application/xmlSearch for a Higgs boson in the diphoton final state using the full CDF data set from [formula omitted] collisions at [formula omitted]CDF CollaborationT. AaltonenB. Álvarez GonzálezS. AmerioD. AmideiA. AnastassovA. AnnoviJ. AntosG. ApollinariJ.A. AppelT. ArisawaA. ArtikovJ. AsaadiW. AshmanskasB. AuerbachA. AurisanoF. AzfarW. BadgettT. BaeA. Barbaro-GaltieriV.E. BarnesB.A. BarnettP. BarriaP. BartosM. BauceF. BedeschiS. BehariG. BellettiniJ. BellingerD. BenjaminA. BeretvasA. BhattiD. BiselloI. BizjakK.R. BlandB. BlumenfeldA. BocciA. BodekD. BortolettoJ. BoudreauA. BoveiaL. BrigliadoriC. BrombergE. BruckenJ. BudagovH.S. BuddK. BurkettG. BusettoP. BusseyA. BuzatuA. CalambaC. CalanchaS. CamardaM. CampanelliM. CampbellF. CanelliB. CarlsD. CarlsmithR. CarosiS. CarrilloS. CarronB. CasalM. CasarsaA. CastroP. CatastiniD. CauzV. CavaliereM. Cavalli-SforzaA. CerriL. CerritoY.C. ChenM. ChertokG. ChiarelliG. ChlachidzeF. ChlebanaK. ChoD. ChokheliW.H. ChungY.S. ChungM.A. CiocciA. ClarkC. ClarkeG. CompostellaM.E. ConveryJ. ConwayM. CorboM. CordelliC.A. CoxD.J. CoxF. CrescioliJ. CuevasR. CulbertsonD. DagenhartN. dʼAscenzoM. DattaP. de BarbaroM. DellʼOrsoL. DemortierM. DeninnoF. DevotoM. dʼErricoA. Di CantoB. Di RuzzaJ.R. DittmannM. DʼOnofrioS. DonatiP. DongM. DorigoT. DorigoK. EbinaA. ElaginA. EppigR. ErbacherS. ErredeN. ErshaidatR. EusebiS. FarringtonM. FeindtJ.P. FernandezR. FieldG. FlanaganR. ForrestM.J. FrankM. FranklinJ.C. FreemanY. FunakoshiI. FuricM. GallinaroJ.E. GarciaA.F. GarfinkelP. GarosiH. GerberichE. GerchteinS. GiaguV. GiakoumopoulouP. GiannettiK. GibsonC.M. GinsburgN. GiokarisP. GirominiG. GiurgiuV. GlagolevD. GlenzinskiM. GoldD. GoldinN. GoldschmidtA. GolossanovG. GomezG. Gomez-CeballosM. GoncharovO. GonzálezI. GorelovA.T. GoshawK. GoulianosS. GrinsteinC. Grosso-PilcherR.C. GroupJ. Guimaraes da CostaS.R. HahnE. HalkiadakisA. HamaguchiJ.Y. HanF. HappacherK. HaraD. HareM. HareR.F. HarrK. HatakeyamaC. HaysM. HeckJ. HeinrichM. HerndonS. HewamanageA. HockerW. HopkinsD. HornS. HouR.E. HughesM. HurwitzU. HusemannN. HussainM. HusseinJ. HustonG. IntrozziM. IoriA. IvanovE. JamesD. JangB. JayatilakaE.J. JeonS. JindarianiM. JonesK.K. JooS.Y. JunT.R. JunkT. KamonP.E. KarchinA. KasmiY. KatoW. KetchumJ. KeungV. KhotilovichB. KilminsterD.H. KimH.S. KimJ.E. KimM.J. KimS.B. KimS.H. KimY.K. KimY.J. KimN. KimuraM. KirbyS. KlimenkoK. KnoepfelK. KondoD.J. KongJ. KonigsbergA.V. KotwalM. KrepsJ. KrollD. KropM. KruseV. KrutelyovT. KuhrM. KurataS. KwangA.T. LaasanenS. LamiS. LammelM. LancasterR.L. LanderK. LannonA. LathG. LatinoT. LeCompteE. LeeH.S. LeeJ.S. LeeS.W. LeeS. LeoS. LeoneJ.D. LewisA. LimosaniC.-J. LinM. LindgrenE. LipelesA. ListerD.O. LitvintsevC. LiuH. LiuQ. LiuT. LiuS. LockwitzA. LoginovD. LucchesiJ. LueckP. LujanP. LukensG. LunguJ. LysR. LysakR. MadrakK. MaeshimaP. MaestroS. MalikG. MancaA. Manousakis-KatsikakisF. MargaroliC. MarinoM. MartínezP. MastrandreaK. MateraM.E. MattsonA. MazzacaneP. MazzantiK.S. McFarlandP. McIntyreR. McNultyA. MehtaP. MehtalaC. MesropianT. MiaoD. MietlickiA. MitraH. MiyakeS. MoedN. MoggiM.N. MondragonC.S. MoonR. MooreM.J. MorelloJ. MorlockP. Movilla FernandezA. MukherjeeTh. MullerP. MuratM. MussiniJ. NachtmanY. NagaiJ. NaganomaI. NakanoA. NapierJ. NettC. NeuM.S. NeubauerJ. NielsenL. NodulmanS.Y. NohO. NorniellaL. OakesS.H. OhY.D. OhI. OksuzianT. OkusawaR. OravaL. OrtolanS. Pagan GrisoC. PagliaroneE. PalenciaV. PapadimitriouA.A. ParamonovJ. PatrickG. PaulettaM. PauliniC. PausD.E. PellettA. PenzoT.J. PhillipsG. PiacentinoE. PianoriJ. PilotK. PittsC. PlagerL. PondromS. PoprockiK. PotamianosF. ProkoshinA. PrankoF. PtohosG. PunziA. RahamanV. RamakrishnanN. RanjanI. RedondoP. RentonM. RescignoT. RiddickF. RimondiL. RistoriA. RobsonT. RodrigoT. RodriguezE. RogersS. RolliR. RoserF. RuffiniA. RuizJ. RussV. RusuA. SafonovW.K. SakumotoY. SakuraiL. SantiK. SatoV. SavelievA. Savoy-NavarroP. SchlabachA. SchmidtE.E. SchmidtT. SchwarzL. ScodellaroA. ScribanoF. ScuriS. SeidelY. SeiyaA. SemenovF. SforzaS.Z. ShalhoutT. ShearsP.F. ShepardM. ShimojimaM. ShochetI. Shreyber-TeckerA. SimonenkoP. SinervoK. SliwaJ.R. SmithF.D. SniderA. SohaV. SorinH. SongP. SquillaciotiM. StancariR. St. DenisB. StelzerO. Stelzer-ChiltonD. StentzJ. StrologasG.L. StryckerY. SudoA. SukhanovI. SuslovK. TakemasaY. TakeuchiJ. TangM. TecchioP.K. TengJ. ThomJ. ThomeG.A. ThompsonE. ThomsonD. TobackS. TokarK. TollefsonT. TomuraD. TonelliS. TorreD. TorrettaP. TotaroM. TrovatoF. UkegawaS. UozumiA. VarganovF. VázquezG. VelevC. VellidisM. VidalI. VilaR. VilarJ. VizánM. VogelG. VolpiP. WagnerR.L. WagnerT. WakisakaR. WallnyS.M. WangA. WarburtonD. WatersW.C. Wester IIID. WhitesonA.B. WicklundE. WicklundS. WilburF. WickH.H. WilliamsJ.S. WilsonP. WilsonB.L. WinerP. WittichS. WolbersH. WolfeT. WrightX. WuZ. WuK. YamamotoD. YamatoT. YangU.K. YangY.C. YangW.-M. YaoG.P. YehK. YiJ. YohK. YoritaT. YoshidaG.B. YuI. YuS.S. YuJ.C. YunA. ZanettiY. ZengC. ZhouS. ZucchelliPhysics Letters B 717 (2012) 173-181. doi:10.1016/j.physletb.2012.08.051journalPhysics Letters BCopyright © 2012 Elsevier B.V. All rights reserved.Elsevier B.V.0370-26937171-322 October 20122012-10-22173-18117318110.1016/j.physletb.2012.08.051http://dx.doi.org/10.1016/j.physletb.2012.08.051doi:10.1016/j.physletb.2012.08.051http://vtw.elsevier.com/data/voc/oa/OpenAccessStatus#Full2013-07-16T20:28:18Zhttp://vtw.elsevier.com/data/voc/oa/SponsorType#Otherhttp://creativecommons.org/licenses/by/3.0/

