application/xmlSearch for neutral Higgs bosons in the multi-b-jet topology in [formula omitted] of [formula omitted] collisions at [formula omitted]D0 CollaborationV.M. AbazovB. AbbottB.S. AcharyaM. AdamsT. AdamsG.D. AlexeevG. AlkhazovA. AltonG. AlversonG.A. AlvesL.S. AncuM. AokiY. ArnoudM. ArovA. AskewB. ÅsmanO. AtramentovC. AvilaJ. BackusMayesF. BadaudL. BagbyB. BaldinD.V. BandurinS. BanerjeeE. BarberisP. BaringerJ. BarretoJ.F. BartlettU. BasslerV. BazterraS. BealeA. BeanM. BegalliM. BegelC. Belanger-ChampagneL. BellantoniS.B. BeriG. BernardiR. BernhardI. BertramM. BesançonR. BeuselinckV.A. BezzubovP.C. BhatV. BhatnagarG. BlazeyS. BlessingK. BloomA. BoehnleinD. BolineT.A. BoltonE.E. BoosG. BorissovT. BoseA. BrandtO. BrandtR. BrockG. BrooijmansA. BrossD. BrownJ. BrownX.B. BuM. BuehlerV. BuescherV. BunichevS. BurdinT.H. BurnettC.P. BuszelloB. CalpasE. Camacho-PérezM.A. Carrasco-LizarragaB.C.K. CaseyH. Castilla-ValdezS. ChakrabartiD. ChakrabortyK.M. ChanA. ChandraG. ChenS. Chevalier-ThéryD.K. ChoS.W. ChoS. ChoiB. ChoudharyT. ChristoudiasS. CihangirD. ClaesJ. ClutterM. CookeW.E. CooperM. CorcoranF. CoudercM.-C. CousinouA. CrocD. CuttsM. ĆwiokA. DasG. DaviesK. DeS.J. de JongE. De La Cruz-BureloF. DéliotM. DemarteauR. DeminaD. DenisovS.P. DenisovS. DesaiK. DeVaughanH.T. DiehlM. DiesburgA. DominguezT. DorlandA. DubeyL.V. DudkoD. DugganA. DuperrinS. DuttA. DyshkantM. EadsD. EdmundsJ. EllisonV.D. ElviraY. EnariH. EvansA. EvdokimovV.N. EvdokimovG. FaciniT. FerbelF. FiedlerF. FilthautW. FisherH.E. FiskM. FortnerH. FoxS. FuessT. GadfortA. Garcia-BellidoV. GavrilovP. GayW. GeistW. GengD. GerbaudoC.E. GerberY. GershteinG. GintherG. GolovanovA. GoussiouP.D. GrannisS. GrederH. GreenleeZ.D. GreenwoodE.M. GregoresG. GrenierPh. GrisJ.-F. GrivazA. GrohsjeanS. GrünendahlM.W. GrünewaldF. GuoG. GutierrezP. GutierrezA. HaasS. HagopianJ. HaleyL. HanK. HarderA. HarelJ.M. HauptmanJ. HaysT. HeadT. HebbekerD. HedinH. HegabA.P. HeinsonU. HeintzC. HenselI. Heredia-De La CruzK. HernerG. HeskethM.D. HildrethR. HiroskyT. HoangJ.D. HobbsB. HoeneisenM. HohlfeldS. HossainZ. HubacekN. HuskeV. HynekI. IashviliR. IllingworthA.S. ItoS. JabeenM. JaffréS. JainD. JaminR. JesikK. JohnsM. JohnsonD. JohnstonA. JonckheereP. JonssonJ. JoshiA. JusteK. KaadzeE. KajfaszD. KarmanovP.A. KasperI. KatsanosR. KehoeS. KermicheN. KhalatyanA. KhanovA. KharchilavaY.N. KharzheevD. KhatidzeM.H. KirbyJ.M. KohliA.V. KozelovJ. KrausA. KumarA. KupcoT. KurčaV.A. KuzminJ. KvitaS. LammersG. LandsbergP. LebrunH.S. LeeS.W. LeeW.M. LeeJ. LellouchL. LiQ.Z. LiS.M. LiettiJ.K. LimD. LincolnJ. LinnemannV.V. LipaevR. LiptonY. LiuZ. LiuA. LobodenkoM. LokajicekP. LoveH.J. LubattiR. Luna-GarciaA.L. LyonA.K.A. MacielD. MackinR. MadarR. Magaña-VillalbaP.K. MalS. MalikV.L. MalyshevY. MaravinJ. Martínez-OrtegaR. McCarthyC.L. McGivernM.M. MeijerA. MelnitchoukD. MenezesP.G. MercadanteM. MerkinA. MeyerJ. MeyerN.K. MondalG.S. MuanzaM. MulhearnE. NagyM. NaimuddinM. NarainR. NayyarH.A. NealJ.P. NegretP. NeustroevS.F. NovaesT. NunnemannG. ObrantJ. OrdunaN. OsmanJ. OstaG.J. Otero y GarzónM. OwenM. PadillaM. PangilinanN. ParasharV. PariharS.K. ParkJ. ParsonsR. PartridgeN. ParuaA. PatwaB. PenningM. PerfilovK. PetersY. PetersG. PetrilloP. PétroffR. PiegaiaJ. PiperM.-A. PleierP.L.M. Podesta-LermaV.M. PodstavkovM.-E. PolP. PolozovA.V. PopovM. PrewittD. PriceS. ProtopopescuJ. QianA. QuadtB. QuinnM.S. RangelK. RanjanP.N. RatoffI. RazumovP. RenkelP. RichM. RijssenbeekI. Ripp-BaudotF. RizatdinovaM. RominskyC. RoyonP. RubinovR. RuchtiG. SafronovG. SajotA. Sánchez-HernándezM.P. SandersB. SanghiA.S. SantosG. SavageL. SawyerT. ScanlonR.D. SchambergerY. ScheglovH. SchellmanT. SchliephakeS. SchlobohmC. SchwanenbergerR. SchwienhorstJ. SekaricH. SeveriniE. ShabalinaV. SharyA.A. ShchukinR.K. ShivpuriV. SimakV. SirotenkoP. SkubicP. SlatteryD. SmirnovK.J. SmithG.R. SnowJ. SnowS. SnyderS. Söldner-RemboldL. SonnenscheinA. SopczakM. SosebeeK. SoustruznikB. SpurlockJ. StarkV. StolinD.A. StoyanovaM. StraussD. StromL. StutteL. SuterP. SvoiskyM. TakahashiA. TanasijczukW. TaylorM. TitovV.V. TokmeninY.-T. TsaiD. TsybychevB. TuchmingC. TullyP.M. TutsL. UvarovS. UvarovS. UzunyanR. Van KootenW.M. van LeeuwenN. VarelasE.W. VarnesI.A. VasilyevP. VerdierL.S. VertogradovM. VerzocchiM. VesterinenD. VilanovaP. VintP. VokacH.D. WahlM.H.L.S. WangJ. WarcholG. WattsM. WayneM. WeberL. Welty-RiegerA. WhiteD. WickeM.R.J. WilliamsG.W. WilsonS.J. WimpennyM. WobischD.R. WoodT.R. WyattY. XieC. XuS. YacoobR. YamadaW.-C. YangT. YasudaY.A. YatsunenkoZ. YeH. YinK. YipS.W. YounJ. YuS. ZelitchT. ZhaoB. ZhouJ. ZhuM. ZielinskiD. ZieminskaL. ZivkovicHiggs bosonSupersymmetryBottom quarksTevatronPhysics Letters B 698 (2011) 97-104. doi:10.1016/j.physletb.2011.02.062journalPhysics Letters BCopyright © 2011 Elsevier B.V. All rights reserved.Elsevier B.V.0370-269369824 April 20112011-04-0497-1049710410.1016/j.physletb.2011.02.062http://dx.doi.org/10.1016/j.physletb.2011.02.062doi:10.1016/j.physletb.2011.02.062http://vtw.elsevier.com/data/voc/oa/OpenAccessStatus#Full2014-01-01T00:14:32ZSCOAP3 - Sponsoring Consortium for Open Access Publishing in Particle Physicshttp://vtw.elsevier.com/data/voc/oa/SponsorType#FundingBodyhttp://creativecommons.org/licenses/by/3.0/

