S. Polikarpov98 , V. Popov, O. Radchenko98 , M. Savina ,\nV. Savrin , D. Selivanova , V. Shalaev , S. Shmatov , S. Shulha , Y. Skovpen98 ,\nS. Slabospitskii , V. Smirnov , D. Sosnov , V. Sulimov , E. Tcherniaev , A. Terkulov ,\nO. Teryaev , I. Tlisova , A. Toropin , L. Uvarov , A. Uzunian , A. Vorobyev†,\nN. Voytishin , B.S. Yuldashev103, A. Zarubin , I. Zhizhin , A. Zhokin\n\n†: Deceased\n1Also at Yerevan State University, Yerevan, Armenia\n2Also at TU Wien, Vienna, Austria\n3Also at Institute of Basic and Applied Sciences, Faculty of Engineering, Arab Academy for\nScience, Technology and Maritime Transport, Alexandria, Egypt\n4Also at Université Libre de Bruxelles, Bruxelles, Belgium\n5Also at Universidade Estadual de Campinas, Campinas, Brazil\n6Also at Federal University of Rio Grande do Sul, Porto Alegre, Brazil\n7Also at UFMS, Nova Andradina, Brazil\n8Also at University of Chinese Academy of Sciences, Beijing, China\n9Also at Nanjing Normal University Department of Physics, Nanjing, China\n10Now at The University of Iowa, Iowa City, Iowa, USA\n11Also at University of Chinese Academy of Sciences, Beijing, China\n12Also at an institute or an international laboratory covered by a cooperation agreement with\nCERN\n13Also at Suez University, Suez, Egypt\n14Now at British University in Egypt, Cairo, Egypt\n15Also at Purdue University, West Lafayette, Indiana, USA\n16Also at Université de Haute Alsace, Mulhouse, France\n17Also at Department of Physics, Tsinghua University, Beijing, China\n18Also at Tbilisi State University, Tbilisi, Georgia\n19Also at The University of the State of Amazonas, Manaus, Brazil\n20Also at Erzincan Binali Yildirim University, Erzincan, Turkey\n21Also at University of Hamburg, Hamburg, Germany\n\nhttps://orcid.org/0000-0003-1284-3470\nhttps://orcid.org/0000-0001-7880-922X\nhttps://orcid.org/0000-0001-7320-5080\nhttps://orcid.org/0000-0001-8026-5380\nhttps://orcid.org/0000-0001-5993-9045\nhttps://orcid.org/0000-0003-1704-4360\nhttps://orcid.org/0000-0003-3848-324X\nhttps://orcid.org/0009-0008-3906-2037\nhttps://orcid.org/0000-0003-3043-1090\nhttps://orcid.org/0000-0002-1959-2363\nhttps://orcid.org/0000-0002-4548-9992\nhttps://orcid.org/0000-0002-2562-4405\nhttps://orcid.org/0000-0003-2590-763X\nhttps://orcid.org/0000-0002-3793-8516\nhttps://orcid.org/0000-0001-8152-927X\nhttps://orcid.org/0000-0001-9665-4575\nhttps://orcid.org/0000-0002-1436-6092\nhttps://orcid.org/0000-0003-1287-1471\nhttps://orcid.org/0000-0003-3195-0909\nhttps://orcid.org/0000-0002-2550-2184\nhttps://orcid.org/0000-0003-1058-1163\nhttps://orcid.org/0000-0001-7463-7360\nhttps://orcid.org/0009-0006-8766-226X\nhttps://orcid.org/0000-0002-5492-6920\nhttps://orcid.org/0000-0002-7397-9665\nhttps://orcid.org/0000-0002-6347-7055\nhttps://orcid.org/0000-0002-7448-1447\nhttps://orcid.org/0000-0001-8876-3886\nhttps://orcid.org/0000-0003-1692-1173\nhttps://orcid.org/0000-0002-0193-5073\nhttps://orcid.org/0000-0002-5479-1982\nhttps://orcid.org/0000-0002-2029-1007\nhttps://orcid.org/0000-0003-4418-2072\nhttps://orcid.org/0000-0003-1814-1218\nhttps://orcid.org/0000-0001-9227-5164\nhttps://orcid.org/0000-0001-5619-376X\nhttps://orcid.org/0000-0002-9560-0660\nhttps://orcid.org/0000-0001-7451-247X\nhttps://orcid.org/0000-0002-7766-7175\nhttps://orcid.org/0000-0002-4462-3192\nhttps://orcid.org/0000-0001-5779-142X\nhttps://orcid.org/0000-0001-9689-7999\nhttps://orcid.org/0000-0002-9617-2928\nhttps://orcid.org/0000-0001-6495-7619\nhttps://orcid.org/0000-0002-0595-0297\nhttps://orcid.org/0000-0002-9504-7754\nhttps://orcid.org/0009-0007-6508-0215\nhttps://orcid.org/0000-0003-3777-6606\nhttps://orcid.org/0000-0001-5163-7632\nhttps://orcid.org/0000-0002-3062-010X\nhttps://orcid.org/0009-0000-3501-9607\nhttps://orcid.org/0000-0002-5326-3854\nhttps://orcid.org/0000-0001-9983-1004\nhttps://orcid.org/0000-0001-7161-2133\nhttps://orcid.org/0000-0002-7177-077X\nhttps://orcid.org/0000-0002-8879-6538\nhttps://orcid.org/0000-0002-8577-6531\nhttps://orcid.org/0000-0003-1342-4251\nhttps://orcid.org/0000-0001-6673-7273\nhttps://orcid.org/0000-0002-2342-7862\nhttps://orcid.org/0000-0003-0684-9235\nhttps://orcid.org/0000-0002-8717-6492\nhttps://orcid.org/0000-0001-8244-7321\nhttps://orcid.org/0000-0003-4913-0538\nhttps://orcid.org/0000-0001-5084-9019\nhttps://orcid.org/0000-0002-8406-8605\nhttps://orcid.org/0000-0001-8569-8409\nhttps://orcid.org/0000-0002-2745-5908\nhttps://orcid.org/0000-0002-0554-4627\nhttps://orcid.org/0000-0002-1933-5383\nhttps://orcid.org/0009-0001-1152-2758\nhttps://orcid.org/0000-0002-2583-1412\nhttps://orcid.org/0009-0008-0356-1061\nhttps://orcid.org/0009-0005-5039-4874\nhttps://orcid.org/0000-0003-0210-9061\nhttps://orcid.org/0000-0001-6839-928X\nhttps://orcid.org/0000-0001-7116-9469\nhttps://orcid.org/0000-0002-9020-7384\nhttps://orcid.org/0009-0000-3973-2485\nhttps://orcid.org/0000-0002-7031-9434\nhttps://orcid.org/0000-0002-2893-6922\nhttps://orcid.org/0000-0001-5354-8350\nhttps://orcid.org/0000-0002-4265-928X\nhttps://orcid.org/0000-0002-3316-0604\nhttps://orcid.org/0000-0001-8178-2494\nhttps://orcid.org/0000-0002-9049-9196\nhttps://orcid.org/0000-0002-7452-8380\nhttps://orcid.org/0009-0009-8645-6685\nhttps://orcid.org/0000-0002-3685-0635\nhttps://orcid.org/0000-0003-4985-3226\nhttps://orcid.org/0000-0001-7002-9093\nhttps://orcid.org/0000-0003-1552-2015\nhttps://orcid.org/0000-0002-2106-4041\nhttps://orcid.org/0000-0002-7602-2527\nhttps://orcid.org/0000-0002-7007-9020\nhttps://orcid.org/0000-0001-6590-6266\nhttps://orcid.org/0000-0002-1964-6106\nhttps://orcid.org/0000-0001-6171-9682\nhttps://orcid.org/0000-0001-7178-5907\n\n\n37\n\n22Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany\n23Also at Isfahan University of Technology, Isfahan, Iran\n24Also at Bergische University Wuppertal (BUW), Wuppertal, Germany\n25Also at Brandenburg University of Technology, Cottbus, Germany\n26Also at Forschungszentrum Jülich, Juelich, Germany\n27Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland\n28Also at Physics Department, Faculty of Science, Assiut University, Assiut, Egypt\n29Also at Wigner Research Centre for Physics, Budapest, Hungary\n30Also at Institute of Physics, University of Debrecen, Debrecen, Hungary\n31Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary\n32Now at Universitatea Babes-Bolyai - Facultatea de Fizica, Cluj-Napoca, Romania\n33Also at Faculty of Informatics, University of Debrecen, Debrecen, Hungary\n34Also at Punjab Agricultural University, Ludhiana, India\n35Also at UPES - University of Petroleum and Energy Studies, Dehradun, India\n36Also at University of Visva-Bharati, Santiniketan, India\n37Also at University of Hyderabad, Hyderabad, India\n38Also at Indian Institute of Science (IISc), Bangalore, India\n39Also at Indian Institute of Technology (IIT), Mumbai, India\n40Also at IIT Bhubaneswar, Bhubaneswar, India\n41Also at Institute of Physics, Bhubaneswar, India\n42Also at Deutsches Elektronen-Synchrotron, Hamburg, Germany\n43Now at Department of Physics, Isfahan University of Technology, Isfahan, Iran\n44Also at Sharif University of Technology, Tehran, Iran\n45Also at Department of Physics, University of Science and Technology of Mazandaran,\nBehshahr, Iran\n46Also at Helwan University, Cairo, Egypt\n47Also at Italian National Agency for New Technologies, Energy and Sustainable Economic\nDevelopment, Bologna, Italy\n48Also at Centro Siciliano di Fisica Nucleare e di Struttura Della Materia, Catania, Italy\n49Also at Università degli Studi Guglielmo Marconi, Roma, Italy\n50Also at Scuola Superiore Meridionale, Università di Napoli ’Federico II’, Napoli, Italy\n51Also at Fermi National Accelerator Laboratory, Batavia, Illinois, USA\n52Also at Università di Napoli ’Federico II’, Napoli, Italy\n53Also at Ain Shams University, Cairo, Egypt\n54Also at Consiglio Nazionale delle Ricerche - Istituto Officina dei Materiali, Perugia, Italy\n55Also at Riga Technical University, Riga, Latvia\n56Also at Department of Applied Physics, Faculty of Science and Technology, Universiti\nKebangsaan Malaysia, Bangi, Malaysia\n57Also at Consejo Nacional de Ciencia y Tecnologı́a, Mexico City, Mexico\n58Also at IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France\n59Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia\n60Also at Trincomalee Campus, Eastern University, Sri Lanka, Nilaveli, Sri Lanka\n61Also at INFN Sezione di Pavia, Università di Pavia, Pavia, Italy\n62Also at Indian Institute of Technology Hyderabad, Hyderabad, India\n63Also at National and Kapodistrian University of Athens, Athens, Greece\n64Also at Ecole Polytechnique Fédérale Lausanne, Lausanne, Switzerland\n65Also at Universität Zürich, Zurich, Switzerland\n66Also at Stefan Meyer Institute for Subatomic Physics, Vienna, Austria\n67Also at Laboratoire d’Annecy-le-Vieux de Physique des Particules, IN2P3-CNRS, Annecy-le-\n\n\n\n38\n\nVieux, France\n68Also at Near East University, Research Center of Experimental Health Science, Mersin,\nTurkey\n69Also at Konya Technical University, Konya, Turkey\n70Also at Izmir Bakircay University, Izmir, Turkey\n71Also at Adiyaman University, Adiyaman, Turkey\n72Also at Istanbul Gedik University, Istanbul, Turkey\n73Also at Necmettin Erbakan University, Konya, Turkey\n74Also at Bozok Universitetesi Rektörlügü, Yozgat, Turkey\n75Also at Marmara University, Istanbul, Turkey\n76Also at Milli Savunma University, Istanbul, Turkey\n77Also at Kafkas University, Kars, Turkey\n78Also at Hacettepe University, Ankara, Turkey\n79Also at Istanbul University - Cerrahpasa, Faculty