application/xmlSearch for supersymmetry in di-photon final states at [formula omitted]DØ CollaborationV.M. AbazovB. AbbottM. AbolinsB.S. AcharyaM. AdamsT. AdamsE. AguiloS.H. AhnM. AhsanG.D. AlexeevG. AlkhazovA. AltonG. AlversonG.A. AlvesM. AnastasoaieL.S. AncuT. AndeenS. AndersonB. AndrieuM.S. AnzelcY. ArnoudM. ArovM. ArthaudA. AskewB. ÅsmanA.C.S. Assis JesusO. AtramentovC. AutermannC. AvilaC. AyF. BadaudA. BadenL. BagbyB. BaldinD.V. BandurinS. BanerjeeP. BanerjeeE. BarberisA.-F. BarfussP. BargassaP. BaringerJ. BarretoJ.F. BartlettU. BasslerD. BauerS. BealeA. BeanM. BegalliM. BegelC. Belanger-ChampagneL. BellantoniA. BellavanceJ.A. BenitezS.B. BeriG. BernardiR. BernhardI. BertramM. BesançonR. BeuselinckV.A. BezzubovP.C. BhatV. BhatnagarC. BiscaratG. BlazeyF. BlekmanS. BlessingD. BlochK. BloomA. BoehnleinD. BolineT.A. BoltonG. BorissovT. BoseA. BrandtR. BrockG. BrooijmansA. BrossD. BrownN.J. BuchananD. BuchholzM. BuehlerV. BuescherS. BunichevS. BurdinS. BurkeT.H. BurnettC.P. BuszelloJ.M. ButlerP. CalfayanS. CalvetJ. CamminW. CarvalhoB.C.K. CaseyN.M. CasonH. Castilla-ValdezS. ChakrabartiD. ChakrabortyK.M. ChanK. ChanA. ChandraF. CharlesE. CheuF. ChevallierD.K. ChoS. ChoiB. ChoudharyL. ChristofekT. ChristoudiasS. CihangirD. ClaesY. CoadouM. CookeW.E. CooperM. CorcoranF. CoudercM.-C. CousinouS. Crépé-RenaudinD. CuttsM. ĆwiokH. da MottaA. DasG. DaviesK. DeS.J. de JongE. De La Cruz-BureloC. De Oliveira MartinsJ.D. DegenhardtF. DéliotM. DemarteauR. DeminaD. DenisovS.P. DenisovS. DesaiH.T. DiehlM. DiesburgA. DominguezH. DongL.V. DudkoL. DuflotS.R. DugadD. DugganA. DuperrinJ. DyerA. DyshkantM. EadsD. EdmundsJ. EllisonV.D. ElviraY. EnariS. EnoP. ErmolovH. EvansA. EvdokimovV.N. EvdokimovA.V. FerapontovT. FerbelF. FiedlerF. FilthautW. FisherH.E. FiskM. FordM. FortnerH. FoxS. FuS. FuessT. GadfortC.F. GaleaE. GallasE. GalyaevC. GarciaA. Garcia-BellidoV. GavrilovP. GayW. GeistD. GeléC.E. GerberYu. GershteinD. GillbergG. GintherN. GollubB. GómezA. GoussiouP.D. GrannisH. GreenleeZ.D. GreenwoodE.M. GregoresG. GrenierPh. GrisJ.-F. GrivazA. GrohsjeanS. GrünendahlM.W. GrünewaldJ. GuoF. GuoP. GutierrezG. GutierrezA. HaasN.J. HadleyP. HaefnerS. HagopianJ. HaleyI. HallR.E. HallL. HanK. HanagakiP. HanssonK. HarderA. HarelR. HarringtonJ.M. HauptmanR. HauserJ. HaysT. HebbekerD. HedinJ.G. HegemanJ.M. HeinmillerA.P. HeinsonU. HeintzC. HenselK. HernerG. HeskethM.D. HildrethR. HiroskyJ.D. HobbsB. HoeneisenH. HoethM. HohlfeldS.J. HongS. HossainP. HoubenY. HuZ. HubacekV. HynekI. IashviliR. IllingworthA.S. ItoS. JabeenM. JaffréS. JainK. JakobsC. JarvisR. JesikK. JohnsC. JohnsonM. JohnsonA. JonckheereP. JonssonA. JusteD. KäferE. KajfaszA.M. KalininJ.R. KalkJ.M. KalkS. KapplerD. KarmanovP. KasperI. KatsanosD. KauR. KaurV. KaushikR. KehoeS. KermicheN. KhalatyanA. KhanovA. KharchilavaY.M. KharzheevD. KhatidzeH. KimT.J. KimM.H. KirbyM. KirschB. KlimaJ.M. KohliJ.