Journals

S300.3

PLB28840S0370-2693(12)00917-310.1016/j.physletb.2012.08.051Elsevier B.V.Experiments

Fig. 1

The invariant mass distribution of CC photon pairs in the data is shown for (a) the entire pTγγ region used in the SM Higgs boson diphoton resonance search and (b) the highest-pTγγ region (the most sensitive region) used in the hf diphoton resonance search. Each distribution shows a fit to the data for the hypothesis of mH=125 GeV/c2, for which the signal region centered at 125 GeV/c2 is excluded from the fit. The expected shape of the signal from simulation is shown in the inset of (a). A Gaussian fit to the 125 GeV/c2 signal simulation yields a 1σ resolution of less than 4 GeV/c2.

Fig. 2

For a Higgs boson mass of 125 GeV/c2, the reweighting function obtained from the ratio of the pTγγ distribution in pythia to the pTγγ distribution in prompt diphoton data, for events with (a) zero jets and (b) at least one jet. In both plots, the best fit to the pythia-to-data ratio points is given by a solid curve. The other two curves show the systematic uncertainty of the fit.

Fig. 3

For a Higgs boson mass of 125 GeV/c2, a comparison of the data to the background prediction in (a) the pTγγ distribution for the CC0 category and (b) the distribution of the sum of the reconstructed jet ET for the CCJ category. The expected SM Higgs boson signal for the three production processes is multiplied by a factor of 20.

Fig. 4

For a Higgs boson mass of 125 GeV/c2, a comparison of the NN output distributions for the data and the background prediction for (a) the CC0 category and (b) the CCJ category. The expected SM Higgs boson signal for the three production processes is multiplied by a factor of 20.

Fig. 5

(a) As a function of mH, the 95% C.L. upper limit on the cross section times branching ratio for the SM Higgs boson decay to two photons, relative to the SM prediction. (b) The 95% C.L. upper limit on the branching ratio for the fermiophobic Higgs boson decay to two photons as a function of mhf. For reference, the 95% C.L. limits from LEP are also included. The shaded regions represent the 68% C.L. and 95% C.L. bands for the observed limit with respect to the expected limit based on the distribution of simulated experimental outcomes.