of Engineering, Istanbul, Turkey\n80Also at Ozyegin University, Istanbul, Turkey\n81Also at Vrije Universiteit Brussel, Brussel, Belgium\n82Also at School of Physics and Astronomy, University of Southampton, Southampton, United\nKingdom\n83Also at University of Bristol, Bristol, United Kingdom\n84Also at IPPP Durham University, Durham, United Kingdom\n85Also at Monash University, Faculty of Science, Clayton, Australia\n86Also at Università di Torino, Torino, Italy\n87Also at Bethel University, St. Paul, Minnesota, USA\n88Also at Karamanoğlu Mehmetbey University, Karaman, Turkey\n89Also at California Institute of Technology, Pasadena, California, USA\n90Also at United States Naval Academy, Annapolis, Maryland, USA\n91Also at University of Florida, Gainesville, Florida, USA\n92Also at Bingol University, Bingol, Turkey\n93Also at Georgian Technical University, Tbilisi, Georgia\n94Also at Sinop University, Sinop, Turkey\n95Also at Erciyes University, Kayseri, Turkey\n96Also at Texas A&M University at Qatar, Doha, Qatar\n97Also at Kyungpook National University, Daegu, Korea\n98Also at another institute or international laboratory covered by a cooperation agreement\nwith CERN\n99Also at Yerevan Physics Institute, Yerevan, Armenia\n100Also at Northeastern University, Boston, Massachusetts, USA\n101Now at another institute or international laboratory covered by a cooperation agreement\nwith CERN\n102Also at Imperial College, London, United Kingdom\n103Also at Institute of Nuclear Physics of the Uzbekistan Academy of Sciences, Tashkent,\nUzbekistan"},"original_url":"https://lss.fnal.gov/archive/2023/pub/fermilab-pub-23-252-cms.pdf","fulltext":true,"description":"Fulltext","key":"4cdac48d2559215ea13b3ed3956f5cf8","url":"https://inspirehep.net/files/4cdac48d2559215ea13b3ed3956f5cf8"}],"authors":[{"raw_affiliations":[{"value":"Yerevan Physics Institute, Yerevan, Armenia"},{"value":"Yerevan State University, Yerevan, Armenia"}],"affiliations_identifiers":[{"schema":"GRID","value":"grid.48507.3e"},{"schema":"GRID","value":"grid.21072.36"},{"schema":"ROR","value":"https://ror.org/00ad27c73"}],"full_name_unicode_normalized":"tumasyan, armen","full_name":"Tumasyan, Armen","record":{"$ref":"https://inspirehep.net/api/authors/1065519"},"ids":[{"schema":"INSPIRE ID","value":"INSPIRE-00175052"},{"schema":"CERN","value":"CERN-673689"},{"schema":"ORCID","value":"0009-0000-0684-6742"},{"schema":"INSPIRE BAI","value":"Armen.Tumasyan.1"}],"last_name":"Tumasyan","affiliations":[{"record":{"$ref":"https://inspirehep.net/api/institutions/903361"},"value":"Yerevan Phys. 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Feynman diagrams for $\\PQq\\Pg\\to\\gammajet$ resonance signal models of \\PQqst, \\PQbst (left), and  QBH production (right).","label":"fig:feynman","source":"arxiv","key":"797a34cefcb627783357e0a00a0fa79e","url":"https://inspirehep.net/files/797a34cefcb627783357e0a00a0fa79e"},{"filename":"w1_Figure_001-b.png","material":"preprint","caption":"Illustrative Feynman diagrams for $\\PQq\\Pg\\to\\gammajet$ resonance signal models of \\PQqst, \\PQbst (left), and  QBH production (right).","label":"fig:feynman","source":"arxiv","key":"d632b6b5249a961a41f8480de803aab6","url":"https://inspirehep.net/files/d632b6b5249a961a41f8480de803aab6"},{"filename":"w2_Figure_002.png","material":"preprint","caption":"Distributions of reconstructed \\gammajet invariant mass for the q* and b* signal models with resonance mass of 4\\TeV, and for QBH from the ADD and RS1 models with $\\Mth=4$\\TeV.","label":"fig:Signal_shapes","source":"arxiv","key":"c322da921d1e38a82e43e1d6c2160913","url":"https://inspirehep.net/files/c322da921d1e38a82e43e1d6c2160913"},{"filename":"w3_Figure_003.png","material":"preprint","caption":"The product of the cross section and branching fraction, \\sigmaBR, as a function of the resonance mass of \\PQqst or \\PQbst signals (\\McPqst or \\McPbst) or the threshold mass of QBH signal models (\\Mth).","label":"fig:Signal_XS","source":"arxiv","key":"e2986adfa3ca2231ee6ec9dc301676d7","url":"https://inspirehep.net/files/e2986adfa3ca2231ee6ec9dc301676d7"},{"filename":"w4_Figure_004-a.png","material":"preprint","caption":"The product of acceptance and efficiency for the \\PQqst signal in the inclusive category and the \\PQbst signal in the \\PQb tag and 0-\\PQb tag categories, for SM coupling $f = 1.0$ and for different resonance values (left), and the signal for the QBH (ADD/RS1) model in the inclusive category, for different \\Mth values (right), for the years 2016, 2017, and 2018.","label":"fig:acceff","source":"arxiv","key":"ba8390da090729310ca21645561b7442","url":"https://inspirehep.net/files/ba8390da090729310ca21645561b7442"},{"filename":"w5_Figure_004-b.png","material":"preprint","caption":"The product of acceptance and efficiency for the \\PQqst signal in the inclusive category and the \\PQbst signal in the \\PQb tag and 0-\\PQb tag categories, for SM coupling $f = 1.0$ and for different resonance values (left), and the signal for the QBH (ADD/RS1) model in the inclusive category, for different \\Mth values (right), for the years 2016, 2017, and 2018.","label":"fig:acceff","source":"arxiv","key":"f3cfb082a21a6a15b2bf3bb6b4004a1b","url":"https://inspirehep.net/files/f3cfb082a21a6a15b2bf3bb6b4004a1b"},{"filename":"w6_Figure_005.png","material":"preprint","caption":"Fit to the \\gammajet invariant mass distribution in data with Eq.~\\eqref{eq:bkgfun} for the \"inclusive\" category of \\PQqst and QBH after all selections. Simulations of the \\PQqst signal with a 2\\TeV mass and coupling $f = 1.0$, the QBH ADD signal with $\\Mth=3\\TeV$, and the QBH RS1 signal with $\\Mth=4\\TeV$ are also shown. The signal distributions are normalized to their exclusion upper limit cross sections. The lower panel shows the difference between the data yield and the background prediction divided by the statistical uncertainty of the data. The green (inner) and yellow (outer) bands, respectively, represent the 68 and 95\\% confidence level statistical uncertainties in the fit.","label":"fig:MassFitq","source":"arxiv","key":"328af8cfbdc7caa8f25b9c28c8af1a23","url":"https://inspirehep.net/files/328af8cfbdc7caa8f25b9c28c8af1a23"},{"filename":"w7_Figure_006-a.png","material":"preprint","caption":"Fits to the \\gammajet invariant mass distributions in data with Eq.~\\eqref{eq:bkgfun} for the \\PQbst selection for the \\PQb tag category (left) and 0-\\PQb tag category (right). Simulations of \\PQbst signals are shown for mass values of 1.0 and 2.0\\TeV and for $f = 1.0$. The signal distributions are normalized to their exclusion upper limit cross sections. The lower panel shows the difference between the data yield and background prediction divided by the statistical uncertainty of the data. The green (inner) and yellow (outer) bands, respectively, represent the 68 and 95\\% confidence level statistical uncertainties in the fit.","label":"fig:MassFit","source":"arxiv","key":"d263f33c214e2c549711982f9c731557","url":"https://inspirehep.net/files/d263f33c214e2c549711982f9c731557"},{"filename":"w8_Figure_006-b.png","material":"preprint","caption":"Fits to the \\gammajet invariant mass distributions in data with Eq.~\\eqref{eq:bkgfun} for the \\PQbst selection for the \\PQb tag category (left) and 0-\\PQb tag category (right). Simulations of \\PQbst signals are shown for mass values of 1.0 and 2.0\\TeV and for $f = 1.0$. The signal distributions are normalized to their exclusion upper limit cross sections. The lower panel shows the difference between the data yield and background prediction divided by the statistical uncertainty of the data. The green (inner) and yellow (outer) bands, respectively, represent the 68 and 95\\% confidence level statistical uncertainties in the fit.","label":"fig:MassFit","source":"arxiv","key":"5d0e292de16d0b95c5ff1b72fd60bf44","url":"https://inspirehep.net/files/5d0e292de16d0b95c5ff1b72fd60bf44"},{"filename":"w9_Figure_007-a.png","material":"preprint","caption":"The expected (dashed) and observed (solid) 95\\% \\CL upper limits on the product of the cross section and branching fraction, as functions of \\PQqst mass, for coupling strength $f=1.0$ (upper left), $f=0.5$ (upper right), and $f=0.1$ (lower). The green (inner) and yellow (outer) bands correspond to 1 and 2 standard deviation uncertainties in the expected limit, respectively. The limits are compared with the theoretical predictions for \\PQqst production for the corresponding coupling strengths.","label":"fig:qstarlimit","source":"arxiv","key":"b15e66241a160c14be202ce78b90cb9c","url":"https://inspirehep.net/files/b15e66241a160c14be202ce78b90cb9c"},{"filename":"w10_Figure_007-b.png","material":"preprint","caption":"The expected (dashed) and observed (solid) 95\\% \\CL upper limits on the product of the cross section and branching fraction, as functions of \\PQqst mass, for coupling strength $f=1.0$ (upper left), $f=0.5$ (upper right), and $f=0.1$ (lower). The green (inner) and yellow (outer) bands correspond to 1 and 2 standard deviation uncertainties in the expected limit, respectively. The limits are compared with the theoretical predictions for \\PQqst production for the corresponding coupling strengths.","label":"fig:qstarlimit","source":"arxiv","key":"607170e508c3e5813cfa838eefc902a0","url":"https://inspirehep.net/files/607170e508c3e5813cfa838eefc902a0"},{"filename":"w11_Figure_007-c.png","material":"preprint","caption":"The expected (dashed) and observed (solid) 95\\% \\CL upper limits on the product of the cross