Journals

S300.3

PLB27437S0370-2693(11)00231-010.1016/j.physletb.2011.02.062Elsevier B.V.Experiments

Fig. 1

(Color online.) Comparison of the a) low-mass and b) high-mass likelihood distributions for the data and predicted background defined by Eq. (3) in the 3Tag exclusive three-jet channel. Each event has one entry, the jet pairing with the highest likelihood output. Black crosses refer to data, the solid line shows the total background estimate, and the shaded region represents the heavy flavor component (bb¯b, bb¯c, and bcc¯). The distributions for a Higgs boson of mass 120 and 200 GeV are shown as a dashed line in a) and b), respectively. The background and signal contributions are normalized to have an equal number of events as data. The arrows indicate the selection cut at D=0.65.

Fig. 2

(Color online.) Invariant mass distribution for the 3Tag exclusive three-jet channel for: a) the low-mass likelihood selection and b) the high-mass likelihood selection. Each event has one entry, the jet pairing with the highest likelihood output. Black crosses refer to data, the solid line shows the total background estimate, and the shaded region represents the heavy flavor component (bb¯b, bb¯c, and bcc¯). The lower panels show the difference between the data and the predicted background.

Fig. 3

(Color online.) Invariant mass distribution of Higgs signals in the three-jet channel for MA=120, 180 and 240 GeV, respectively. The distributions are normalized to unit area.

Fig. 4

(Color online.) Invariant mass distribution for the jet pair with the lower likelihood for data (black crosses) and background (line) in the 3Tag exclusive three-jet channel for the 4.2 fb−1 data set collected after the silicon detector upgrade. The lower panel shows the difference between the data and the predicted background.

Fig. 5

(Color online.) Model independent 95% C.L. upper limit on the cross section multiplied by the branching ratio for the combined 5.2 fb−1 analysis. The light and dark grey regions correspond to the one and two standard deviation (s.d.) bands around the expected limit.