-P. KonrathM. KopalV.M. KorablevA.V. KozelovD. KropT. KuhlA. KumarS. KunoriA. KupcoT. KurčaJ. KvitaF. LacroixD. LamS. LammersG. LandsbergP. LebrunW.M. LeeA. LeflatF. LehnerJ. LellouchJ. LevequeP. LewisJ. LiQ.Z. LiL. LiS.M. LiettiJ.G.R. LimaD. LincolnJ. LinnemannV.V. LipaevR. LiptonY. LiuZ. LiuL. LoboA. LobodenkoM. LokajicekP. LoveH.J. LubattiA.L. LyonA.K.A. MacielD. MackinR.J. MadarasP. MättigC. MagassA. MagerkurthP.K. MalH.B. MalbouissonS. MalikV.L. MalyshevH.S. MaoY. MaravinB. MartinR. McCarthyA. MelnitchoukA. MendesL. MendozaP.G. MercadanteM. MerkinK.W. MerrittJ. MeyerA. MeyerT. MilletJ. MitrevskiJ. MolinaR.K. MommsenN.K. MondalR.W. MooreT. MoulikG.S. MuanzaM. MuldersM. MulhearnO. MundalL. MundimE. NagyM. NaimuddinM. NarainN.A. NaumannH.A. NealJ.P. NegretP. NeustroevH. NilsenH. NogimaA. NomerotskiS.F. NovaesT. NunnemannV. O'DellD.C. O'NeilG. ObrantC. OchandoD. OnoprienkoN. OshimaJ. OstaR. OtecG.J. Otero y GarzónM. OwenP. PadleyM. PangilinanN. ParasharS.-J. ParkS.K. ParkJ. ParsonsR. PartridgeN. ParuaA. PatwaG. PawloskiB. PenningM. PerfilovK. PetersY. PetersP. PétroffM. PetteniR. PiegaiaJ. PiperM.-A. PleierP.L.M. Podesta-LermaV.M. PodstavkovY. PogorelovM.-E. PolP. PolozovB.G. PopeA.V. PopovC. PotterW.L. Prado da SilvaH.B. ProsperS. ProtopopescuJ. QianA. QuadtB. QuinnA. RakitineM.S. RangelK. RanjanP.N. RatoffP. RenkelS. ReucroftP. RichM. RijssenbeekI. Ripp-BaudotF. RizatdinovaS. RobinsonR.F. RodriguesM. RominskyC. RoyonP. RubinovR. RuchtiG. SafronovG. SajotA. Sánchez-HernándezM.P. SandersA. SantoroG. SavageL. SawyerT. ScanlonD. SchaileR.D. SchambergerY. ScheglovH. SchellmanP. SchieferdeckerT. SchliephakeC. SchwanenbergerA. SchwartzmanR. SchwienhorstJ. SekaricH. SeveriniE. ShabalinaM. ShamimV. SharyA.A. ShchukinR.K. ShivpuriV. SiccardiV. SimakV. SirotenkoP. SkubicP. SlatteryD. SmirnovJ. SnowG.R. SnowS. SnyderS. Söldner-RemboldL. SonnenscheinA. SopczakM. SosebeeK. SoustruznikM. SouzaB. SpurlockJ. StarkJ. SteeleV. StolinD.A. StoyanovaJ. StrandbergS. StrandbergM.A. StrangM. StraussE. StraussR. StröhmerD. StromL. StutteS. SumowidagdoP. SvoiskyA. SznajderM. TalbyP. TamburelloA. TanasijczukW. TaylorJ. TempleB. TillerF. TissandierM. TitovV.V. TokmeninT. TooleI. TorchianiT. TrefzgerD. TsybychevB. TuchmingC. TullyP.M. TutsR. UnalanS. UvarovL. UvarovS. UzunyanB. VachonP.J. van den BergR. Van KootenW.M. van LeeuwenN. VarelasE.W. VarnesI.A. VasilyevM. VaupelP. VerdierL.S. VertogradovM. VerzocchiF. Villeneuve-SeguierP. VintP. VokacE. Von ToerneM. VoutilainenR. WagnerH.D. WahlL. WangM.H.L.S. WangJ. WarcholG. WattsM. WayneM. WeberG. WeberA. WengerN. WermesM. WetsteinA. WhiteD. WickeG.W. WilsonS.J. WimpennyM. WobischD.R. WoodT.R. WyattY. XieS. YacoobR. YamadaM. YanT. YasudaY.A. YatsunenkoK. YipH.D. YooS.W. YounJ. YuA. ZatserklyaniyC. ZeitnitzT. ZhaoB. ZhouJ. ZhuM. ZielinskiD. ZieminskaA. ZieminskiL. ZivkovicV. ZutshiE.G. ZverevPhysics Letters B 659 (2008) 856-863. doi:10.1016/j.physletb.2007.12.006journalPhysics Letters BCopyright © 2007 Elsevier B.V. All rights reserved.Elsevier B.V.0370-269365957 February 20082008-02-07856-86385686310.1016/j.physletb.2007.12.006http://dx.doi.org/10.1016/j.physletb.2007.12.006doi:10.1016/j.physletb.2007.12.006http://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