section and branching fraction, as functions of \\PQqst mass, for coupling strength $f=1.0$ (upper left), $f=0.5$ (upper right), and $f=0.1$ (lower). The green (inner) and yellow (outer) bands correspond to 1 and 2 standard deviation uncertainties in the expected limit, respectively. The limits are compared with the theoretical predictions for \\PQqst production for the corresponding coupling strengths.","label":"fig:qstarlimit","source":"arxiv","key":"e04b5de256d7e869ff16d18a1990dadf","url":"https://inspirehep.net/files/e04b5de256d7e869ff16d18a1990dadf"},{"filename":"w12_Figure_008-a.png","material":"preprint","caption":"The expected (dashed) and observed (solid) 95\\% \\CL upper limits on the product of the cross section and branching fraction, as functions of \\PQbst mass, for coupling strength $f=1.0$ (upper left), $f=0.5$ (upper right), and $f=0.1$ (lower). The green (inner) and yellow (outer) bands correspond to 1 and 2 standard deviation uncertainties in the expected limit, respectively. The limits are compared with the theoretical predictions for \\PQbst production for the corresponding coupling strengths. For coupling $f=1.0$, the limits are compared for \\PQbst production by gauge interactions (red), contact interactions (violet), and total \\PQbst signal by the addition of these two production modes.","label":"fig:bstarlimit","source":"arxiv","key":"055083e922a17c24a8513c9cf736b06d","url":"https://inspirehep.net/files/055083e922a17c24a8513c9cf736b06d"},{"filename":"w13_Figure_008-b.png","material":"preprint","caption":"The expected (dashed) and observed (solid) 95\\% \\CL upper limits on the product of the cross section and branching fraction, as functions of \\PQbst mass, for coupling strength $f=1.0$ (upper left), $f=0.5$ (upper right), and $f=0.1$ (lower). The green (inner) and yellow (outer) bands correspond to 1 and 2 standard deviation uncertainties in the expected limit, respectively. The limits are compared with the theoretical predictions for \\PQbst production for the corresponding coupling strengths. For coupling $f=1.0$, the limits are compared for \\PQbst production by gauge interactions (red), contact interactions (violet), and total \\PQbst signal by the addition of these two production modes.","label":"fig:bstarlimit","source":"arxiv","key":"633b9443d2817c1beae401b233cad09c","url":"https://inspirehep.net/files/633b9443d2817c1beae401b233cad09c"},{"filename":"w14_Figure_008-c.png","material":"preprint","caption":"The expected (dashed) and observed (solid) 95\\% \\CL upper limits on the product of the cross section and branching fraction, as functions of \\PQbst mass, for coupling strength $f=1.0$ (upper left), $f=0.5$ (upper right), and $f=0.1$ (lower). The green (inner) and yellow (outer) bands correspond to 1 and 2 standard deviation uncertainties in the expected limit, respectively. The limits are compared with the theoretical predictions for \\PQbst production for the corresponding coupling strengths. For coupling $f=1.0$, the limits are compared for \\PQbst production by gauge interactions (red), contact interactions (violet), and total \\PQbst signal by the addition of these two production modes.","label":"fig:bstarlimit","source":"arxiv","key":"ec585d59f151ab221582448c4b58cd7d","url":"https://inspirehep.net/files/ec585d59f151ab221582448c4b58cd7d"},{"filename":"w15_Figure_009-a.png","material":"preprint","caption":"The expected (dashed) and observed (solid) 95\\% \\CL upper limit on the product of the cross section and branching fraction as a function of the minimum black hole mass for the ADD ($n=6$) and RS1 ($n=1$) models on the left and right, respectively. The green (inner) and yellow (outer) bands correspond to 1 and 2 standard deviation uncertainties in the expected limit. The limits are compared with the theoretical predictions for QBH production for ADD ($n=6$) and RS1 ($n=1$) models.","label":"fig:QBHlimit","source":"arxiv","key":"3139d5de677e2bc6777d3c72de9407b2","url":"https://inspirehep.net/files/3139d5de677e2bc6777d3c72de9407b2"},{"filename":"w16_Figure_009-b.png","material":"preprint","caption":"The expected (dashed) and observed (solid) 95\\% \\CL upper limit on the product of the cross section and branching fraction as a function of the minimum black hole mass for the ADD ($n=6$) and RS1 ($n=1$) models on the left and right, respectively. The green (inner) and yellow (outer) bands correspond to 1 and 2 standard deviation uncertainties in the expected limit. The limits are compared with the theoretical predictions for QBH production for ADD ($n=6$) and RS1 ($n=1$) models.","label":"fig:QBHlimit","source":"arxiv","key":"348b07801559c956968cb945c868f487","url":"https://inspirehep.net/files/348b07801559c956968cb945c868f487"},{"filename":"w17_Figure_010.png","material":"preprint","caption":"The expected and observed 95\\% \\CL exclusion mass limit variation with the SM couplings for the excited \\PQqst and \\PQbst signal models.","label":"fig:2Dplot","source":"arxiv","key":"36142b8ea1795ca10c28cc916ae40e1c","url":"https://inspirehep.net/files/36142b8ea1795ca10c28cc916ae40e1c"}],"inspire_categories":[{"term":"Experiment-HEP","source":"arxiv"}],"accelerator_experiments":[{"legacy_name":"CERN-LHC-CMS","record":{"$ref":"https://inspirehep.net/api/experiments/1108642"}}],"urls":[{"description":"Fermilab Library Server","value":"https://lss.fnal.gov/archive/2023/pub/fermilab-pub-23-252-cms.pdf"}],"first_author":{"affiliations_identifiers":[{"schema":"GRID","value":"grid.48507.3e"},{"schema":"GRID","value":"grid.21072.36"},{"schema":"ROR","value":"https://ror.org/00ad27c73"}],"full_name":"Tumasyan, Armen","ids":[{"schema":"INSPIRE ID","value":"INSPIRE-00175052"},{"schema":"CERN","value":"CERN-673689"},{"schema":"ORCID","value":"0009-0000-0684-6742"},{"schema":"INSPIRE BAI","value":"Armen.Tumasyan.1"}],"last_name":"Tumasyan","first_name":"Armen","recid":1065519},"control_number":2659689,"dois":[{"source":"Springer","value":"10.1007/JHEP12(2023)189"},{"material":"publication","source":"arXiv","value":"10.1007/JHEP12(2023)189"}],"document_type":["article"],"texkeys":["CMS:2023twl"],"abstracts":[{"source":"Springer","value":"A search for resonances in events with the γ+jet final state has been performed using proton-proton collision data collected at $ \\sqrt{s} $ = 13 TeV by the CMS experiment at the LHC. The total data analyzed correspond to an integrated luminosity of 138 fb$^{−1}$. Models of excited quarks and quantum black holes are considered. Using a wide-jet reconstruction for the candidate jet, the γ+jet invariant mass spectrum measured in data is examined for the presence of resonances over the standard model continuum background. The background is estimated by fitting this mass distribution with a functional form. The data exhibit no statistically significant deviations from the expected standard model background. Exclusion limits at 95% confidence level on the resonance mass and other parameters are set. Excited light-flavor quarks (excited bottom quarks) are excluded up to a mass of 6.0 (3.8) TeV. Quantum black hole production is excluded for masses up to 7.5 (5.2) TeV in the Arkani-Hamed-Dimopoulos-Dvali (Randall-Sundrum) model. These lower mass bounds are the most stringent to date among those obtained in the γ+jet final state.[graphic not available: see fulltext]","abstract_source_suggest":{"input":"Springer"}},{"source":"arXiv","value":"A search for resonances in events with the $\\gamma$+jet final state has been performed using proton-proton collision data collected at $\\sqrt{s}$ = 13 TeV by the CMS experiment at the LHC. The total data analyzed correspond to an integrated luminosity of 138 fb$^{-1}$. Models of excited quarks and quantum black holes are considered. Using a wide-jet reconstruction for the candidate jet, the $\\gamma$+jet invariant mass spectrum measured in data is examined for the presence of resonances over the standard model continuum background. The background is estimated by fitting the mass distribution with a functional form. The data exhibit no statistically significant deviations from the expected standard model background. Exclusion limits at 95% confidence level on the resonance mass and other parameters are set. Excited light-flavor quarks (excited bottom quarks) are excluded up to a mass of 6.0 (3.8) TeV. Quantum black hole production is excluded for masses up to 7.5 (5.2) TeV in the Arkani-Hamed-Dimopoulos-Dvali (Randall-Sundrum) model. These lower mass bounds are the most stringent to date among those obtained in the $\\gamma$+jet final state.","abstract_source_suggest":{"input":"arXiv"}}],"primary_arxiv_category":["hep-ex"],"titles":[{"source":"Springer","title":"Search for resonances in events with photon and jet final states in proton-proton collisions at $ \\sqrt{s} $ = 13 TeV"},{"source":"arXiv","title":"Search for resonances in events with photon and jet final states in proton-proton collisions at $\\sqrt{s}$= 13 TeV"},{"source":"arXiv","title":"Search for resonances in events with photon and jet final states in proton-proton collisions at $sqrt{s}$ = 13 TeV"}],"imprints":[{"date":"2023-12-28"}],"curated":true},"updated":"2026-04-08T19:31:37.190361+00:00"},{"id":"1768904","created":"2019-12-08T00:00:00+00:00","links":{"bibtex":"https://inspirehep.net/api/literature/1768904?format=bibtex","latex-eu":"https://inspirehep.net/api/literature/1768904?format=latex-eu","latex-us":"https://inspirehep.net/api/literature/1768904?format=latex-us","json":"https://inspirehep.net/api/literature/1768904?format=json","json-expanded":"https://inspirehep.net/api/literature/1768904?format=json-expanded","cv":"https://inspirehep.net/api/literature/1768904?format=cv","citations":"https://inspirehep.net/api/literature/?q=refersto%3Arecid%3A1768904"},"metadata":{"citation_count":0,"authors":[{"full_name_unicode_normalized":"buyens, boye","full_name":"Buyens, Boye","record":{"$ref":"https://inspirehep.net/api/authors/2352935"},"affiliations":[{"record":{"$ref":"https://inspirehep.net/api/institutions/902815"},"value":"Gent U."