Fig. 6

(Color online.) a) 95% C.L. lower limit in the (MA,tanβ) plane obtained for the mhmax, μ=−200 GeV scenario, b) the lower limit for the no-mixing, μ=−200 GeV scenario. The one and two standard deviation bands around the expected limit and the exclusion limit obtained from the LEP experiments are also shown [5].

Table 1

The number and fraction of events in data and signal efficiency for each selection requirement. As the data are split into three- and four-jet sub-samples, these numbers are reported separately in the last three rows.

Number of events (×103)Fraction (%)Signal eff. (%) MA=200 GeVEvents517,288100–Trigger198,1063830zPV cut195,58738253/4 jets96,318/21,89819/4.212/3.72 b-tag jets710/2300.14/0.0445.4/1.83 b-tag jets15/110.0029/0.00211.2/0.61Table 2

Model independent 95% C.L. upper limits on the cross section times branching ratio for the combined 5.2 fb−1 analysis.

MA [GeV]Observed [pb]Expected [pb]9089.573.910046.042.511055.034.012042.022.613023.115.014017.610.815012.48.051608.526.381707.245.051806.374.111905.823.512005.462.982104.432.642203.652.232302.802.022402.191.812501.801.552601.621.352701.311.232801.161.102900.731.063000.630.95Search for neutral Higgs bosons in the multi-b-jet topology in 5.2 fb−1 of pp¯ collisions at s=1.96 TeV

D0 Collaboration

V.M.

Abazov

Abbott

B.S.

Acharya

Adams

G.D.

Alexeev

Alkhazov

Alton

Alverson

G.A.

Alves

L.S.

Ancu

Aoki

Arnoud

Arov

Askew

Åsman

Atramentov

Avila

BackusMayes

Badaud

Bagby

Baldin

D.V.

Bandurin

Banerjee

Barberis

Baringer

Barreto

J.F.

Bartlett

Bassler

Bazterra

Beale

Bean

Begalli

Begel

Belanger-Champagne

Bellantoni

S.B.

Beri

Bernardi

Bernhard

Bertram

Besançon

Beuselinck

V.A.

Bezzubov

P.C.

Bhat

Bhatnagar

Blazey

Blessing

Bloom

Boehnlein

Boline

T.A.

Bolton

E.E.

Boos

Borissov

Bose

Brandt

Brock

Brooijmans

Bross

Brown

X.B.

Buehler

Buescher

Bunichev

Burdin

T.H.

Burnett

C.P.

Buszello

Calpas

Camacho-Pérez

M.A.

Carrasco-Lizarraga

B.C.K.

Casey

Castilla-Valdez

Chakrabarti

Chakraborty

K.M.

Chan

Chandra

Chen

Chevalier-Théry

D.K.

Cho

S.W.

Cho

Choi

Choudhary

Christoudias

Cihangir

Claes

Clutter

Cooke

W.E.

Cooper

Corcoran

Couderc

M.-C.

Cousinou

Croc

Cutts

Ćwiok

Das

Davies

S.J.

de Jong

De La Cruz-Burelo

Déliot

Demarteau

Demina

Denisov

S.P.

Denisov

Desai

DeVaughan

H.T.

Diehl

Diesburg

Dominguez

Dorland

Dubey

L.V.

Dudko

Duggan

Duperrin

Dutt

Dyshkant

Eads

Edmunds

Ellison

V.D.

Elvira

Enari

Evans

Evdokimov

V.N.

Evdokimov

Facini

Ferbel

Fiedler

Filthaut

Fisher

H.E.

Fisk

Fortner

Fox

Fuess

Gadfort

Garcia-Bellido

Gavrilov

Gay

Geist

Geng

Gerbaudo

C.E.

Gerber

Gershtein

Ginther

Golovanov

Goussiou

P.D.

Grannis

Greder

Greenlee

Z.D.

Greenwood

E.M.

Gregores

Grenier

Ph.

Gris

J.-F.

Grivaz

Grohsjean

Grünendahl

M.W.

Grünewald

Guo

Gutierrez

Haas

Hagopian

Haley

Han

Harder

Harel

J.M.

Hauptman

Hays

Head

Hebbeker

Hedin

Hegab

A.P.

Heinson

Heintz

Hensel

Heredia-De La Cruz

Herner

Hesketh

M.D.

Hildreth

Hirosky

Hoang

J.D.

Hobbs

Hoeneisen

Hohlfeld

Hossain

Hubacek

Huske

Hynek

Iashvili

Illingworth

A.S.

Ito

Jabeen

Jaffré

Jain

Jamin

Jesik

Johns

Johnson

Johnston

Jonckheere

Jonsson

Joshi

Juste

Kaadze

Kajfasz

Karmanov

P.A.

Kasper

Katsanos

Kehoe

Kermiche

Khalatyan

Khanov

Kharchilava

Y.N.

Kharzheev

Khatidze

M.H.

Kirby

J.M.

Kohli

A.V.

Kozelov

Kraus

Kumar

Kupco

Kurča

V.A.

Kuzmin

Kvita

Lammers

Landsberg

Lebrun

H.S.

Lee

S.W.

Lee

W.M.

Lee

Lellouch

Q.Z.

S.M.

Lietti

J.K.

Lim

Lincoln

Linnemann

V.V.