Table 1

Expected and observed 95% C.L. upper limits on the production cross section multiplied by the H→γγ branching ratio relative to the SM prediction for the most sensitive category (CC) using the NN discriminant. For comparison, values for the CC category are also provided based on the diphoton resonance technique, which uses the mγγ shape as a discriminant for setting limits. The expected and observed 95% C.L. upper limits on the hf branching ratio (in %) are provided in parentheses, based on both the NN discriminant and diphoton resonance technique for the CC category.

mH (GeV/c2)NN discriminantmγγ discriminantExpectedObservedExpectedObserved10013.9 (4.6)10.6 (4.7)15.1 (5.1)11.3 (3.5)10512.6 (4.6)13.0 (6.1)14.1 (5.5)10.6 (5.1)11011.9 (5.2)11.8 (5.5)13.5 (5.8)11.4 (6.3)11511.4 (5.2)14.1 (6.7)12.9 (6.2)15.4 (6.0)12011.3 (5.5)23.2 (9.2)12.8 (6.6)22.2 (7.3)12511.7 (6.4)20.5 (10.2)12.9 (6.9)21.2 (8.0)13012.5 (7.0)13.1 (6.5)13.9 (7.3)16.0 (6.0)13513.7 (7.7)15.0 (6.0)15.3 (7.9)17.2 (4.9)14016.5 (8.2)20.4 (8.1)17.5 (8.3)25.4 (5.9)14518.5 (8.4)27.4 (11.8)21.2 (8.6)24.3 (8.8)15025.7 (8.7)17.1 (7.0)28.2 (9.0)15.1 (8.4)Table 2

Expected and observed 95% C.L. upper limits on the production cross section times branching ratio relative to the SM prediction, the production cross section times branching ratio with theoretical cross section uncertainties removed, and the hf branching ratio. The fermiophobic benchmark model prediction for B(hf→γγ) is also shown for comparison.

mH (GeV/c2)100105110115120125130135140145150σ×B(H→γγ)/SMExpected12.210.910.69.79.79.910.511.614.016.021.3Observed10.411.07.710.921.317.012.912.918.321.214.9σ×B(H→γγ) (fb)Expected45.139.037.231.829.727.225.524.023.020.420.2Observed37.940.626.835.966.647.731.526.530.727.213.9B(hf→γγ) (%)Expected3.73.84.34.34.65.35.76.16.66.77.1Observed4.95.13.54.85.94.95.37.98.48.35.0Fermiophobic prediction18.510.46.03.72.31.61.10.80.50.40.3Search for a Higgs boson in the diphoton final state using the full CDF data set from pp¯ collisions at s=1.96 TeV

CDF Collaboration

Aaltonen

Álvarez González

Amerio

Amidei

Anastassov

Annovi

Antos

Apollinari

J.A.

Appel

Arisawa

Artikov

Asaadi

Ashmanskas

Auerbach

Aurisano

Azfar

Badgett

Bae

Barbaro-Galtieri

V.E.

Barnes

B.A.

Barnett

Barria

Bartos

Bauce

Bedeschi

Behari

Bellettini

Bellinger

Benjamin

Beretvas

Bhatti

Bisello

Bizjak

K.R.

Bland

Blumenfeld

Bocci

Bodek

Bortoletto

Boudreau

Boveia

Brigliadori

Bromberg

Brucken

Budagov

H.S.

Budd

Burkett

Busetto

Bussey

Buzatu

Calamba

Calancha

Camarda

Campanelli

Campbell

Canelli

Carls

Carlsmith

Carosi

Carrillo

Carron

Casal

Casarsa

Castro

Catastini

Cauz

Cavaliere

Cavalli-Sforza

Cerri

Cerrito

Y.C.

Chen

Chertok

Chiarelli

Chlachidze

Chlebana

Cho

Chokheli

W.H.

Chung

Y.S.

Chung

M.A.

Ciocci

Clark

Clarke

Compostella

M.E.

Convery

Conway

Corbo

Cordelli

C.A.

Cox

D.J.

Cox

Crescioli

Cuevas

Culbertson

Dagenhart

dʼAscenzo

Datta

de Barbaro

DellʼOrso

Demortier

Deninno

Devoto

dʼErrico

Di Canto

Di Ruzza

J.R.

Dittmann

DʼOnofrio

Donati

Dong

Dorigo

Ebina

Elagin

Eppig

Erbacher

Errede

Ershaidat

Eusebi

Farrington

Feindt

J.P.

Fernandez

Field

Flanagan

Forrest

M.J.

Frank

Franklin

J.C.

Freeman

Funakoshi

Furic

Gallinaro

J.E.

Garcia

A.F.

Garfinkel

Garosi

Gerberich

Gerchtein

Giagu

Giakoumopoulou

Giannetti

Gibson

C.M.

Ginsburg

Giokaris

Giromini

Giurgiu

Glagolev

Glenzinski

Gold

Goldin

Goldschmidt

Golossanov

Gomez

Gomez-Ceballos

Goncharov

González

Gorelov

A.T.

Goshaw

Goulianos

Grinstein

Grosso-Pilcher

R.C.

Group

Guimaraes da Costa

S.R.

Hahn

Halkiadakis

Hamaguchi

J.Y.

Han

Happacher

Hara

Hare

R.F.

Harr

Hatakeyama

Hays

Heck

Heinrich

Herndon

Hewamanage

Hocker

Hopkins

Horn

Hou

R.E.

Hughes

Hurwitz

Husemann

Hussain

Hussein

Huston

Introzzi

Iori

Ivanov

James

Jang

Jayatilaka

E.J.

Jeon

Jindariani

Jones

K.K.

Joo

S.Y.

Jun

T.R.

Junk

Kamon

P.E.

Karchin

Kasmi

Kato

Ketchum

Keung

Khotilovich

Kilminster

D.H.

Kim

H.S.

Kim

J.E.

Kim

M.J.

Kim

S.B.

Kim

S.H.

Kim

Y.K.

Kim

Y.J.

Kim

Kimura

Kirby

Klimenko

Knoepfel

Kondo

D.J.

Kong

Konigsberg

A.V.

Kotwal

Kreps

Kroll

Krop

Kruse

Krutelyov

Kuhr

Kurata

Kwang

A.T.

Laasanen

Lami

Lammel

Lancaster

R.L.

Lander

Lannon

Lath

Latino

LeCompte

Lee

H.S.

Lee

J.S.

Lee

S.W.

Lee

Leo

Leone

J.D.

Lewis

Limosani

C.-J.

Lin

Lindgren

Lipeles

Lister

D.O.