}],"ids":[{"schema":"INSPIRE BAI","value":"B.Buyens.1"}],"last_name":"Buyens","signature_block":"BYANb","uuid":"7b091e97-3878-4572-b050-b73c3f8be0ee","first_name":"Boye","recid":2352935}],"citation_count_without_self_citations":0,"$schema":"https://inspirehep.net/schemas/records/hep.json","keywords":[{"schema":"INSPIRE","value":"network"}],"references":[{"reference":{"label":"1","publication_info":{"journal_volume":"128","artid":"2425","year":1962,"page_start":"2425","journal_title":"Phys.Rev."},"title":{"title":"Gauge invariance and mass. ii"},"authors":[{"full_name":"Schwinger, J."}]},"raw_refs":[{"schema":"text","value":"[1] J. Schwinger, “Gauge invariance and mass. ii,” Phys. Rev. 128, 2425 (1962)."}],"curated_relation":false,"record":{"$ref":"https://inspirehep.net/api/literature/14009"}},{"reference":{"label":"2","publication_info":{"journal_volume":"125","artid":"397","year":1962,"page_start":"397","journal_title":"Phys.Rev."},"title":{"title":"Gauge invariance and mass"},"authors":[{"full_name":"Schwinger, J."}]},"raw_refs":[{"schema":"text","value":"[2] J. Schwinger, “Gauge invariance and mass,” Phys. Rev. 125, 397 (1962)."}],"curated_relation":false,"record":{"$ref":"https://inspirehep.net/api/literature/14008"}},{"reference":{"label":"3","publication_info":{"journal_volume":"130","artid":"439","year":1963,"page_start":"439","journal_title":"Phys.Rev."},"title":{"title":"Plasmons, gauge invariance, and mass"},"authors":[{"full_name":"Anderson, P.W."}]},"raw_refs":[{"schema":"text","value":"[3] P. W. Anderson, “Plasmons, gauge invariance, and mass,” Phys. 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Tirkkonen, “Charge screening in the Vnite temperature schwinger model,” International Journal of Modern Physics A 11, 4103 (1996)."}],"curated_relation":false,"record":{"$ref":"https://inspirehep.net/api/literature/402270"}},{"reference":{"label":"19","publication_info":{"journal_volume":"389","artid":"121","year":1996,"page_start":"121","journal_title":"Phys.Lett.B"},"title":{"title":"Anomalous behavior in the massive schwinger model"},"authors":[{"full_name":"Rodriguez, R."},{"full_name":"Hosotani, Y."}]},"raw_refs":[{"schema":"text","value":"[19] R. Rodriguez and Y. Hosotani, “Anomalous behavior in the massive schwinger model,” Physics Letters B 389, 121 (1996)."}],"curated_relation":false,"record":{"$ref":"https://inspirehep.net/api/literature/422614"}},{"reference":{"arxiv_eprint":"hep-th/9602029","label":"20","publication_info":{"journal_volume":"375","artid":"273","year":1996,"page_start":"273","journal_title":"Phys.Lett.B"},"title":{"title":"ConVnement and chiral condensates in 2d QED with massive N-Wavor fermions"},"authors":[{"full_name":"Rodriguez, R."},{"full_name":"Hosotani, Y."}]},"raw_refs":[{"schema":"text","value":"[20] R. Rodriguez and Y. Hosotani, “ConVnement and chiral condensates in 2d QED with massive N-Wavor fermions,” Physics Letters B 375, 273 (1996), hep-th/9602029 ."}],"curated_relation":false,"record":{"$ref":"https://inspirehep.net/api/literature/415781"}},{"reference":{"arxiv_eprint":"hep-th/9704064","label":"21","publication_info":{"journal_volume":"259","artid":"1","year":1997,"page_start":"1","journal_title":"Annals Phys."},"title":{"title":"Massive Schwinger Model within Mass Perturbation Theory"},"authors":[{"full_name":"Adam, C."}]},"raw_refs":[{"schema":"text","value":"[21] C. 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In CAMPS, two-site Clifford circuits are applied to the MPS repeatedly. Details about the optimization of the ansatz can be found in Ref.~\\cite{PhysRevLett.133.190402}. (b) Critical spin chains conjugated by Clifford gates obtained from variational optimization in CAMPS. CAMPS changes the free boundary condition of the quantum Ising chain to the fixed boundary condition~\\cite{ref_ising_bc_discussion}, and maps the XX chain to two decoupled critical quantum Ising chains. The XXZ chain is mapped to the Ashkin-Teller quantum spin chain.","label":"fig:1","source":"arxiv","key":"5b3fb4b77b57b4befe49e4290f4455ab","url":"https://inspirehep.net/files/5b3fb4b77b57b4befe49e4290f4455ab"},{"filename":"IsingXYwithposition.png","material":"preprint","caption":"Entanglement entropy at different cuts for the critical Ising model (a) and XXZ chain at $g=0$, i.e., the XX model (b) with open boundary conditions. Notice that the entanglement entropy from CAMPS is actually the NsEE. The size of the chain is $L=100$. The bond dimension is $D=200$ and $60$ for MPS and CAMPS, respectively, which gives converged results. $p$ denotes the position of the cut.","label":"fig_entanglement_entropy","source":"arxiv","key":"b776c0fc6ba8d344dcefa649f0c04282","url":"https://inspirehep.net/files/b776c0fc6ba8d344dcefa649f0c04282"},{"filename":"IsingandXY.png","material":"preprint","caption":"Comparison of the MPS and the CAMPS results for the critical quantum Ising [(a) and (b)] and XX [(c) and (d)] chains. Notice that the entanglement entropy from CAMPS is actually the NsEE. Finite-size scaling of the entanglement entropy is shown in (a) for the critical quantum Ising chain and (c) for the XX chain. Shifted and rescaled entanglement spectrum is shown in (b) for the critical quantum Ising chain and (d) for the XX chain. The cut is at the center bond of the spin chain in all the cases except for the CAMPS result of the XX chain, where the cut is at the $L/4$-th site because the spin chain is transformed into two decoupled Ising chains [see Fig.~\\ref{fig_entanglement_entropy}(b)]. In (a) and (c), the $x$-axis is in the logarithmic scale and the central charges are fitted to be $c\\sim0.50$ for the CAMPS result. In (b) and (d), the lowest eigenvalue in the entanglement spectrum $\\Delta$ is normalized to be $0$ and $1/16$ for the MPS and CAMPS results, respectively. For both MPS and CAMPS, converged results with bond dimension $D$ are plotted.","label":"fig_isingandXX","source":"arxiv","key":"620013011810e12f397cf380e622b6fb","url":"https://inspirehep.net/files/620013011810e12f397cf380e622b6fb"},{"filename":"XXZ05andHeientropy.png","material":"preprint","caption":"Comparison of the MPS and the CAMPS results for the XXZ chain with (a) $g = 0.5$ and (b) $g=1$. Finite-size scaling of the entanglement entropies are shown. For both cases, only a constant reduction of entanglement entropy is found in CAMPS result, while the slopes remain unchanged. The reduction values can be found in Fig.~\\ref{fig_entropyfit} and Table.~\\ref{t1} in the Appendix. These results are consistent with the fact that optimized Clifford circuit in CAMPS [see Fig.~\\ref{fig_circuitIsingandHei_1}(b) in Appendix~\\ref{sec:optimized-Clifford-circuits}] is a MPO with finite bond dimension.","label":"fig:XXZ","source":"arxiv","key":"5ef4806c48064e10c3b2900b5434d5f1","url":"https://inspirehep.net/files/5ef4806c48064e10c3b2900b5434d5f1"},{"filename":"energycomparison.png","material":"preprint","caption":"Comparison of the relative error of calculated ground state energy ($\\delta$) between MPS and CAMPS for the (a) critical Ising (b) XX, (c) XXZ with $g=0.5$, and (d) Heisenberg model. The system size is $L = 200$. The MPS value of $D=1000$ is used as reference.","label":"fig_energycomparison","source":"arxiv","key":"58371953e346ceed525dd161cd6129fb","url":"https://inspirehep.net/files/58371953e346ceed525dd161cd6129fb"},{"filename":"entropyfit.png","material":"preprint","caption":"The reduction of entanglement entropy in CAMPS ($\\Delta S$) for (a) the critical Ising (b) the XXZ with $g=0.5$, and the Heisenberg models. Fits using $\\Delta S = \\alpha \\times L^{-\\beta} + \\gamma$ are also shown.","label":"fig_entropyfit","source":"arxiv","key":"0b24e8be83a8c0565081250176e1712c","url":"https://inspirehep.net/files/0b24e8be83a8c0565081250176e1712c"},{"filename":"circuitIsingandHei.png","material":"preprint","caption":"Illustration of the optimized Clifford circuits for the critical transverse Ising (a) and XXZ (b) chains. Here, systems of $8$ sites are used as examples. Results for larger system size are similar. As mentioned in the main text, the optimized Clifford circuits are $\\prod_{i=1}^{L-1}\\text{CNOT}_{i+1,i}$ for the critical transverse Ising chain. The optimized Clifford circuits for XXZ are more complicated, as shown in (b), where the effect of the two-qubit circuits is listed in Table.~\\ref{def_gate}.","label":"fig_circuitIsingandHei_1","source":"arxiv","key":"e55b08ca4d3cf3184bea81ed7df5d9a3","url":"https://inspirehep.net/files/e55b08ca4d3cf3184bea81ed7df5d9a3"},{"filename":"circuitXX.png","material":"preprint","caption":"Illustration of the optimized Clifford circuits for the XX chain. The first two layers are exactly the same as the XXZ chain in Fig.