Lipaev

Lipton

Liu

Lobodenko

Lokajicek

Love

H.J.

Lubatti

Luna-Garcia

A.L.

Lyon

A.K.A.

Maciel

Mackin

Madar

Magaña-Villalba

P.K.

Mal

Malik

V.L.

Malyshev

Maravin

Martínez-Ortega

McCarthy

C.L.

McGivern

M.M.

Meijer

Melnitchouk

Menezes

P.G.

Mercadante

Merkin

Meyer

N.K.

Mondal

G.S.

Muanza

Mulhearn

Nagy

Naimuddin

Narain

Nayyar

H.A.

Neal

J.P.

Negret

Neustroev

S.F.

Novaes

Nunnemann

Obrant

Orduna

Osman

Osta

G.J.

Otero y Garzón

Owen

Padilla

Pangilinan

Parashar

Parihar

S.K.

Park

Parsons

Partridge

Parua

Patwa

Penning

Perfilov

Peters

Petrillo

Pétroff

Piegaia

Piper

M.-A.

Pleier

P.L.M.

Podesta-Lerma

V.M.

Podstavkov

M.-E.

Pol

Polozov

A.V.

Popov

Prewitt

Price

Protopopescu

Qian

Quadt

Quinn

M.S.

Rangel

Ranjan

P.N.

Ratoff

Razumov

Renkel

Rich

Rijssenbeek

Ripp-Baudot

Rizatdinova

Rominsky

Royon

Rubinov

Ruchti

Safronov

Sajot

Sánchez-Hernández

M.P.

Sanders

Sanghi

A.S.

Santos

Savage

Sawyer

Scanlon

R.D.

Schamberger

Scheglov

Schellman

Schliephake

Schlobohm

Schwanenberger

Schwienhorst

Sekaric

Severini

Shabalina

Shary

A.A.

Shchukin

R.K.

Shivpuri

Simak

Sirotenko

Skubic

Slattery

Smirnov

K.J.

Smith

G.R.

Snow

Snyder

Söldner-Rembold

Sonnenschein

Sopczak

Sosebee

Soustruznik

Spurlock

Stark

Stolin

D.A.

Stoyanova

Strauss

Strom

Stutte

Suter

Svoisky

Takahashi

Tanasijczuk

Taylor

Titov

V.V.

Tokmenin

Y.-T.

Tsai

Tsybychev

Tuchming

Tully

P.M.

Tuts

Uvarov

Uzunyan

Van Kooten

W.M.

van Leeuwen

Varelas

E.W.

Varnes

I.A.

Vasilyev

Verdier

L.S.

Vertogradov

Verzocchi

Vesterinen

Vilanova

Vint

Vokac

H.D.

Wahl

M.H.L.S.

Wang

Warchol

Watts

Wayne

Weber

Welty-Rieger

White

Wicke

M.R.J.

Williams

G.W.

Wilson

S.J.

Wimpenny

Wobisch

D.R.

Wood

T.R.

Wyatt

Xie

Yacoob

Yamada

W.-C.

Yang

Yasuda

Y.A.

Yatsunenko

Yin

Yip

S.W.