Litvintsev

Liu

Lockwitz

Loginov

Lucchesi

Lueck

Lujan

Lukens

Lungu

Lys

Lysak

Madrak

Maeshima

Maestro

Malik

Manca

Manousakis-Katsikakis

Margaroli

Marino

Martínez

Mastrandrea

Matera

M.E.

Mattson

Mazzacane

Mazzanti

K.S.

McFarland

McIntyre

McNulty

Mehta

Mehtala

Mesropian

Miao

Mietlicki

Mitra

Miyake

Moed

Moggi

M.N.

Mondragon

C.S.

Moon

Moore

M.J.

Morello

Morlock

Movilla Fernandez

Mukherjee

Th.

Muller

Murat

Mussini

Nachtman

Nagai

Naganoma

Nakano

Napier

Nett

Neu

M.S.

Neubauer

Nielsen

Nodulman

S.Y.

Noh

Norniella

Oakes

S.H.

Y.D.

Oksuzian

Okusawa

Orava

Ortolan

Pagan Griso

Pagliarone

Palencia

Papadimitriou

A.A.

Paramonov

Patrick

Pauletta

Paulini

Paus

D.E.

Pellett

Penzo

T.J.

Phillips

Piacentino

Pianori

Pilot

Pitts

Plager

Pondrom

Poprocki

Potamianos

Prokoshin

Pranko

Ptohos

Punzi

Rahaman

Ramakrishnan

Ranjan

Redondo

Renton

Rescigno

Riddick

Rimondi

Ristori

Robson

Rodrigo

Rodriguez

Rogers

Rolli

Roser

Ruffini

Ruiz

Russ

Rusu

Safonov

W.K.

Sakumoto

Sakurai

Santi

Sato

Saveliev

Savoy-Navarro

Schlabach

Schmidt

E.E.

Schmidt

Schwarz

Scodellaro

Scribano

Scuri

Seidel

Seiya

Semenov

Sforza

S.Z.

Shalhout

Shears

P.F.

Shepard

Shimojima

Shochet

Shreyber-Tecker

Simonenko

Sinervo

Sliwa

J.R.

Smith

F.D.

Snider

Soha

Sorin

Song

Squillacioti

Stancari

St. Denis

Stelzer

Stelzer-Chilton

Stentz

Strologas

G.L.

Strycker

Sudo

Sukhanov

Suslov

Takemasa

Takeuchi

Tang

Tecchio

P.K.

Teng

Thom

Thome

G.A.

Thompson

Thomson

Toback

Tokar

Tollefson

Tomura

Tonelli

Torre

Torretta

Totaro

Trovato

Ukegawa

Uozumi

Varganov

Vázquez

Velev

Vellidis

⁎

vellidis@fnal.gov

Vidal

Vila

Vilar

Vizán

Vogel

Volpi

Wagner

R.L.

Wagner

Wakisaka

Wallny

S.M.

Wang

Warburton

Waters

W.C.

WesterIII

Whiteson

A.B.

Wicklund

Wilbur

Wick

H.H.

Williams

J.S.

Wilson

B.L.

Winer

Wittich

Wolbers

Wolfe

Wright

Yamamoto

Yamato

Yang

U.K.

Yang

Y.C.

Yang

W.-M.

Yao

G.P.

Yeh

Yoh

Yorita

Yoshida

G.B.

S.S.

J.C.