S300.2

PLB24567S0370-2693(07)01511-010.1016/j.physletb.2007.12.006Elsevier B.V.Experiments

Fig. 1

The E̸T distribution in γγ data with W/Z+γγ background (hatched histogram), instrumental background with no genuine E̸T: γγ (solid black line) and multi-jet (filled histogram), and background from processes with genuine E̸T and a misidentified electron (cross-hatched histogram). The expected E̸T distributions if GMSB SUSY events were present are shown as dotted and dashed lines.

Fig. 2

Predicted cross section for the Snowmass Slope model versus Λ. The observed and expected 95% C.L. limits are shown in solid and dash-dotted lines, respectively.

Table 1

Numbers of background events from Wγ, W+jet, and tt¯ (Genuine E̸T), no inherent E̸T (No E̸T), Zγγ→ννγγ and Wγγ→ℓγγν (Physics) processes; the total number of expected background events; numbers of expected GMSB SUSY signal events for two values of Λ; and the observed numbers of events for E̸T>30 GeV and 60 GeV. Errors are statistical and systematic combined

Background eventsExpected signal eventsObserved eventsGenuine E̸TNo E̸TPhysicsTotalΛ=75 TeVΛ=90 TeVE̸T>30 GeV0.97±0.129.62±1.120.19±0.0710.8±1.128.3±4.28.7±1.316E̸T>60 GeV0.11±0.041.44±0.430.08±0.041.6±0.418.1±2.76.4±1.03Table 2

Points on the GMSB Snowmass Slope model: neutralino and chargino masses, cross sections predicted by PYTHIA, k-factors, and reconstruction efficiencies with total uncertainty

Λ, TeVmχ˜10, GeVmχ˜1+, GeVσLO, fbk-factorEfficiency7093.7168.22151.210.17±0.0375101.0182.31481.200.18±0.0380108.5198.197.51.190.18±0.0385115.8212.065.41.180.19±0.0390123.0225.841.81.170.19±0.0395130.2239.729.51.160.20±0.03100137.4253.420.61.150.20±0.03105144.5267.014.41.140.18±0.03110151.7280.710.31.130.19±0.03Search for supersymmetry in di-photon final states at s=1.96 TeV

DØ Collaboration

V.M.