Youn

Zelitch

Zhao

Zhou

Zhu

Zielinski

Zieminska

Zivkovic

aUniversidad de Buenos Aires, Buenos Aires, ArgentinabLAFEX, Centro Brasileiro de Pesquisas Físicas, Rio de Janeiro, BrazilcUniversidade do Estado do Rio de Janeiro, Rio de Janeiro, BrazildUniversidade Federal do ABC, Santo André, BrazileInstituto de Física Teórica, Universidade Estadual Paulista, São Paulo, BrazilfSimon Fraser University, Vancouver, British Columbia, and York University, Toronto, Ontario, CanadagUniversity of Science and Technology of China, Hefei, Peopleʼs Republic of ChinahUniversidad de los Andes, Bogotá, ColombiaiCharles University, Faculty of Mathematics and Physics, Center for Particle Physics, Prague, Czech RepublicjCzech Technical University in Prague, Prague, Czech RepublickCenter for Particle Physics, Institute of Physics, Academy of Sciences of the Czech Republic, Prague, Czech RepubliclUniversidad San Francisco de Quito, Quito, EcuadormLPC, Université Blaise Pascal, CNRS/IN2P3, Clermont, FrancenLPSC, Université Joseph Fourier Grenoble 1, CNRS/IN2P3, Institut National Polytechnique de Grenoble, Grenoble, FranceoCPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille, FrancepLAL, Université Paris-Sud, CNRS/IN2P3, Orsay, FranceqLPNHE, Universités Paris VI and VII, CNRS/IN2P3, Paris, FrancerCEA, Irfu, SPP, Saclay, FrancesIPHC, Université de Strasbourg, CNRS/IN2P3, Strasbourg, FrancetIPNL, Université Lyon 1, CNRS/IN2P3, Villeurbanne, France and Université de Lyon, Lyon, FranceuIII. Physikalisches Institut A, RWTH Aachen University, Aachen, GermanyvPhysikalisches Institut, Universität Freiburg, Freiburg, GermanywII. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen, GermanyxInstitut für Physik, Universität Mainz, Mainz, GermanyyLudwig-Maximilians-Universität München, München, GermanyzFachbereich Physik, Bergische Universität Wuppertal, Wuppertal, GermanyaaPanjab University, Chandigarh, IndiaabDelhi University, Delhi, IndiaacTata Institute of Fundamental Research, Mumbai, IndiaadUniversity College Dublin, Dublin, IrelandaeKorea Detector Laboratory, Korea University, Seoul, KoreaafCINVESTAV, Mexico City, MexicoagFOM-Institute NIKHEF and University of Amsterdam/NIKHEF, Amsterdam, The NetherlandsahRadboud University Nijmegen/NIKHEF, Nijmegen, The NetherlandsaiJoint Institute for Nuclear Research, Dubna, RussiaajInstitute for Theoretical and Experimental Physics, Moscow, RussiaakMoscow State University, Moscow, RussiaalInstitute for High Energy Physics, Protvino, RussiaamPetersburg Nuclear Physics Institute, St. Petersburg, RussiaanStockholm University, Stockholm and Uppsala University, Uppsala, SwedenaoLancaster University, Lancaster LA1 4YB, United KingdomapImperial College London, London SW7 2AZ, United KingdomaqThe University of Manchester, Manchester M13 9PL, United KingdomarUniversity of Arizona, Tucson, AZ 85721, USAasUniversity of California Riverside, Riverside, CA 92521, USAatFlorida State University, Tallahassee, FL 32306, USAauFermi National Accelerator Laboratory, Batavia, IL 60510, USAavUniversity of Illinois at Chicago, Chicago, IL 60607, USAawNorthern Illinois University, DeKalb, IL 60115, USAaxNorthwestern University, Evanston, IL 60208, USAayIndiana University, Bloomington, IN 47405, USAazPurdue University Calumet, Hammond, IN 46323, USAbaUniversity of Notre Dame, Notre Dame, IN 46556, USAbbIowa State University, Ames, IA 50011, USAbcUniversity of Kansas, Lawrence, KS 66045, USAbdKansas State University, Manhattan, KS 66506, USAbeLouisiana Tech University, Ruston, LA 71272, USAbfBoston University, Boston, MA 02215, USAbgNortheastern University, Boston, MA 02115, USAbhUniversity of Michigan, Ann Arbor, MI 48109, USAbiMichigan State University, East Lansing, MI 48824, USAbjUniversity of Mississippi, University, MS 38677, USAbkUniversity of Nebraska, Lincoln, NE 68588, USAblRutgers University, Piscataway, NJ 08855, USAbmPrinceton University, Princeton, NJ 08544, USAbnState University of New York, Buffalo, NY 14260, USAboColumbia University, New York, NY 10027, USAbpUniversity of Rochester, Rochester, NY 14627, USAbqState University of New York, Stony Brook, NY 11794, USAbrBrookhaven National Laboratory, Upton, NY 11973, USAbsLangston University, Langston, OK 73050, USAbtUniversity of Oklahoma, Norman, OK 73019, USAbuOklahoma State University, Stillwater, OK 74078, USAbvBrown University, Providence, RI 02912, USAbwUniversity of Texas, Arlington, TX 76019, USAbxSouthern Methodist University, Dallas, TX 75275, USAbyRice University, Houston, TX 77005, USAbzUniversity of Virginia, Charlottesville, VA 22901, USAcaUniversity of Washington, Seattle, WA 98195, USA1

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Editor: H. Weerts

Abstract

Data recorded by the D0 experiment at the Fermilab Tevatron Collider are analyzed to search for neutral Higgs bosons produced in association with b quarks. The search is performed in the three-b-quark channel using multijet-triggered events corresponding to an integrated luminosity of 5.2 fb−1. In the absence of any significant excess above background, limits are set on the cross section multiplied by the branching ratio in the Higgs boson mass range 90 to 300 GeV, extending the excluded regions in the parameter space of the minimal supersymmetric standard model.