Yun

Zanetti

Zeng

Zhou

Zucchelli

aInstitute of Physics, Academia Sinica, Taipei, Taiwan 11529, ROCbArgonne National Laboratory, Argonne, IL 60439, USAcUniversity of Athens, 157 71 Athens, GreecedInstitut de Fisica dʼAltes Energies, ICREA, Universitat Autonoma de Barcelona, E-08193, Bellaterra (Barcelona), SpaineBaylor University, Waco, TX 76798, USAfIstituto Nazionale di Fisica Nucleare Bologna, ItalygUniversity of Bologna, I-40127 Bologna, ItalyhUniversity of California Davis, Davis, CA 95616, USAiUniversity of California Los Angeles, Los Angeles, CA 90024, USAjInstituto de Fisica de Cantabria, CSIC–University of Cantabria, 39005 Santander, SpainkCarnegie Mellon University, Pittsburgh, PA 15213, USAlEnrico Fermi Institute, University of Chicago, Chicago, IL 60637, USAmComenius University, 842 48 Bratislava, SlovakianInstitute of Experimental Physics, 040 01 Kosice, SlovakiaoJoint Institute for Nuclear Research, RU-141980 Dubna, RussiapDuke University, Durham, NC 27708, USAqFermi National Accelerator Laboratory, Batavia, IL 60510, USArUniversity of Florida, Gainesville, FL 32611, USAsLaboratori Nazionali di Frascati, Istituto Nazionale di Fisica Nucleare, I-00044 Frascati, ItalytUniversity of Geneva, CH-1211 Geneva 4, SwitzerlanduGlasgow University, Glasgow G12 8QQ, United KingdomvHarvard University, Cambridge, MA 02138, USAwDivision of High Energy Physics, Department of Physics, University of Helsinki and Helsinki Institute of Physics, FIN-00014, Helsinki, FinlandxUniversity of Illinois, Urbana, IL 61801, USAyThe Johns Hopkins University, Baltimore, MD 21218, USAzInstitut für Experimentelle Kernphysik, Karlsruhe Institute of Technology, D-76131 Karlsruhe, GermanyaaCenter for High Energy Physics: Kyungpook National University, Daegu 702-701, Republic of Korea; Seoul National University, Seoul 151-742, Republic of Korea; Sungkyunkwan University, Suwon 440-746, Republic of Korea; Korea Institute of Science and Technology Information, Daejeon 305-806, Republic of Korea; Chonnam National University, Gwangju 500-757, Republic of Korea; Chonbuk National University, Jeonju 561-756, Republic of KoreaabErnest Orlando Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USAacUniversity of Liverpool, Liverpool L69 7ZE, United KingdomadUniversity College London, London WC1E 6BT, United KingdomaeCentro de Investigaciones Energeticas Medioambientales y Tecnologicas, E-28040 Madrid, SpainafMassachusetts Institute of Technology, Cambridge, MA 02139, USAagInstitute of Particle Physics: McGill University, Montréal, Québec, H3A 2T8, Canada; Simon Fraser University, Burnaby, British Columbia, V5A 1S6, Canada; University of Toronto, Toronto, Ontario, M5S 1A7, Canada; TRIUMF, Vancouver, British Columbia, V6T 2A3, CanadaahUniversity of Michigan, Ann Arbor, MI 48109, USAaiMichigan State University, East Lansing, MI 48824, USAajInstitution for Theoretical and Experimental Physics, ITEP, Moscow 117259, RussiaakUniversity of New Mexico, Albuquerque, NM 87131, USAalThe Ohio State University, Columbus, OH 43210, USAamOkayama University, Okayama 700-8530, JapananOsaka City University, Osaka 588, JapanaoUniversity of Oxford, Oxford OX1 3RH, United KingdomapIstituto Nazionale di Fisica Nucleare, Sezione di Padova–Trento, ItalyaqUniversity of Padova, I-35131 Padova, ItalyarUniversity of Pennsylvania, Philadelphia, PA 19104, USAasIstituto Nazionale di Fisica Nucleare Pisa, ItalyatUniversity of Pisa, ItalyauUniversity of Siena, ItalyavScuola Normale Superiore, I-56127 Pisa, ItalyawUniversity of Pittsburgh, Pittsburgh, PA 15260, USAaxPurdue University, West Lafayette, IN 47907, USAayUniversity of Rochester, Rochester, NY 14627, USAazThe Rockefeller University, New York, NY 10065, USAbaIstituto Nazionale di Fisica Nucleare, Sezione di Roma 1, ItalybbSapienza Università di Roma, I-00185 Roma, ItalybcRutgers University, Piscataway, NJ 08855, USAbdTexas A&M University, College Station, TX 77843, USAbeIstituto Nazionale di Fisica Nucleare Trieste/Udine, I-34100 Trieste, ItalybfUniversity of Udine, I-33100 Udine, ItalybgUniversity of Tsukuba, Tsukuba, Ibaraki 305, JapanbhTufts University, Medford, MA 02155, USAbiUniversity of Virginia, Charlottesville, VA 22906, USAbjWaseda University, Tokyo 169, JapanbkWayne State University, Detroit, MI 48201, USAblUniversity of Wisconsin, Madison, WI 53706, USAbmYale University, New Haven, CT 06520, USA⁎Corresponding author.1

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Editor: M. Doser

Abstract

A search for a narrow Higgs boson resonance in the diphoton mass spectrum is presented based on data corresponding to 10 fb−1 of integrated luminosity collected by the CDF experiment from proton–antiproton collisions at s=1.96 TeV. To increase the sensitivity of the search, we employ a multivariate discriminant technique for the first time in this channel at CDF. No evidence of signal is observed, and upper limits are set on the cross section times branching ratio of the resonant state as a function of the Higgs boson mass. The limits are interpreted in the context of the standard model with an expected (observed) limit on the cross section times branching ratio of 9.9 (17.0) times the standard model prediction at the 95% credibility level for a Higgs boson mass of 125 GeV/c2. Moreover, a Higgs boson with suppressed couplings to fermions is excluded for masses below 114 GeV/c2 at the 95% credibility level.

Introduction

The standard model (SM) of particle physics has proven to be a robust theory that accurately describes the properties of elementary particles and the forces of interaction between them. However, the origin of mass has remained an unsolved mystery for decades. The SM suggests that particles acquire mass due to interactions with the Higgs field via spontaneous symmetry breaking [1]. In direct searches at the Large Electron–Positron Collider (LEP) [2] and recent search results from the Tevatron [3] and the Large Hadron Collider (LHC) [4], all potential SM Higgs boson masses outside the ranges 116.6–119.4 GeV/c2 and 122.1–127.0 GeV/c2 are excluded by at least one experiment.In the SM, the branching ratio for a Higgs boson decaying into a photon pair B(H→γγ) is maximal for Higgs boson masses between about 110 and 140 GeV/c2. This is a mass range that is most suitable for Higgs boson searches at the Fermilab Tevatron [3] and is favored by indirect constraints from electroweak observables [5]. The SM H→γγ branching ratio peaks at a value of about 0.23% for a Higgs boson mass mH=125 GeV/c2[6]. This is a very small branching ratio; however, the distinctive signal that photons produce in the detector makes H→γγ an appealing search mode. Compared to the dominant decay modes involving b quarks, a larger fraction of H→γγ events can be identified and the diphoton invariant mass of these events would cluster in a narrower range, thus providing a better discriminator against the smoothly distributed background. There are also theories beyond the standard model that predict a suppressed coupling of a Higgs boson to fermions. In these “fermiophobic” Higgs boson models, the diphoton decay can be greatly enhanced [7].The Collider Detector at Fermilab (CDF) and D0 experiments at the Tevatron have searched for both a SM Higgs boson, H, and a fermiophobic Higgs boson, hf, decaying to two photons [8]. The CDF and D0 experiments recently set 95% credibility level (C.L.) upper limits on the cross section times branching ratio σ×B(H→γγ) relative to the SM prediction and on B(hf→γγ) using data corresponding to integrated luminosities L of 7.0 fb−1[9] and 8.2 fb−1[10], respectively. The hf result sets a lower limit on mhf of 114 GeV/c2 and 112.9 GeV/c2, respectively. These results surpassed for the first time the 109.7 GeV/c2 mass limit obtained from combined searches at the LEP collider at CERN [11].The ATLAS and CMS experiments at the LHC at CERN have searched for a SM Higgs boson decaying to two photons using L=4.9 fb−1[12] and 4.8 fb−1[13], respectively. In the low mass range, rates corresponding to more than twice the SM cross section are excluded at the 95% C.L. An excess of 1.8σ is present in the CMS result and of 1.5σ in the ATLAS result, accounting for the look-elsewhere effect, which could be consistent with a SM Higgs boson with a mass near 125 GeV/c2. Recent updates confirm these excesses at the 5σ level [14]. Searches for a fermiophobic Higgs boson in the ATLAS diphoton data exclude the ranges 110.0–118.0 GeV/c2 and 119.5–121.0 GeV/c2 at the 95% C.L. [15], and in the CMS diphoton data the ranges 110.0–124.5 GeV/c2 and 127.0–137.5 at the 95% C.L. [16].In this Letter, we present a search for a Higgs boson decaying to two photons using the final CDF diphoton data set, corresponding to an integrated luminosity of 10 fb−1. This analysis searches the diphoton mass distribution for a narrow resonance that could reveal the presence of a SM or fermiophobic Higgs boson, updating the previous CDF result [9] with more than 40% additional integrated luminosity. We furthermore implement a new multivariate technique for events that contain two central photons, using both diphoton and jet kinematic variables to improve the sensitivity for identifying a Higgs boson signal from the diphoton backgrounds.2