~\\ref{fig_circuitIsingandHei_1}(b). CAMPS also finds layers of swap gates in the shape of a pyramid which arrange even (odd) sites into the left (right) of the chain (except for the first and the last sites), spatially separating the two decoupled critical transverse Ising chains.","label":"fig_circuitXX_1","source":"arxiv","key":"fadf8623dd83d72e2207813f6207d7fd","url":"https://inspirehep.net/files/fadf8623dd83d72e2207813f6207d7fd"}],"inspire_categories":[{"term":"Quantum Physics","source":"arxiv"},{"term":"Condensed Matter","source":"arxiv"},{"term":"Theory-HEP","source":"arxiv"}],"first_author":{"affiliations_identifiers":[{"schema":"ROR","value":"https://ror.org/05cvf7v30"},{"schema":"ROR","value":"https://ror.org/05qbk4x57"}],"full_name":"Fan, Chaohui","ids":[{"schema":"ORCID","value":"0009-0005-1271-6238"},{"schema":"INSPIRE BAI","value":"C.Fan.13"}],"last_name":"Fan","first_name":"Chaohui","recid":2274978},"control_number":2849946,"dois":[{"material":"publication","source":"APS","value":"10.1103/PhysRevB.111.085121"},{"material":"publication","source":"arXiv","value":"10.1103/PhysRevB.111.085121"}],"document_type":["article"],"texkeys":["Fan:2024bzi"],"abstracts":[{"source":"APS","value":"Clifford circuits can be utilized to disentangle quantum states with polynomial cost, thanks to the Gottesman-Knill theorem. Based on this idea, the Clifford Circuits Augmented Matrix Product States (CAMPS) method, which is a seamless integration of Clifford circuits within the density-matrix renormalization group algorithm, was proposed recently and was shown to be able to reduce entanglement in various quantum systems. In this work, we further explore the power of the CAMPS method in critical spin chains described by conformal field theories (CFTs) in the scaling limit. We find that the optimized disentanglers correspond to duality transformations, which significantly reduce the entanglement entropy in the ground state. For the critical quantum Ising spin chain governed by the Ising CFT with self-duality, the Clifford circuits found by CAMPS coincide with the duality transformation, i.e., the Kramer-Wannier self-duality in the critical Ising chain. It reduces the entanglement entropy by mapping the free conformal boundary condition to the fixed one. In the more general case of the XXZ chain, the CAMPS gives rise to a duality transformation mapping the model to the quantum Ashkin-Teller spin chain. Our results highlight the potential of the framework as a versatile tool for uncovering hidden dualities and simplifying the entanglement structure of critical quantum systems.","abstract_source_suggest":{"input":"APS"}},{"source":"arXiv","value":"Clifford circuits can be utilized to disentangle quantum states with polynomial cost, thanks to the Gottesman-Knill theorem. Based on this idea, the Clifford circuits augmented matrix product states (CAMPS) method, which is a seamless integration of Clifford circuits within the density-matrix renormalization group algorithm, was proposed recently and was shown to be able to reduce entanglement in various quantum systems. In this work, we further explore the power of the CAMPS method in critical spin chains described by conformal field theories (CFTs) in the scaling limit. We find that the optimized disentanglers correspond to {\\it duality} transformations, which significantly reduce the entanglement entropy in the ground state. For the critical quantum Ising spin chain governed by the Ising CFT with self-duality, the Clifford circuits found by CAMPS coincide with the duality transformation, i.e., the Kramers-Wannier self-duality in the critical Ising chain. It reduces the entanglement entropy by mapping the free conformal boundary condition to the fixed one. In the more general case of the XXZ chain, the CAMPS gives rise to a duality transformation mapping the model to the quantum Ashkin-Teller spin chain. Our results highlight the potential of the framework as a versatile tool for uncovering hidden dualities and simplifying the entanglement structure of critical quantum systems.","abstract_source_suggest":{"input":"arXiv"}}],"primary_arxiv_category":["quant-ph"],"titles":[{"source":"APS","title":"Disentangling critical quantum spin chains with Clifford circuits"},{"source":"arXiv","title":"Disentangling critical quantum spin chains with Clifford circuits"}],"imprints":[{"date":"2025-02-10"}],"curated":false},"updated":"2025-10-05T10:14:20.156837+00:00"},{"id":"2763335","created":"2024-03-02T03:36:51.258676+00:00","links":{"bibtex":"https://inspirehep.net/api/literature/2763335?format=bibtex","latex-eu":"https://inspirehep.net/api/literature/2763335?format=latex-eu","latex-us":"https://inspirehep.net/api/literature/2763335?format=latex-us","json":"https://inspirehep.net/api/literature/2763335?format=json","json-expanded":"https://inspirehep.net/api/literature/2763335?format=json-expanded","cv":"https://inspirehep.net/api/literature/2763335?format=cv","citations":"https://inspirehep.net/api/literature/?q=refersto%3Arecid%3A2763335"},"metadata":{"citation_count":0,"publication_info":[{"journal_volume":"1067","artid":"169672","material":"publication","year":2024,"journal_record":{"$ref":"https://inspirehep.net/api/journals/1613981"},"journal_title":"Nucl.Instrum.Meth.A"},{"journal_volume":"1067","artid":"169672","material":"publication","conference_record":{"$ref":"https://inspirehep.net/api/conferences/2692274"},"year":2024,"journal_record":{"$ref":"https://inspirehep.net/api/journals/1613981"},"journal_title":"Nucl.Instrum.Meth.A","cnum":"C23-09-03.3"}],"documents":[{"filename":"Publication.pdf","material":"publication","attachment":{"content":"Nuclear Instruments and Methods in Physics Research A 1067 (2024) 169672\n\nA\n0\n\nContents lists available at ScienceDirect\n\nNuclear Inst. and Methods in Physics Research, A\n\njournal homepage: www.elsevier.com/locate/nima\n\nIn-beam performance of a Resistive Plate Chamber operated with\neco-friendly gas mixtures\nL. Quaglia a ,∗, on behalf of the ALICE and RPC ECOgas@GIF++ collaborations., The RPC\nECOgas@GIF++ collaboration:, M. Abbrescia f,c, G. Aielli u, R. Aly c,h, M.C. Arena q, M. Barroso k,\nL. Benussi d, S. Bianco d, D. Boscherini g, F. Bordon p, A. Bruni g, S. Buontempo r, M. Busato p,\nP. Camarri u, R. Cardarelli m, L. Congedo c, D. De Jesus Damiao k, M. De Serio f,c, A. Di Ciaccio u,\nL. Di Stante u, P. Dupieux n, J. Eysermans s, A. Ferretti l,a, G. Galati f,c, M. Gagliardi l,a, R. Guida p,\nG. Iaselli b,c, B. Joly n, S.A. Juks x, K.S. Lee w, B. Liberti m, D. Lucero Ramirez v, B. Mandelli p,\nS.P. Manen n, L. Massa g, A. Pastore c, E. Pastori m, D. Piccolo d, L. Pizzimento m, A. Polini g,\nG. Proto m, G. Pugliese b,c, D. Ramos b,c, G. Rigoletti p, A. Rocchi m, M. Romano g, A. Samalan j,\nP. Salvini i, R. Santonico u, G. Saviano e, M. Sessa m, S. Simone f,c, L. Terlizzi l,a, M. Tytgat j,t,\nE. Vercellin l,a, M. Verzeroli o, N. Zaganidis v\n\na INFN Sezione di Torino, Via P. Giuria 1, Torino, 10125, Italy\nb Politecnico di Bari, Dipartimento Interateneo di Fisica, via Amendola 173, Bari, 70125, Italy\nc INFN Sezione di Bari, Via E. Orabona 4, Bari, 70125, Italy\nd INFN - Laboratori Nazionali di Frascati, Via Enrico Fermi 54, Frascati (Roma), 00044, Italy\ne Sapienza Università di Roma, Dipartimento di Ingegneria Chimica Materiali Ambiente, Piazzale Aldo Moro 5, Roma, 00185, Italy\nf Università degli studi di Bari, Dipartimento Interateneo di Fisica, Via Amendola 173, Bari, 70125, Italy\ng INFN Sezione di Bologna, Via C. Berti Pichat 4/2, Bologna, 40127, Italy\nh Helwan University, Helwan, Cairo Governorate, 4037120, Egypt\ni INFN Sezione di Pavia, Via A. Bassi 6, Pavia, 27100, Italy\nj Ghent University, Department of Physics and Astronomy, Proeftuinstraat 86, Ghent, B-9000, Belgium\nk Universidade do Estado do Rio de Janeiro, R. São Francisco Xavier, 524, Maracanã, Rio de Janeiro - RJ, 20550-013, Brazil\nl Università degli studi di Torino, Dipartimento di Fisica, Via P. Giuria 1, Torino, 10125, Italy\nm INFN Sezione di Roma Tor Vergata, Via della Ricerca Scientifica 1, Roma, 00133, Italy\nn Clermont Université, Université Blaise Pascal, CNRS/IN2P3, Laboratoire de Physique Corpusculaire, BP 10448, Clermont-Ferrand, F-63000, France\no Universitè Claude Bernard Lyon I, 43 Bd du 11 Novembre 1918, Villeurbanne, 69100, France\np CERN, Espl. des Particules 1, Meyrin, 1211, Switzerland\nq Università degli studi di Pavia, Corso Strada Nuova 65, Pavia, 27100, Italy\nr INFN Sezione di Napoli, Complesso universitario di Monte S. Angelo ed. 6 Via Cintia, Napoli, 80126, Italy\ns Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA, 02139, USA\nt Vrije Universiteit Brussel (VUB-ELEM), Department of Physics, Pleinlaan 2, Brussels, 1050, Belgium\nu Università degli studi di Roma Tor Vergata, Dipartimento di Fisica, Via della Ricerca Scientifica 1, Roma, 00133, Italy\nv Universidad Iberoamericana, Dept. de Fisica y Matematicas, Mexico City, 01210, Mexico\nw Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, Republic of Korea\nx Université Paris-Saclay, 3 rue Joliot Curie, Bâtiment Breguet, Gif-sur-Yvette, 91190, France\n\nA R T I C L E I N F O\n\nKeywords:\nResistive plate chambers\nBeam test\nEco-friendly gas mixtures\n\nA B S T R A C T\n\nALICE (A Large Ion Collider Experiment) studies the Quark-Gluon Plasma (QGP): a deconfined state of nuclear\nmatter obtained in ultra-relativistic heavy-ion collisions. One of the key probes for QGP characterization is the\nstudy of quarkonia and open heavy flavor production, of which ALICE exploits the muonic decay. In particular,\na set of Resistive Plate Chambers (RPCs), placed in the forward rapidity region of the ALICE detector, is used\nfor muon identification purposes.