Keywords

Higgs bosonSupersymmetryBottom quarksTevatron

The two Higgs boson doublets in the minimal supersymmetric standard model (MSSM) [1,2] lead to five physical Higgs bosons: three neutral (collectively denoted as ϕ): h, H, and A; and two charged: H+ and H−.Two parameters, conventionally chosen as the ratio of the two Higgs doublet vacuum expectation values, tanβ, and the mass of the pseudoscalar A, MA, are sufficient to describe the MSSM Higgs sector at tree level. Though tanβ is a free parameter in the MSSM, there are indications which suggest that it should be large. A value of tanβ≈35 naturally explains the top to bottom quark mass ratio [3], and high tanβ values also provide a good explanation for the observed density of dark matter [4].The couplings of the Higgs bosons to fermions in the MSSM are proportional to the corresponding couplings in the standard model (SM). The proportionality factor depends on the type of the quark (up- or down-type) and on the type of the Higgs boson. At large tanβ, the two Higgs bosons A and either h or H have approximately the same mass and a down-type quark coupling enhanced by tanβ compared to the SM coupling, while the coupling to up-type quarks is suppressed. Here, the three neutral Higgs boson couplings to b quarks follow the sum rule ghbb¯2+gHbb¯2+gAbb¯2≈2×tan2β×gH,SM2, where gH,SM is the SM coupling. Therefore, in these cases the production of Higgs bosons associated with bottom quarks (down-type quarks with the highest mass) is enhanced by a factor of 2×tan2β compared to SM production. Due to the tanβ enhancement, the main decay for the three neutral Higgs bosons is ϕ→bb¯ with branching ratios near 90% (the remainder being mostly ϕ→ττ). Since a direct search for ϕ→bb¯ is difficult due to large multijet backgrounds, searches rely on the case where ϕ is produced in association with one b quark. The final state with three b quarks represents a powerful search channel, with the third b-jet providing additional suppression of the large multijet background at a hadron collider.MSSM Higgs boson production has been studied at the CERN LEP e+e− collider which excluded Mh,A<93 GeV for all tanβ values [5]. The CDF [6,7] and D0 [8–12] collaborations have extended MSSM Higgs boson searches to higher masses for high tanβ values. This Letter uses data collected during Run II at the Fermilab Tevatron collider by the D0 collaboration corresponding to an integrated luminosity of 5.2 fb−1[13]. The dataset is broken into two periods, corresponding to the period before (1.0 fb−1) and after (4.2 fb−1) the upgrade of the D0 silicon vertex detector and trigger system. The dataset is five times larger than that used in the previous publication [9]. The full dataset has been reanalyzed to incorporate recent improvements to analysis procedures, algorithms, and calibrations. Improved modeling of the background has resulted in reduced systematic uncertainties. In addition, the Higgs boson mass range under consideration has been extended to 300 GeV. The limits are calculated using a program [14], which is an implementation of the modified frequentist limit setting procedure [27,28], and are based only on the shape, and not the normalization, of the distribution of the final discriminating variable.The D0 detector is described in Refs. [15,16]. Dedicated triggers for the three trigger levels (L1, L2, L3) designed to select events with at least three jets are used in this analysis. The majority of the data were recorded with b-tagging requirements at the trigger level, either at L3 or at both L2 and L3. The trigger has an efficiency of approximately 60% for ϕb→bb¯b events with a Higgs boson mass of 150 GeV when measured relative to events with three or four reconstructed jets.The midpoint cone algorithm [17] with a radius R=(Δy)2+(Δφ)2=0.5, where y is the rapidity and φ the azimuthal angle, is used to reconstruct jets from energy deposits in the calorimeters. Details of the jet reconstruction and energy scale determination are described in Ref. [18]. In addition to passing a set of quality criteria, all jets are required to be matched to at least two tracks reconstructed in the central detector, pointing to the pp¯ vertex and with hits in the silicon detector. The matching criterion is ΔR(track,jet-axis)=(Δη)2+(Δφ)2<0.5, where η is the pseudorapidity. Signal events are selected by requiring three or four jets with transverse momenta pT>20 GeV and |η|<2.5. The distance in the coordinate along the beam axis of the position of the pp¯ vertex (zPV) is required to be within 35 cm of the center of the detector. This is well within the geometric acceptance of the silicon detector, as needed for efficient b-tagging. A neural network (NN) b-tagging algorithm [19], which considers lifetime based information involving the track impact parameters and secondary vertices, is used to identify b-quark jets. Each event must have at least three jets satisfying a b-tag NN requirement. The single jet b-tagging efficiency is approximately 50% for a light-quark jet mistag rate of 0.8%. Data events with two tagged jets are used together with simulated events with two and three tagged jets to model the background. Finally, the transverse momenta of the two b-tagged jets with the highest pT are required to be above 25 GeV. The data are split into four independent channels based on jet multiplicity (three or four jets) and running period.The leading order event generator pythia[20] is used to generate samples of associated production of ϕ and a b quark in the 5-flavor scheme [21], gb→ϕb. The cross section,88

All cross sections are quoted with respect to acceptance requirements on the highest-pTb-quark not from the Higgs decay with pT>12 GeV and |η|<5.0.

experimental acceptance, and the kinematic distributions of the b-quark jet produced in association with the Higgs boson are corrected to next-to-leading order (NLO) using mcfm[21]. Multijet background events from the bb¯j, bb¯jj, cc¯j, cc¯jj, bb¯cc¯, and bb¯bb¯ processes, where j denotes a light parton (u, d, s quark or gluon), are generated with the alpgen[22] event generator. A matching algorithm is used to avoid double counting of final states [23]. The small contribution from tt¯ production to the background is also simulated with alpgen. Other processes, such as Zbb¯ and single top quark production, are negligible. The alpgen samples are processed through pythia for showering and hadronization. All samples are then processed through a geant-based [24] simulation of the D0 detector. The same reconstruction algorithms are used for the simulated samples as for the data. A parameterized trigger simulation, based on efficiencies measured in data, is used to model the effects of the trigger requirements. The b-tagging is modeled by weighting simulated events based on their tagging probability measured using data [19]. The efficiency of the requirements on the triggers, zPV, and the number of jets, range from 1.9% to 26.4% for Higgs boson masses between 90 and 300 GeV. After the three b-tag requirement the efficiency with respect to the total number of signal events ranges from 0.2% to 1.4% in the three-jet channel (0.1% to 0.9% in the four-jet channel). Table 1

shows the number of events in data and the signal efficiency at different stages of the event selection.