Higgs boson signal model

For the SM search, we consider the three most likely production mechanisms at the Tevatron: gluon fusion (GF); associated production (VH), where a Higgs boson is produced in association with a W or Z boson; and vector boson fusion (VBF), where a Higgs boson is produced alongside two quark jets. As an example, the SM cross sections [3] for mH=125 GeV/c2 are 949.3 fb [17], 208.0 fb [18], and 65.3 fb [19] respectively. In the fermiophobic search, we consider a benchmark model in which a Higgs boson does not couple to fermions, yet retains its SM couplings to bosons [7]. In this model, the GF loop process is suppressed and fermiophobic Higgs boson production is dominated by VH and VBF. With L=10 fb−1, about 28 (43) H→γγ (hf→γγ) events are predicted to be produced for mH=125 GeV/c2.The acceptance of these events in well-instrumented regions of the CDF detector times the efficiency of passing the full diphoton selection discussed in Section 3[9] is only about 25%. This fraction, along with the predicted distributions of kinematic variables, is obtained from a simulation of Higgs boson decays into diphotons. For each Higgs boson mass hypothesis tested in the range 100–150 GeV/c2, in 5 GeV/c2 steps, signal samples are developed from the pythia 6.2 [20] Monte Carlo (MC) event generator and a parametrized response of the CDF II detector [21]. All pythia samples were made with CTEQ5L [22] parton distribution functions, where the pythia underlying event model is tuned to CDF jet data [23]. Each signal sample is corrected for multiple interactions and differences between the identification of photons in the simulation and the data [9,24]. The GF signal is furthermore corrected based on a higher-order theoretical prediction of the transverse momentum distribution [25].3

Detector and event selection

We use the CDF II detector [26] to identify photon candidate events produced in pp¯ collisions at s=1.96 TeV. The silicon vertex tracker [27] and the central outer tracker [28], contained within a 1.4 T axial magnetic field, measure the trajectories of charged particles and determine their momenta. Particles that pass through the outer tracker reach the electromagnetic (EM) and hadronic calorimeters [29–31], which are divided into two regions: central (|η|<1.1) and forward or “plug” (1.1<|η|<3.6). The EM calorimeters contain fine-grained shower maximum detectors [32], which measure the shower shape and centroid position in the plane transverse to the direction of the shower development.The event selection is the same as in the previous H→γγ search [9]. Events with two photon candidates are selected and the data are divided into four independent categories according to the position and type of the photons. In central–central (CC) events with non-converted photons, both photon candidates are detected within the fiducial region of the central EM calorimeter (|η|<1.05); in central–plug (CP) events with non-converted photons, one photon candidate is detected in this region and the other is in the fiducial region of the plug calorimeter (1.2<|η|<2.8); in central–central events with a conversion (C′C), both photon candidates are in the central region, but one photon converts and is reconstructed from its e+e− decay products; in central–plug events with a conversion (C′P), there is one central conversion candidate together with a plug photon candidate.For the diphoton resonance technique described in Section 4, the event selection in the fermiophobic Higgs boson search is extended by taking advantage of the final-state features present in the VH and VBF processes. Because the Higgs boson from these processes will be produced in association with a W or Z boson, or with two jets, the transverse momentum of the diphoton system pTγγ is generally higher relative to the diphoton backgrounds. A requirement of pTγγ>75 GeV/c isolates a region of high hf sensitivity, retaining roughly 30% of the signal while removing 99.5% of the background [8]. Two lower-pTγγ regions, pTγγ<35 GeV/c and 35 GeV/c<pTγγ<75 GeV/c, are additionally included and provide about 15% more sensitivity to the hf signal.4

Diphoton resonance search

The decay of a Higgs boson into a diphoton pair would appear as a very narrow peak in the distribution of the invariant mass mγγ of the two photons. The diphoton mass resolution as determined from simulation is better than 3% for the Higgs boson mass region studied here and is limited by the energy resolution of the electromagnetic calorimeters [33] and the ability to identify the primary interaction vertex [9,24]. The diphoton invariant mass distribution for the most sensitive search category in the SM and fermiophobic scenarios is provided in Fig. 1

, with an inset showing the signal shape expected from simulation. In each diphoton category, we perform a search of the mγγ spectrum for signs of a resonance.