\n\nThe correct operation of these detectors is ensured by the choice of the proper gas mixture. Currently they\nare operated with a mixture of C2H2F4, i-C4H10 and SF6 but, starting from 2017, new EU regulations have\n\n∗ Corresponding author.\nE-mail address: luca.quaglia@cern.ch (L. Quaglia).\nvailable online 2 August 2024\n168-9002/© 2024 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).\n\nhttps://doi.org/10.1016/j.nima.2024.169672\nReceived 7 December 2023; Received in revised form 9 July 2024; Accepted 28 July 2024\n\nhttps://www.elsevier.com/locate/nima\nhttps://www.elsevier.com/locate/nima\nhttps://orcid.org/0000-0002-0793-8275\nmailto:luca.quaglia@cern.ch\nhttps://doi.org/10.1016/j.nima.2024.169672\nhttps://doi.org/10.1016/j.nima.2024.169672\nhttp://crossmark.crossref.org/dialog/?doi=10.1016/j.nima.2024.169672&domain=pdf\nhttp://creativecommons.org/licenses/by/4.0/\n\n\nNuclear Inst. and Methods in Physics Research, A 1067 (2024) 169672L. Quaglia et al.\nenforced a progressive phase-out of C2H2F4 because of its large Global Warming Potential (GWP), which is\nmaking it difficult and costly to purchase. Moreover, CERN asked LHC experiments to reduce greenhouse gases\nemissions, to which RPC operation contributes significantly.\n\nA possible candidate for C2H2F4 replacement is the C3H2F4 (diluted with other gases, such as CO2), which\nhas been extensively tested using cosmic muons. Promising gas mixtures have been devised; the next crucial\nsteps are the detailed in-beam characterization of such mixtures as well as the study of their performance\nunder increasing irradiation levels.\n\nThis contribution will describe the methodology and results of beam tests carried out at the CERN Gamma\nIrradiation Facility (equipped with a high activity 137Cs source and muon beam) with an ALICE-like RPC\nprototype, operated with several mixtures with varying proportions of CO2, C3H2F4, i-C4H10 and SF6 . Absorbed\ncurrents, efficiencies, prompt charges, cluster sizes, time resolutions and rate capabilities will be presented,\nboth from digitized (for detailed shape and charge analysis) and discriminated (using the same front-end\nelectronics as employed in ALICE) signals.\n1. Introduction\n\nA Large Ion Collider Experiment (ALICE) [1] is one of the four main\nLHC experiments. Its main goal is the study of the Quark Gluon plasma\n(QGP) in heavy-ion collisions. One of the exploited signatures for QGP\nstudies in ALICE is the suppression of quarkonia (bound states of heavy\nquarks and corresponding anti-quark) production [2]. ALICE studies\ntheir dimuon decays using its forward muon spectrometer [3] and the\nResistive Plate Chambers (RPCs), main subject of this contribution,\nare employed to identify the muons among all the particles crossing\nthe spectrometer since they are located downstream of a hadron filter\nwhich absorbs any hadron traversing the muon spectrometer (hence the\nname Muon IDentifier, MID)\n\nRPCs are gaseous detectors with planar geometry and resistive\nelectrodes. In the case of the ALICE MID, they have a 2 mm single\ngas gap and 2 mm thick bakelite electrodes (𝜌 ≈ 109–1010 Ω⋅cm);\nthey are readout by two perpendicular copper strips planes and they\nemploy the FEERIC front-end electronics [4]. The RPCs are operated in\nmaxi-avalanche mode, with a mixture of 89.7% C2H2F4, 10% i-C4H10\nand 0.3% SF6 and, although this mixture satisfies all the performance\nrequirements, it contains a high fraction of fluorinated greenhouse\ngases (F-gases/GHGs) (C2H2F4 and SF6).\n\nStarting from 2017, new EU regulations [5] have imposed a progres-\nsive phase-down in the production and usage of these gases, leading to\nan increase of cost and reduction in availability. For this reason, CERN\nhas adopted a policy of F-gases reduction. Since RPCs represent a signif-\nicant fraction of the total GHG-gases emission of the LHC experiments,\nit is of the utmost importance to search for more eco-friendly RPC\ngas mixtures. The first efforts are concentrated on the replacement of\nC2H2F4 using a gas known as tetrafluoropropene (C3H2F4) diluted with\nother gases to lower the detector working voltage [6–9]. Promising gas\nmixtures have been identified by different research groups and their\ncomplete characterization in controlled data-taking environments (such\nas beam tests), as well as the study of the detectors long-term behavior\nwhen operated with low-GWP gas mixtures is now needed.\n\nTo this aim, the RPC ECOgas@GIF++ collaboration [10] (between\nALICE, ATLAS, CMS, SHiP/LHCb and the CERN EP-DT group) was cre-\nated to join forces among RPC experts of the different LHC experiments\nto share knowledge and manpower. Each group provided a detector\nprototype to be installed in a common support and the results shown\nhereafter have been obtained with the detector provided by the ALICE\nRPC group.\n\nThis contribution is divided as follows: Section 2 contains a de-\nscription of the experimental setup and the methodology used in the\ndata-taking, Section 3 reports the main results obtained from a beam\ntest campaign where mixtures with different HFO/CO2 ratios have been\nbeam-tested. Lastly, Section 4 is dedicated to the conclusion and to\npossible outlooks for the future of this work.\n2\n\nFig. 1. Sketch of the experimental setup installed in GIF++ (a detailed description of\neach component is reported in the text).\n\n2. Experimental setup\n\nThe experimental setup is located at the CERN Gamma Irradiation\nFacility (GIF++) [11], installed on the H4 secondary beam line of the\nCERN SPS. This facility is equipped with a high activity (∼12.5 TBq)\n137Cs source and, in dedicated beam time periods, it is exposed to a\nhigh energy (∼150 GeV) muon beam. The source can either be used to\nproduce a high background radiation on the detector, simulating long\noperation periods in shorter time-spans (years in ∼months) or it can\nbe combined with the muon beam to study the detector performance\nunder varying background levels.\n\nThe 𝛾 radiation can be attenuated by means of lead filters and a\ntotal of 27 combinations can be obtained. The attenuation is measured\nwith a pure number, which ranges from 1 to 46,000 (maximum and\nminimum irradiation respectively). Moreover, the source can be fully\nshielded, allowing one to access the irradiation zone and to study the\ndetector behavior without background radiation.\n\nThe ALICE detector is 50 × 50 cm2 ALICE-like RPC prototype (made\nwith the same construction process as well as with the same features\nas a real-life MID RPC). It is equipped with two perpendicular planes\nof 16 strips each (with a pitch of ≈3 cm). Fig. 1 reports a sketch of\nthe experimental setup. Its main components are: the gas mixing and\ndistribution system (4 Mass Flow Controllers to regulate the flow of\neach gas mixture component and a humidifier to add water vapour\nto the mixture, up to 40% relative humidity), the high voltage system\n(a CAEN SY1527 mainframe1 and A1526P2 high voltage board), the\nreadout system, which can either be VME TDCs3 coupled with the\nALICE MID front-end discriminators (FEERIC) [4] or a CAEN digitizer4\n\ndirectly connected to the readout strips. Lastly, the DAQ machine\n\n1 https://www.caen.it/subfamilies/mainframes/.\n2 https://www.caen.it/products/a1526/.\n3 V1190 with 128 input channels and time resolution of 100 ps.\n4 DT5742, 16 input channels, 12 bit resolution and 1, 2.5 and 5 Gs/s\n\nsampling rate.\n\nhttps://www.caen.it/subfamilies/mainframes/\nhttps://www.caen.it/products/a1526/\n\n\nNuclear Inst. and Methods in Physics Research, A 1067 (2024) 169672L. Quaglia et al.\nTable 1\nComposition of the gas mixtures used in the tests described.\nName C2H2F4 % HFO % CO2 % i-C4H10 % SF6 %\n\nSTD 95.2 0 0 4.5 0.3\nMIX0 0 0 95 4 1\nMIX1 0 10 85 4 1\nMIX2 0 20 75 4 1\nMIX3 0 25 69 5 1\nMIX4 0 30 65 4 1\nMIX5 0 35 60 4 1\nMIX6 0 40 55 4 1\n\nFig. 2. Efficiency as a function of the effective high voltage without gamma\nbackground. Results obtained when the readout strips are coupled directly to the\ndigitizer.\n\nsupervising the whole data-taking procedure (as well as the continuous\nlogging of relevant environmental parameters) is also shown in the\nfigure.\n\nA total of seven low-GWP candidate mixtures has been tested,\ntogether with the mixture currently employed by CMS for reference. Ta-\nble 1 reports the composition of the different beam-tested gas mixtures\n(MIX0-6 for the low-GWP and STD for the reference one).\n\n3. Results\n\nSection 3.1 describes the RPC response to the muon beam in the\nabsence of 𝛾 background (source-off) while Section 3.2 reports the\nresults for varying levels of 𝛾 background (source-on)\n\n3.1. Source-off results\n\nThe first parameter that has been studied in the beam test is the\nRPC efficiency without any gamma background from the 137Cs source.\nThis value has been computed using both the digitizer and the FEERIC\nfront-end electronics. Fig. 2 shows the efficiency curves obtained when\nthe digitizer was used. In this case, the threshold was set on the signal\namplitude. A time interval where no muon signal is expected was\nidentified as the ‘‘noise window’’ and the RMS of the signal amplitude\nwas calculated in this interval. Then, if the signal amplitude, in a time\nregion where a muon-induced signal is expected, is above five times\nthe RMS calculated earlier(which usually translates to ≈1.5 mV), the\nRPC is considered efficient. Fig. 3 reports the efficiency trend when\nthe FEERIC front-end electronics are used in combination with the VME\nTDCs (in this case only the STD and two of the seven mentioned low-\nGWP mixtures have been tested), the threshold was set to ≈150 fC\nbefore amplification. In general, the efficiency is calculated as the ratio\nbetween the number of signals above the thresholds and the total\nnumber of muon triggers.