Abazov

Abbott

Abolins

B.S.

Acharya

Adams

Aguilo

S.H.

Ahn

Ahsan

G.D.

Alexeev

Alkhazov

Alton

Alverson

G.A.

Alves

Anastasoaie

L.S.

Ancu

Andeen

Anderson

Andrieu

M.S.

Anzelc

Arnoud

Arov

Arthaud

Askew

Åsman

A.C.S.

Assis Jesus

Atramentov

Autermann

Avila

Badaud

Baden

Bagby

Baldin

D.V.

Bandurin

Banerjee

Barberis

A.-F.

Barfuss

Bargassa

Baringer

Barreto

J.F.

Bartlett

Bassler

Bauer

Beale

Bean

Begalli

Begel

Belanger-Champagne

Bellantoni

Bellavance

J.A.

Benitez

S.B.

Beri

Bernardi

Bernhard

Bertram

Besançon

Beuselinck

V.A.

Bezzubov

P.C.

Bhat

Bhatnagar

Biscarat

Blazey

Blekman

Blessing

Bloch

Bloom

Boehnlein

Boline

T.A.

Bolton

Borissov

Bose

Brandt

Brock

Brooijmans

Bross

Brown

N.J.

Buchanan

Buchholz

Buehler

Buescher

Bunichev

Burdin

Burke

T.H.

Burnett

C.P.

Buszello

J.M.

Butler

Calfayan

Calvet

Cammin

Carvalho

B.C.K.

Casey

N.M.

Cason

Castilla-Valdez

Chakrabarti

Chakraborty

K.M.

Chan

Chandra

Charles

Cheu

Chevallier

D.K.

Cho

Choi

Choudhary

Christofek

Christoudias

✠

Cihangir

Claes

Coadou

Cooke

W.E.

Cooper

Corcoran

Couderc

M.-C.

Cousinou

Crépé-Renaudin

Cutts

Ćwiok

da Motta

Das

Davies

S.J.

de Jong

De La Cruz-Burelo

De Oliveira Martins

J.D.

Degenhardt

Déliot

Demarteau

Demina

Denisov

S.P.

Denisov

Desai

H.T.

Diehl

Diesburg

Dominguez

Dong

L.V.

Dudko

Duflot

S.R.

Dugad

Duggan

Duperrin

Dyer

Dyshkant

Eads

Edmunds

Ellison

V.D.

Elvira

Enari

Eno

Ermolov

Evans

Evdokimov

V.N.

Evdokimov

A.V.

Ferapontov

Ferbel

Fiedler

Filthaut

Fisher

H.E.

Fisk

Ford

Fortner

Fox

Fuess

Gadfort

C.F.

Galea

Gallas

Galyaev

Garcia

Garcia-Bellido

Gavrilov

Gay

Geist

Gelé

C.E.

Gerber

Yu.

Gershtein

⁎

gershtein@hep.fsu.edu

Gillberg

Ginther

Gollub

Gómez

Goussiou

P.D.

Grannis

Greenlee

Z.D.

Greenwood

E.M.

Gregores

Grenier

Ph.

Gris

J.-F.

Grivaz

Grohsjean

Grünendahl

M.W.

Grünewald

Guo

Gutierrez

Haas

N.J.

Hadley

Haefner

Hagopian

Haley

Hall

R.E.

Hall

Han

Hanagaki

Hansson

Harder

Harel

Harrington

J.M.

Hauptman

Hauser

Hays

Hebbeker

Hedin

J.G.

Hegeman

J.M.

Heinmiller

A.P.

Heinson

Heintz

Hensel

Herner

Hesketh

M.D.