For this search, the total diphoton background is modeled from a fit to the binned diphoton mass spectrum of the data using a log-likelihood method, as described in [9,24]. The fit is performed independently for each diphoton category and includes only the sideband region for each mH hypothesis, which is the control region excluding a mass window centered on the Higgs boson mass being tested. The full width of the mass window is chosen to be approximately ±2 standard deviations of the expected Higgs boson mass resolution, which amounts to 12 GeV/c2, 16 GeV/c2, and 20 GeV/c2 for mass hypotheses of 100–115 GeV/c2, 120–135 GeV/c2, and 140–150 GeV/c2, respectively. Example fits for the CC category for mH=125 GeV/c2 are shown in Fig. 1.5

Multivariate discriminator

The diphoton mass distribution is the most powerful variable for separating a Higgs boson signal from the diphoton backgrounds. However, other information is available that can be used to further distinguish this signal. We improve the most sensitive search category (CC) by replacing the diphoton mass shape as a final discriminator with a “Multi-Layer Perceptron” neural network (NN) [34] output distribution. The NN combines the information of several well-modeled kinematic variables into a single discriminator, optimized to separate signal and background events. Four diphoton kinematic variables are included: mγγ, pTγγ, the difference between the azimuthal angles of the two photons, and the cosine of the photon emission angle relative to the colliding hadrons in the diphoton rest frame (the Collins–Soper angle) [35]. For events with jets, we also include four variables related to the jet activity, which are particularly useful for identifying VBF and VH signal events. These variables are the number of jets in the event, the sum of the jet transverse energies, and the event sphericity and aplanarity [36]. Jets are reconstructed from tower clusters in the hadronic calorimeter within a cone of radius 0.4 in the η–ϕ plane [37]. Each jet is required to have |η|<2 and a transverse energy ET>20 GeV, where the energy is corrected for calorimeter response, multiple interactions, and absolute energy scale.In order to optimize the performance of the method, we divide the CC category into two independent subsamples of events: the CC0 category for events with no jets and the CCJ category for events with at least one jet. The CC0 category uses a network trained with only the four diphoton variables; the CCJ category uses a network trained with the four diphoton and four jet variables.The sideband fit used in the diphoton resonance search provides an estimate of the total background prediction in each signal mass window; however, the multivariate analysis requires a more detailed background model. Specifically, we divide the background into its distinct components in order to best model all input variables used by the discriminant, which is also sensitive to correlations. There are two main background components in the CC data sample: a prompt diphoton (γγ) background produced from the hard parton scattering or from hard photon bremsstrahlung from energetic quarks, and a background comprised of γ–jet and jet–jet events (γj+jj) in which the jets are misidentified as photons [38]. To model the shape of kinematic variables in the γγ background, we use a pythia MC sample developed and studied in a measurement of the diphoton cross section [35]. To model the variable shapes in the γj+jj background, we obtain a data sample enriched in misidentified photons by selecting events for which one or both photon candidates fail the NN photon ID requirement [9].In the diphoton cross section analysis [35] it was found that a pTγγ-dependent correction was needed for the pythia modeling of prompt diphoton events. We adopt the correction for this analysis, reweighting the pTγγ distribution from pythia to match the pTγγ distribution from control regions in prompt diphoton data. For each category, CC0 and CCJ, and for each Higgs boson mass hypothesis, event weights are derived for the γγ background based on the sideband regions, excluding the signal mass window. The weights are derived by fitting a smooth function to the ratio of the pTγγ distribution from the data to that from the pythia prediction. The best fit in the CC0 category is obtained from a polynomial (constant) function for pTγγ<50 GeV/c (pTγγ>50 GeV/c). A different polynomial (constant) function provides the best fit in the CCJ category for pTγγ<60 GeV/c (pTγγ>60 GeV/c). Fig. 2

shows the reweighting function for a Higgs boson mass hypothesis of 125 GeV/c2. The solid curve shows the best fit to the data and the other two curves show the variations induced by propagating the 68% C.L. fit uncertainties to the fitting function. The rise of the reweighting function from pTγγ∼20 GeV/c to pTγγ∼50 GeV/c in both the CC0 and CCJ categories is interpreted in Ref. [35] as an effect of parton fragmentation not modeled in pythia, which contributes to the prompt diphoton production cross section in that range.

The relative contributions of the two background components are obtained from a fit to the diphoton data. Three histograms for each NN input variable are constructed: one from the γγ background sample after reweighting, one from the γj+jj background sample, and one from the diphoton data. Events used for the fit are required to have diphoton mass values greater than 70 GeV/c2 and to be outside of the signal mass window. The histograms are then used to build a χ2 function defined by(1)χ2=∑i=1Nbins∑j=1Nvariables[(αgij+βfij−dij)2dij] where gij, fij, and dij refer to the number of events in the ith bin of the jth input variable for the prompt γγ background, γj+jj background, and diphoton data samples, respectively. The sums are over all bins of each input variable for which there are at least 5 events in the data, and the global α and β coefficients are determined by minimizing the χ2 function. This function is defined and minimized separately for each Higgs boson mass hypothesis and for each category (CC0 and CCJ).A neural network discriminant is trained separately for each mass hypothesis using signal and background events. The signal events used in the training are optimized for the SM scenario and are composed of GF, VH, and VBF MC samples so that the corresponding total numbers are proportional to their SM cross section predictions. The background sample is made by taking a portion of the γj+jj sample available for each mass hypothesis and adding γγ events from pythia weighted by the ratio α/β from the χ2 fit for the given mass hypothesis.After training, the NN is applied to diphoton data events with mass inside the signal window. Fig. 3

shows input variables such as the pTγγ distribution for events with no reconstructed jets and the sum of the jet ET for events with ⩾1 reconstructed jet. The signal shapes are scaled to 20 times the expected number of reconstructed events in the SM scenario. The background prediction is also provided. While the χ2 fit described by Eq. (1) is used to fix the relative composition of the γγ and γj+jj background components, the total expected number of background events is more accurately determined from the sideband mass fits described in Section 4. The resulting NN shapes for mH=125 GeV/c2 are provided in Fig. 4