Multijet processes contribute to the background and the theoretical uncertainty on their cross sections is very large. The background composition is therefore determined by fitting distributions of the scalar sum of the transverse momenta of jets in simulated events to data. The fractional contribution, αi, of the ith multijet background process is calculated from equations linking the b-tag efficiency for the ith background, ϵki, with the number of observed events, Nk, where k indicates the number of b-tagged jets (0–3) in an event,99

The events with four b-tagged jets in the four jet sample are included with the events with three b-tagged jets when determining the background composition.

and the total number of events, Ntot:(1)∑iαi=1,∑iαi×ϵki=Nk/Ntot. The double b-tagged sample is dominated by bb¯j, while the triple b-tagged sample consists of a mixture of approximately 50% bb¯b, 30% bb¯j, 15% bb¯c+bcc¯ and a remaining fraction consisting of cc¯j,bjj,cjj, and jjj.For every event, the two jet pairs with the largest and next-to-largest scalar summed transverse momenta are considered as possible Higgs boson candidates. To remove discrepancies between data and simulation originating from gluon splitting (g→bb¯), jet pairs which do not fulfill ΔR>1.0 are rejected.Six variables for which the data distributions are well modeled by the simulation are used to separate the jet pair from a Higgs boson from the background: Δη between the two jets in the pair, Δϕ between the two jets in the pair, the angle between the leading jet in the pair and the total momentum of the pair, the momentum balance in the pair,1010

The momentum balance is defined as |pb1−pb2|/|pb1+pb2|, where pbi is the magnitude of the momentum three vector of the ith b-quark jet.

the combined rapidity of the pair, and the event sphericity. Based on these kinematic variables a likelihood discriminant, D, is calculated according to:(2)D(x1,…,x6)=∏i=16Pisig(xi)∏i=16Pisig(xi)+∏i=16Pibkg(xi), where Pisig (Pibkg) refers to the signal (background) probability density function (pdf) for variable xi, and (x1,…,x6) is the set of measured kinematic variables. The pdfs are obtained from simulated triple b-tagged signal and background samples. Two likelihood discriminants, providing discrimination in the Higgs boson mass ranges 90–130 GeV (low-mass) and 130–300 GeV (high-mass), respectively, are built by combining simulated signal samples from the appropriate Higgs boson mass ranges. Signal samples of equal size, interspaced by 10 GeV in MA, are hence added together within the low-mass and high-mass range, respectively. After evaluating the likelihood, only the jet pairing with the larger D is kept for each event in each mass range. To further remove background from the final analysis sample, events are only selected if D>0.65. The likelihood requirements are optimized considering the variation of the predicted limit in tanβ. The final discriminant used in the limit calculation is the distribution of the jet pair invariant mass, Mbb¯, after the selection requirement of the likelihood appropriate to the mass of the hypothesized Higgs boson.The bb¯b background is indistinguishable from the signal events where the wrong b-jet pair is chosen by the likelihood and consequently cannot be normalized from the data. The Mbb¯ background shape is modeled using a combination of data and simulated samples. The distribution, S3Tagpred(D,Mbb¯), of the predicted triple b-tagged (3Tag) background sample in the two-dimensional D and Mbb¯ plane is obtained from the inclusive double b-tagged (2Tag) data shape multiplied by the ratio of the simulated shapes of the SM triple (S3TagMC) and double tagged events (S2TagMC):(3)S3Tagpred(D,Mbb¯)=S3TagMC(D,Mbb¯)S2TagMC(D,Mbb¯)S2Tagdata(D,Mbb¯).

Fig. 1

shows D for data and background for the low- and high-mass likelihoods in the three-jet channel. The shape of a signal distribution, normalized to the same number of events as data, is also shown. Fig. 2

shows the Mbb¯ distribution in the three-jet channel after the low- and high-mass likelihood selection requirements, respectively. The invariant mass of a Higgs boson signal in the three-jet channel is shown in Fig. 3

for three different values of MA.

To verify the background model a signal-depleted region is studied – any deviation observed there is unlikely to be as a result of signal and therefore would indicate a possible problem in the background modeling. A sample is hence chosen using the lower likelihood jet pairing and applying a selection of D<0.12 such that there is a low probability of signal contamination and a number of events comparable to that observed in the search region. Fig. 4

shows the invariant mass distributions for background and data in this sample. Agreement (χ2/n.d.f.=0.86) between the background model and the data is observed. This study was performed for each channel, data-taking period and for both high and low mass likelihoods with similar levels of agreement found in all cases. A wide variety of additional cross-checks were carried out, examining aspects of the event selection, b-tagging, and background modeling; no significant changes in the results were observed.