Hildreth

Hirosky

J.D.

Hobbs

Hoeneisen

Hoeth

Hohlfeld

S.J.

Hong

Hossain

Houben

Hubacek

Hynek

Iashvili

Illingworth

A.S.

Ito

Jabeen

Jaffré

Jain

Jakobs

Jarvis

Jesik

Johns

Johnson

Jonckheere

Jonsson

Juste

Käfer

Kajfasz

A.M.

Kalinin

J.R.

Kalk

J.M.

Kalk

Kappler

Karmanov

Kasper

Katsanos

Kau

Kaur

Kaushik

Kehoe

Kermiche

Khalatyan

Khanov

Kharchilava

Y.M.

Kharzheev

Khatidze

Kim

T.J.

Kim

M.H.

Kirby

Kirsch

Klima

J.M.

Kohli

J.-P.

Konrath

Kopal

V.M.

Korablev

A.V.

Kozelov

Krop

Kuhl

Kumar

Kunori

Kupco

Kurča

Kvita

Lacroix

Lam

Lammers

Landsberg

Lebrun

W.M.

Lee

Leflat

Lehner

Lellouch

Leveque

Lewis

Q.Z.

S.M.

Lietti

J.G.R.

Lima

Lincoln

Linnemann

V.V.

Lipaev

Lipton

Liu

Lobo

Lobodenko

Lokajicek

Love

H.J.

Lubatti

A.L.

Lyon

A.K.A.

Maciel

Mackin

R.J.

Madaras

Mättig

Magass

Magerkurth

P.K.

Mal

H.B.

Malbouisson

Malik

V.L.

Malyshev

H.S.

Mao

Maravin

Martin

McCarthy

Melnitchouk

Mendes

Mendoza

P.G.

Mercadante

Merkin

K.W.

Merritt

Meyer

Millet

Mitrevski

Molina

R.K.

Mommsen

N.K.

Mondal

R.W.

Moore

Moulik

G.S.

Muanza

Mulders

Mulhearn

Mundal

Mundim

Nagy

Naimuddin

Narain

N.A.

Naumann

H.A.

Neal

J.P.

Negret

Neustroev

Nilsen

Nogima

Nomerotski

S.F.

Novaes

Nunnemann

O'Dell

D.C.

O'Neil

Obrant

Ochando

Onoprienko

Oshima

Osta

Otec

G.J.

Otero y Garzón

Owen

Padley

Pangilinan

Parashar

S.-J.

Park

S.K.

Park

Parsons

Partridge

Parua

Patwa

Pawloski

Penning

Perfilov

Peters

Pétroff

Petteni

Piegaia

Piper

M.-A.

Pleier

P.L.M.

Podesta-Lerma

V.M.

Podstavkov

Pogorelov

M.-E.

Pol

Polozov

B.G.

Pope

A.V.

Popov

Potter

W.L.

Prado da Silva

H.B.

Prosper

Protopopescu

Qian

Quadt

Quinn

Rakitine

M.S.

Rangel

Ranjan

P.N.

Ratoff

Renkel

Reucroft

Rich

Rijssenbeek

Ripp-Baudot

Rizatdinova

Robinson

R.F.

Rodrigues

Rominsky

Royon

Rubinov

Ruchti

Safronov

Sajot

Sánchez-Hernández

M.P.

Sanders

Santoro

Savage

Sawyer

Scanlon

Schaile

R.D.

Schamberger

Scheglov

Schellman

Schieferdecker

Schliephake

Schwanenberger

Schwartzman

Schwienhorst

Sekaric

Severini

Shabalina

Shamim

Shary

A.A.

Shchukin

R.K.

Shivpuri

Siccardi

Simak

Sirotenko

Skubic

Slattery

Smirnov

Snow

G.R.

Snow

Snyder

Söldner-Rembold

Sonnenschein

Sopczak

Sosebee

Soustruznik

Souza

Spurlock

Stark

Steele

Stolin

D.A.