\n\nNote that the efficiency is shown as a function of the effective high\nvoltage (HV ), i.e. the voltage corrected for temperature and pressure\n3\n\n𝑒𝑓𝑓\nFig. 3. Efficiency as a function of the effective high voltage without gamma back-\nground. Results obtained when the readout strips are connected to the FEERIC\ndiscriminators.\n\nFig. 4. Prompt charge distributions at the HV𝑒𝑓𝑓 closest to the estimated WP for\nselected gas mixtures.\n\nvariations, to keep the gain constant, according to the formula reported\nin [12].\n\nIn both cases, the efficiency curves have been interpolated using the\nlogistic function, reported in Eq. (1)\n\n𝜖(𝐻𝑉 ) =\n𝜖𝑚𝑎𝑥\n\n1 + 𝑒−𝜆(𝐻𝑉 −𝐻𝑉50)\n(1)\n\nwhere 𝜖𝑚𝑎𝑥 represents the maximum asymptotic efficiency reached by\nthe detector, 𝜆 is related to the steepness of the curve and HV50 is\nthe voltage where the efficiency reaches 50% of its maximum. These\nparameters are used to extract the working point (WP, i.e. the voltage\nwhich grants full efficiency) as WP= 𝑙𝑜𝑔(19)\n\n𝜆 +HV50 + 150 V, according\nto [12].\n\nBy looking at both Figs. 2 and 3, one sees that if the HFO concen-\ntration increases, so does the WP (≈1 kV for every 10% HFO added to\nthe mixture). Moreover, the plateau efficiency reaches lower values if\nthe HFO concentration is below 20%. This could probably be explained\nby the lower number of primary electron-ion pairs produced by a MIP\ncrossing CO2 with respect to crossing C2H2F4 [13].\n\nAnother useful quantity, which can be computed when the RPC\nanalog signals are directly sent to a digitizer, and the full waveform\nof each hit is saved, is the signal prompt charge. This quantity is the\ntime integral of the waveform and it has been computed following\nthe procedure described in [14]. Fig. 4 shows the distribution of this\nquantity at the HV𝑒𝑓𝑓 closest to the WP estimated earlier.\n\nIn general, two distinct populations (separated at the ≈20 pC) can\nbe observed; the one below 20 pC represents the avalanche signals\n\n\n\nNuclear Inst. and Methods in Physics Research, A 1067 (2024) 169672L. Quaglia et al.\nFig. 5. Efficiency and large signal contamination as a function of the effective high\nvoltage for increasing 𝛾 background rates for the MIX2 mixture.\n\n(with smaller charge content) while the one above refers to the, so-\ncalled, streamers (larger signals due to avalanche degeneration). The\nSTD gas mixture (in black) shows a single, well-defined peak and almost\nno streamers. For what concerns the low-GWP mixtures, one sees that\nfor lower HFO concentrations the avalanche peak is shifted towards\nhigher values and the amount of streamers is higher (this translates\nto an increase of the absorbed current of ≈1.6/1.7 times with respect\nto the STD gas mixture). If the HFO concentration is increased (going\nfrom MIX0 to MIX6) the avalanche peak moves towards smaller values\nand the number of streamers also decreases, this is due to a quenching\neffect of more HFO in the mixture.\n\n3.2. Source-on results\n\nThe study of the RPC response to the muon beam, when exposed to\na high intensity photon flux from the 137Cs source, is useful to simulate\nreal-life operating conditions at the LHC. The expected background rate\nfor the MID RPCs, during LHC Run 3 and 4, is ≈100 Hz/cm2 [15], for\nthe most exposed RPC during the Pb-Pb data-taking periods.\n\nFig. 5 shows the efficiency (measured using the digitizer), as well\nas the streamer contamination (calculated as the ratio between the\nnumber of signals with a charge above 20 pC and the total number\nof signals), as a function of HV𝑒𝑓𝑓 for the MIX2 mixture, at increasing\nlevels of 𝛾 background (from o up to 200 Hz/cm2)\n\nThree main effects can be pointed out: if the 𝛾 background increases,\nthe efficiency curves tend to shift towards higher voltages, the plateau\nefficiency decreases and the streamer contamination is reduced. A\npossible explanation for this effect is that, when the 𝛾 background\nincreases, so does the current absorbed by the RPC. This current flows\nthrough all the detector elements, including the resistive electrodes.\nWhen it does so, it leads to an ohmic voltage drop across them, leading\nto a decrease of the high voltage effectively applied to the gas, hence\nto a lower gain. All the three effects highlighted earlier seem to point\nto a gain decrease.\n\nSince the current-induced voltage drop is ohmic, one can calculate it\nas the product between the resistance of the electrodes and the flowing\ncurrent. The latter is measured during data-taking while the former can\nbe estimated using the Ar method [16]. Using those quantities one can\ncalculate the actual HV applied to the gas as: HV𝑔𝑎𝑠 = HV − R × I where\nHV is the high voltage measured, R is the electrodes resistance and I\nthe flowing current.\n\nFig. 6 shows the efficiency and large signal (streamer) probability\nas a function of HV𝑔𝑎𝑠 and one can see how the curves are now\nsuperimposed (the same is true also for other mixtures, as reported\nin [14]).\n4\n\nFig. 6. Efficiency and large signal contamination as a function of actual high voltage\napplied to the gas, for increasing 𝛾 background rates for the MIX2 mixture.\n\n4. Conclusions and outlook\n\nSeveral low-GWP mixtures, where C2H2F4 is replaced with different\nratios of HFO/CO2 have been beam-tested at the CERN GIF++. First of\nall, the working point of the detectors increases by ∼1 kV for every 10%\nHFO added to the mixture; secondly, the large signal contamination de-\ncreases if the HFO concentration increases; mixtures with 30–40% HFO\nprovide values of streamer contamination similar to the ones given by\nthe STD gas mixture, but streamers grow faster for voltages above the\nWP, reducing the safe operating region.\n\nWhen exposed to gamma background, the efficiency curves shift\nto higher voltages and the maximum efficiency decreases (these ob-\nservations can be explained by the current-induced voltage drop on\nthe bakelite electrodes). In particular, for ALICE-like background rates\n(≈100 Hz/cm2) the efficiency drop is ∼1 percentage point (pp) for the\nstandard gas mixture and ∼3–4 pp for the low-GWP alternatives.\n\nThe results obtained from the beam tests are promising and a long-\nterm aging test is now ongoing at GIF++, in order to study the stability\nof the detector response when operated for a long time with low-GWP\nalternatives (preliminary results of these studies are reported in [17]).\n\nDeclaration of competing interest\n\nThe authors declare that they have no known competing finan-\ncial interests or personal relationships that could have appeared to\ninfluence the work reported in this paper.\n\nFunding\n\nThis work is part of the AIDA Innova project, which received fund-\ning from the European Union’s Horizon 2020 Research and Innovation\nprogramme under GA n.101004761. In particular, this work is part of\nthe Working Package 7.2 (Multigap RPCs (MRPCs) for fast timing and\nEco-friendly gas mixtures for RPCs)\n\nReferences\n\n[1] ALICE collaboration, ALICE: Technical proposal for a large ion collider experi-\nment at the CERN LHC, LHC technical proposal. ALICE, 1995, https://cds.cern.\nch/record/293391.\n\n[2] T. Matsui, H. Satz, 𝐽∕𝜓 Suppression by Quark-Gluon plasma formation, Phys.\nLett. B 178 (1986) 416–422, http://dx.doi.org/10.1016/0370-2693(86)91404-8.\n\n[3] ALICE collaboration, ALICE technical design report of the dimuon forward\nspectrometer, CERN/LHCC 99-22, 1999.\n\n[4] S. 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B 158 (2006) 143–148, http://dx.doi.org/10.1016/j.nuclphysbps.\n2006.07.025.\n\n[17] L. Quaglia, et al., Preliminary results on the long term operation of RPCs with\neco-friendly gas mixtures under irradiation at the CERN Gamma irradiation\nfacility, EPJ Plus (2024) submitted for publication.\n\nhttp://dx.doi.org/10.1393/ncc/i2021-21070-1\nhttp://dx.doi.org/10.1393/ncc/i2021-21070-1\nhttp://dx.doi.org/10.1393/ncc/i2021-21070-1\nhttp://dx.doi.org/10.1088/1748-0221/15/04/C04039\nhttp://dx.doi.org/10.1088/1748-0221/15/11/C11003\nhttp://dx.doi.org/10.1088/1748-0221/15/11/C11003\nhttp://dx.doi.org/10.1088/1748-0221/15/11/C11003\nhttps://arxiv.org/abs/1505.01648\nhttp://dx.doi.org/10.1016/j.nima.2023.168757\nhttp://dx.doi.org/10.1016/j.nima.2023.168757\nhttp://dx.doi.org/10.1016/j.nima.2023.168757\nhttp://dx.doi.org/10.1016/j.nima.2017.05.045\nhttp://dx.doi.org/10.1016/j.nima.2017.05.045\nhttp://dx.doi.org/10.1016/j.nima.2017.05.045\nhttp://dx.doi.org/10.1088/1748-0221/14/11/C11012\nhttp://dx.doi.org/10.1088/1748-0221/14/11/C11012\nhttp://dx.doi.org/10.1088/1748-0221/14/11/C11012\nhttp://dx.doi.org/10.1017/CBO9781107337701\nhttps://cds.cern.ch/record/2861614\nhttps://cds.cern.ch/record/2861614\nhttps://cds.cern.ch/record/2861614\nhttp://dx.doi.org/10.1088/1748-0221/14/06/C06011\nhttp://dx.doi.org/10.1016/j.nuclphysbps.2006.07.025\nhttp://dx.doi.org/10.1016/j.nuclphysbps.2006.07.025\nhttp://dx.doi.org/10.1016/j.nuclphysbps.2006.07.025\nhttp://refhub.elsevier.com/S0168-9002(24)00598-9/sb17\nhttp://refhub.elsevier.com/S0168-9002(24)00598-9/sb17\nhttp://refhub.elsevier.com/S0168-9002(24)00598-9/sb17\nhttp://refhub.elsevier.com/S0168-9002(24)00598-9/sb17\nhttp://refhub.elsevier.com/S0168-9002(24)00598-9/sb17\n\n\tIn-beam performance of a Resistive Plate Chamber operated with eco-friendly gas mixtures\n\tIntroduction\n\tExperimental setup\n\tResults\n\tSource-off results\n\tSource-on results\n\n\tConclusions and outlook\n\tDeclaration of competing interest\n\t\n\tReferences"},"fulltext":true,"key":"5224af25b5ed8535a0717d3ad7178b2a","url":"https://inspirehep.net/files/5224af25b5ed8535a0717d3ad7178b2a"}],"authors":[{"affiliations_identifiers":[{"schema":"ROR","value":"https://ror.org/01vj6ck58"}],"raw_affiliations":[{"source":"Elsevier B.V.","value":"INFN Sezione di Torino, Via P. 