Systematic uncertainties

The sources of systematic uncertainties on the expected number of signal events are the same as in the previous CDF H→γγ search [9,24]. They arise from the conversion ID efficiency (7%), the integrated luminosity measurement (6%), varying the parton distribution functions used in pythia (up to 5%) [39,40], varying the parameters that control the amount of initial- and final-state radiation from the parton shower model of pythia (about 4%), and the pythia modeling of the shape of the pTγγ distribution for the hf signal (up to 4%) [41]. Finally, we include uncertainties from the photon ID efficiency (up to 4%), the trigger efficiency (less than 3%), and the EM energy scale (less than 1%). The signal rate uncertainties that arise from a common source are treated as correlated when combining results from each category.The statistical uncertainties on the total background rate in the signal region are determined by the mγγ fits. They are 4% or less for the channels associated with the SM diphoton resonance search and are less than 7% for the CC0 and CCJ categories used in the multivariate technique. For the channels associated with the fermiophobic Higgs boson diphoton resonance search, the background rate uncertainty is 12% or less, except for the high-pTγγ bins with conversion photons, where it is 20%. These background rate uncertainties are treated as uncorrelated between categories because the mγγ fits are determined from exclusive data samples.For the search using the multivariate technique, in addition to the rate uncertainties summarized above, we consider shape uncertainties and bin-by-bin statistical uncertainties of the NN discriminant. The signal shape uncertainties are associated with initial- and final-state radiation and the jet energy scale [37], and the background shape uncertainties are associated with the pythiapTγγ-correction and the jet energy scale. The pythia shape uncertainties due to the pTγγ fits are taken as uncorrelated between the CC0 and the CCJ categories because the fits determining the corrections for each category are done independently. The jet energy scale shape uncertainties are correlated between the two categories in order to take into account event migration between categories. The dominant uncertainty in the multivariate analysis is the bin-by-bin statistical uncertainty of the γj+jj background histograms.7

Results

No evidence of a narrow peak or any other structure is visible in the diphoton mass spectrum or the NN output distribution. We calculate a Bayesian C.L. limit for each Higgs boson mass hypothesis based on a combination of likelihoods from the discriminant distributions for all channels in the corresponding mass signal region. The combined limits for the SM search use the NN discriminants of the CC0 and CCJ categories and the mass discriminants from the CP, C′C, and C′P categories. The fermiophobic limits use the NN discriminants of the CC0 and CCJ categories and the mass discriminants from the CP, C′C, and C′P categories divided into pTγγ regions. For the limit calculation, we assume a flat prior (truncated at zero) for the signal rate and a truncated Gaussian prior for each of the systematic uncertainties. A 95% C.L. limit is determined such that 95% of the posterior density for σ×B(H→γγ) falls below the limit [42]. The expected 95% C.L. limits are calculated assuming no signal, based on expected backgrounds only, as the median of 2000 simulated experiments. The observed 95% C.L. limits on σ×B(H→γγ) are calculated from the data.For the SM Higgs boson search, the results are given relative to the theory prediction, where theoretical cross section uncertainties of 14% on the inclusive GF process, 7% on the VH process, and 5% on the VBF process are included in the limit calculation [3,43]. Since the NN technique divides the CC category into separate channels based on the number of reconstructed jets, different GF cross section uncertainties are assigned to the CC0 and CCJ channels [3,44]. For the hf model, SM cross sections and uncertainties are assumed (GF excluded) and used to convert limits on σ×B(hf→γγ) into limits on B(hf→γγ). The SM and fermiophobic limit results for the CC category alone are provided in Table 1

, showing the gain obtained by incorporating a multivariate technique for this category. The combined limit results for both searches are displayed in Table 2

and graphically in Fig. 5

. Limits are also provided on σ×B(H→γγ) for the SM search without including theoretical cross section uncertainties. For the SM limit at mH=120 GeV/c2, we observe a deviation of greater than 2.5σ from the expectation. After accounting for the look-elsewhere effect associated with performing the search at 11 mass points, the significance of this discrepancy decreases to less than 2σ. When the analysis is optimized for the fermiophobic benchmark model, no excess is observed. For the hf model, we obtain a limit of mhf<114 GeV/c2 by linear interpolation between the sampled values of mhf based on the intersection of the observed limit and the model prediction.

Summary and conclusions

This Letter presents the results of a search for a narrow resonance in the diphoton mass spectrum using data taken by the CDF II detector at the Tevatron. We have improved upon the previous CDF analysis by implementing a neural network discriminant to increase sensitivity in the most sensitive diphoton category by as much as 13% (17%) for the SM (fermiophobic) scenario. In addition, we have included the full CDF diphoton data set, which adds more than 40% additional integrated luminosity relative to the previous diphoton Higgs boson search. There is no significant evidence of a resonance in the data. Limits are placed on the production cross section times branching ratio for Higgs boson decay into a photon pair and compared to the predictions of the standard model and a benchmark fermiophobic model. The latter results in a limit on the fermiophobic Higgs boson mass of mhf<114 GeV/c2 at the 95% C.L.

Acknowledgements

We thank the Fermilab staff and the technical staffs of the participating institutions for their vital contributions. This work was supported by the U.S. Department of Energy and National Science Foundation; the Italian Istituto Nazionale di Fisica Nucleare; the Ministry of Education, Culture, Sports, Science and Technology of Japan; the Natural Sciences and Engineering Research Council of Canada; the National Science Council of the Republic of China; the Swiss National Science Foundation; the A.P. Sloan Foundation; the Bundesministerium für Bildung und Forschung, Germany; the Korean World Class University Program, the National Research Foundation of Korea; the Science and Technology Facilities Council and the Royal Society, UK; the Russian Foundation for Basic Research; the Ministerio de Ciencia e Innovación, and Programa Consolider-Ingenio 2010, Spain; the Slovak R&D Agency; the Academy of Finland; and the Australian Research Council (ARC).

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