Sources of systematic uncertainty on both the signal normalization and shape are considered. The sources of systematic uncertainty on the signal included are: b-quark jet identification efficiency, b- and light-quark jet energy resolution, trigger modeling, jet energy calibration, jet identification, integrated luminosity, and theoretical models. The theoretical uncertainty on the signal cross section is estimated from mcfm[21] and consists of a contribution of 10% from the choice of factorization scale as well as an uncertainty of 5% to 13% from the parton distribution functions, depending on Higgs boson mass. Both the theoretical uncertainty and the luminosity uncertainty of 6.1% [13] are treated as normalization uncertainties for each mass hypothesis. The remaining sources of systematic uncertainty are assessed individually by varying parameters within their uncertainties and taking into account the resulting difference in normalization and shape of the Mbb¯ distribution at each mass point.For the dominant background, only systematic uncertainties affecting the shape of Mbb¯ matter, since only the shape and not the normalization is used to distinguish signal from background in this analysis. Additionally, many uncertainties affecting the simulation, like the jet energy scale and resolution uncertainties, cancel in Eq. (3). The estimated variations in the remaining systematic sources are propagated to D, Mbb¯ and the predicted shape S3Tagpred and used in assessing the limits presented below. The uncertainty from the b-tagging of jets is evaluated by varying the b-tag efficiencies within their uncertainties. The uncertainties in the difference of the energy resolution between heavy and light flavor jets is obtained by smearing the energy of the b- and c-quark jets by an additional 7%, corresponding to half the light-quark jet energy resolution. The shape difference between triple and double b-tagged data in the trigger turn-on curves resulting from the b-tagging criteria in the trigger is accounted for as a systematic uncertainty. Small variations in the shape, arising from possible signal contamination when determining the background composition, are included as a systematic uncertainty. Finally, the uncertainty on the tt¯ normalization is taken as 10% [25,26].No significant excess over the background is observed in the data. Limits on the Higgs boson production cross section multiplied by the branching ratio to bb¯ are therefore calculated with the modified frequentist method [14,27,28]. The confidence level of the signal, CLs, which is used to calculate the exclusion, is defined in Refs. [27,28]. The overall normalization of the background expectation is allowed to float independently in the null (background-only) and test (background-plus-signal) hypotheses. The systematic uncertainties on the signal and background are included in the limit setting procedure. Each component of systematic uncertainty is adjusted by introducing multiplicative scale factors and maximizing the likelihood for the agreement between prediction and data with respect to these scale factors, constrained by prior Gaussian uncertainties. Limits on the product of cross section and branching ratio are obtained by scaling the signal cross section until 1−CLs=0.95 is reached. These limits are effectively independent of the signal model but assume the width of the ϕ to be negligible relative to the experimental resolution (≈20% at MA=150 GeV). The four independent analysis channels are combined in the limit setting procedure. Signal hypotheses are considered for discrete Higgs boson mass points from 90 to 300 GeV in steps of 10 GeV. The treatment of the systematic uncertainties and the limit setting procedure were extensively cross-checked; no unexpected effects were observed.The combined result is summarized numerically in Table 2

and the model independent limit is shown in Fig. 5

. The deviation from expectation around 120 GeV corresponds to 2.5 standard deviations. Note that it is more likely to find a deviation (in the background-only hypothesis) when several mass bins are probed than if only one bin is probed. A standard convention to account for this “trial factor” [29] gives a significance of the deviation at 120 GeV of 2.0 standard deviations.

As a consequence of the enhanced couplings to b-quarks at large tanβ, the total width of the Higgs boson mass also increases with tanβ. This can have an impact on the search if the width is comparable to or larger than the experimental resolution. To take this effect into account, the width of the Higgs boson is calculated with feynhiggs[30–33] and included in the simulation as a function of the mass and tanβ by convoluting a relativistic Breit–Wigner function with the NLO cross section. The masses and couplings of the Higgs bosons in the MSSM depend, in addition to tanβ and MA, on the SUSY parameters through radiative corrections. Limits on tanβ as a function of MA are derived for two particular scenarios assuming a CP-conserving Higgs sector [34]: the mhmax

MSUSY=1 TeV, Xt=2 TeV, M2=0.2 TeV|μ|=0.2 TeV, and mg=0.8 TeV.

and no-mixing1212

MSUSY=2 TeV, Xt=0 TeV, M2=0.2 TeV|μ|=0.2 TeV, and mg=1.6 TeV.

scenarios with a negative or positive value of the Higgs sector bilinear coupling, μ. Fig. 6

shows the result interpreted for these two scenarios in the case of μ=−200 GeV. Weaker limits are obtained for the μ>0 scenarios, due to the decrease in the product of cross section and branching ratio for positive values of μ[34].

The results exclude substantial areas in the MSSM parameter space up to Higgs boson masses of 300 GeV, under the assumption that a perturbative treatment is valid over the entire region. These are the most stringent limits to date for this topology over this mass range at a hadron collider.

Acknowledgements

We thank the staffs at Fermilab and collaborating institutions, and acknowledge support from the DOE and NSF (USA); CEA and CNRS/IN2P3 (France); FASI, Rosatom and RFBR (Russia); CNPq, FAPERJ, FAPESP and FUNDUNESP (Brazil); DAE and DST (India); Colciencias (Colombia); CONACyT (Mexico); KRF and KOSEF (Korea); CONICET and UBACyT (Argentina); FOM (The Netherlands); STFC and the Royal Society (United Kingdom); MSMT and GACR (Czech Republic); CRC Program and NSERC (Canada); BMBF and DFG (Germany); SFI (Ireland); The Swedish Research Council (Sweden); and CAS and CNSF (China).

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