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One of the probes for QGP study are quarkonia and open heavy flavour, of which ALICE exploits the muonic decay. A set of Resistive Plate Chambers (RPCs), placed in the forward rapidity region of the ALICE detector, is used for muon identification purposes. The correct operation of these detectors is ensured by the choice of the proper gas mixture. Currently they are operated with a mixture of C$_{2}$H$_{2}$F$_{4}$, i-C$_{4}$H$_{10}$ and SF$_{6}$ but, starting from 2017, new EU regulations have enforced a progressive phase-out of C$_{2}$H$_{2}$F$_{4}$ because of its large Global Warming Potential (GWP), making it difficult and costly to purchase. CERN asked LHC experiments to reduce greenhouse gases emissions, to which RPC operation contributes significantly. A possible candidate for C$_{2}$H$_{2}$F$_{4}$ replacement is the C$_{3}$H$_{2}$F$_{4}$ (diluted with other gases, such as CO$_{2}$), which has been extensively tested using cosmic rays. Promising gas mixtures have been devised; the next crucial steps are the detailed in-beam characterization of such mixtures as well as the study of their performance under increasing irradiation levels. This contribution will describe the methodology and results of beam tests carried out at the CERN GIF++ (equipped with a high activity $^{137}$Cs source and muon beam) with an ALICE-like RPC prototype, operated with several mixtures with varying proportions of CO$_{2}$, C$_{3}$H$_{2}$F$_{4}$, i-C$_{4}$H$_{10}$ and SF$_{6}$ . 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Currently they are operated with a mixture of C2H2F4, i-C4H10 and SF6 but, starting from 2017, new EU regulations have enforced a progressive phase-out of C2H2F4 because of its large Global Warming Potential (GWP), which is making it difficult and costly to purchase. Moreover, CERN asked LHC experiments to reduce greenhouse gases emissions, to which RPC operation contributes significantly. A possible candidate for C2H2F4 replacement is the C3H2F4 (diluted with other gases, such as CO2), which has been extensively tested using cosmic muons. Promising gas mixtures have been devised; the next crucial steps are the detailed in-beam characterization of such mixtures as well as the study of their performance under increasing irradiation levels. This contribution will describe the methodology and results of beam tests carried out at the CERN Gamma Irradiation Facility (equipped with a high activity <sup loc=\"pre\">137</sup>Cs source and muon beam) with an ALICE-like RPC prototype, operated with several mixtures with varying proportions of CO2, C3H2F4, i-C4H10 and SF6 . Absorbed currents, efficiencies, prompt charges, cluster sizes, time resolutions and rate capabilities will be presented, both from digitized (for detailed shape and charge analysis) and discriminated (using the same front-end electronics as employed in ALICE) signals.","abstract_source_suggest":{"input":"Elsevier B.V."}}],"primary_arxiv_category":["hep-ex"],"titles":[{"source":"arXiv","title":"In-beam performance of a Resistive Plate Chamber operated with eco-friendly gas mixtures"},{"source":"Elsevier B.V.","title":"In-beam performance of a Resistive Plate Chamber operated with eco-friendly gas mixtures"}],"imprints":[{"date":"2024-08-02"}],"curated":true},"updated":"2025-08-29T18:26:02.155856+00:00"},{"id":"2029424","created":"2022-02-08T03:22:38.810203+00:00","links":{"bibtex":"https://inspirehep.net/api/literature/2029424?format=bibtex","latex-eu":"https://inspirehep.net/api/literature/2029424?format=latex-eu","latex-us":"https://inspirehep.net/api/literature/2029424?format=latex-us","json":"https://inspirehep.net/api/literature/2029424?format=json","json-expanded":"https://inspirehep.net/api/literature/2029424?format=json-expanded","cv":"https://inspirehep.net/api/literature/2029424?format=cv","citations":"https://inspirehep.net/api/literature/?q=refersto%3Arecid%3A2029424"},"metadata":{"citation_count":1,"publication_info":[{"journal_volume":"2022","artid":"303","year":2022,"journal_record":{"$ref":"https://inspirehep.net/api/journals/2072737"},"page_start":"303","journal_title":"JAIS"}],"documents":[{"filename":"document","fulltext":true,"key":"50c2ab999b4ef6458967c9b2f4bdb419","url":"https://inspirehep.net/files/50c2ab999b4ef6458967c9b2f4bdb419"}],"authors":[{"raw_affiliations":[{"value":"Centre for Cosmology, Particle Physics and Phenomenology (CP3), Universite catholique de Louvain, Louvain-la-Neuve, Belgium"}],"full_name_unicode_normalized":"moussawi, marwa al","full_name":"Moussawi, Marwa Al","record":{"$ref":"https://inspirehep.net/api/authors/1933860"},"last_name":"Moussawi","affiliations":[{"curated_relation":true,"record":{"$ref":"https://inspirehep.net/api/institutions/910783"},"value":"Louvain U., CP3"}],"ids":[{"schema":"INSPIRE BAI","value":"M.Moussawi.1"}],"signature_block":"MASm","uuid":"e319660f-4ce3-44d6-84e4-9d4476490982","first_name":"Marwa Al","recid":1933860},{"raw_affiliations":[{"value":"Centre for Cosmology, Particle Physics and Phenomenology (CP3), Universite catholique de Louvain, Louvain-la-Neuve, Belgium"}],"full_name_unicode_normalized":"basnet, s.","full_name":"Basnet, S.","curated_relation":true,"record":{"$ref":"https://inspirehep.net/api/authors/2791174"},"last_name":"Basnet","affiliations":[{"curated_relation":true,"record":{"$ref":"https://inspirehep.net/api/institutions/910783"},"value":"Louvain U., CP3"}],"ids":[{"schema":"INSPIRE BAI","value":"Samip.Basnet.1"}],"signature_block":"BASNATs","uuid":"56c63374-46cc-4ece-85fb-3166caa0c404","first_name":"S.","recid":2791174},{"raw_affiliations":[{"value":"INFN sez. di Firenze, Florence, Italy"}],"full_name_unicode_normalized":"bonechi, l.","full_name":"Bonechi, L.","record":{"$ref":"https://inspirehep.net/api/authors/1033315"},"last_name":"Bonechi","affiliations":[{"curated_relation":true,"record":{"$ref":"https://inspirehep.net/api/institutions/902880"},"value":"INFN, Florence"}],"ids":[{"schema":"INSPIRE BAI","value":"L.Bonechi.1"}],"signature_block":"BANACl","uuid":"0d77cf54-be12-41da-a4c5-8bf8991bfa29","first_name":"L.","recid":1033315},{"raw_affiliations":[{"value":"University of Naples Federico II, Napoli, Italy; 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A detailed Monte Carlo simulation framework is necessary in order to investigate the effects of the experimental constraints and to perform comparisons with the actual observations. Our Monte Carlo setup combines a variety of Monte Carlo programsthat address different aspects of cosmic muon simulation, from muon generation in the Earth’s upper atmosphere to the response of the detector, including the interactions with the material of the volcano. Wewill elaborate on the rationale for our technical choices, including the trade-off between speed and accuracy, and on the lessons learned, which are of general interest for similar use cases in muon radiography","abstract_source_suggest":{"input":"Andromda"}},{"source":"arXiv","value":"The MUon RAdiography of VESuvius (MURAVES) project aims at the study of the summital cone of Mt. Vesuvius, an active and hazardous volcano near Naples, Italy. A detailed Monte Carlo simulation framework is necessary in order to investigate the effects of the experimental constraints and to perform comparisons with the actual observations. Our Monte Carlo setup combines a variety of Monte Carlo programs that address different aspects of cosmic muon simulation, from muon generation in the Earth's upper atmosphere to the response of the detector, including the interactions with the material of the volcano. We will elaborate on the rationale for our technical choices, including trade-off between speed and accuracy, and on the lessons learned, which are of general interest for similar use cases in muon radiography.","abstract_source_suggest":{"input":"arXiv"}}],"primary_arxiv_category":["physics.ins-det"],"titles":[{"source":"Andromda","title":"The Simulations Chain of the MURAVES Experiment"},{"source":"arXiv","title":"The simulations chain of the MURAVES experiment"}],"imprints":[{"date":"2022-07-14"}],"curated":false},"updated":"2024-06-04T13:57:21.249422+00:00"}],"total":3689},"links":{"self":"https://inspirehep.net/api/literature/?q=aff%20Gent%20U.&size=10&page=1","next":"https://inspirehep.net/api/literature/?q=aff%20Gent%20U.&size=10&page=2","bibtex":"https://inspirehep.net/api/literature/?q=aff%20Gent%20U.&size=10&page=1&format=bibtex","latex-eu":"https://inspirehep.net/api/literature/?q=aff%20Gent%20U.&size=10&page=1&format=latex-eu","latex-us":"https://inspirehep.net/api/literature/?q=aff%20Gent%20U.&size=10&page=1&format=latex-us","json":"https://inspirehep.net/api/literature/?q=aff%20Gent%20U.&size=10&page=1&format=json","json-expanded":"https://inspirehep.net/api/literature/?q=aff%20Gent%20U.&size=10&page=1&format=json-expanded","cv":"https://inspirehep.net/api/literature/?q=aff%20Gent%20U.&size=10&page=1&format=cv"}}