Stoyanova

Strandberg

M.A.

Strang

Strauss

Ströhmer

Strom

Stutte

Sumowidagdo

Svoisky

Sznajder

Talby

Tamburello

Tanasijczuk

Taylor

Temple

Tiller

Tissandier

Titov

V.V.

Tokmenin

Toole

Torchiani

Trefzger

Tsybychev

Tuchming

Tully

P.M.

Tuts

Unalan

Uvarov

Uzunyan

Vachon

P.J.

van den Berg

Van Kooten

W.M.

van Leeuwen

Varelas

E.W.

Varnes

I.A.

Vasilyev

Vaupel

Verdier

L.S.

Vertogradov

Verzocchi

Villeneuve-Seguier

Vint

Vokac

Von Toerne

Voutilainen

Wagner

H.D.

Wahl

Wang

M.H.L.S.

Wang

Warchol

Watts

Wayne

Weber

Wenger

Wermes

Wetstein

White

Wicke

G.W.

Wilson

S.J.

Wimpenny

Wobisch

D.R.

Wood

T.R.

Wyatt

Xie

Yacoob

Yamada

Yan

Yasuda

Y.A.

Yatsunenko

Yip

H.D.

Yoo

S.W.

Youn

Zatserklyaniy

Zeitnitz

Zhao

Zhou

Zhu

Zielinski

Zieminska

Zieminski

Zivkovic

Zutshi

E.G.

Zverev

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, BrazilfUniversity of Alberta, Edmonton, Alberta, and Simon Fraser University, Burnaby, British Columbia, and York University, Toronto, Ontario, and McGill University, Montreal, Quebec, CanadagUniversity of Science and Technology of China, Hefei, People's Republic of ChinahUniversidad de los Andes, Bogotá, ColombiaiCenter for Particle Physics, Charles University, Prague, Czech RepublicjCzech Technical University, Prague, Czech RepublickCenter for Particle Physics, Institute of Physics, Academy of Sciences of the Czech Republic, Prague, Czech RepubliclUniversidad San Francisco de Quito, Quito, EcuadormLaboratoire de Physique Corpusculaire, IN2P3-CNRS, Université Blaise Pascal, Clermont-Ferrand, FrancenLaboratoire de Physique Subatomique et de Cosmologie, IN2P3-CNRS, Universite de Grenoble 1, Grenoble, FranceoCPPM, IN2P3-CNRS, Université de la Méditerranée, Marseille, FrancepLaboratoire de l'Accélérateur Linéaire, IN2P3-CNRS et Université Paris-Sud, Orsay, FranceqLPNHE, IN2P3-CNRS, Universités Paris VI and VII, Paris, FrancerDAPNIA/Service de Physique des Particules, CEA, Saclay, FrancesIPHC, Université Louis Pasteur et Université de Haute Alsace, CNRS, IN2P3, Strasbourg, FrancetIPNL, Université Lyon 1, CNRS/IN2P3, Villeurbanne, France and Université de Lyon, Lyon, FranceuIII. Physikalisches Institut A, RWTH Aachen, Aachen, GermanyvPhysikalisches Institut, Universität Bonn, Bonn, GermanywPhysikalisches Institut, Universität Freiburg, Freiburg, GermanyxInstitut für Physik, Universität Mainz, Mainz, GermanyyLudwig-Maximilians-Universität München, München, GermanyzFachbereich Physik, University of Wuppertal, Wuppertal, GermanyaaPanjab University, Chandigarh, IndiaabDelhi University, Delhi, IndiaacTata Institute of Fundamental Research, Mumbai, IndiaadUniversity College Dublin, Dublin, IrelandaeKorea Detector Laboratory, Korea University, Seoul, South KoreaafSungKyunKwan University, Suwon, South KoreaagCINVESTAV, Mexico City, MexicoahFOM-Institute NIKHEF and University of Amsterdam/NIKHEF, Amsterdam, The NetherlandsaiRadboud University Nijmegen/NIKHEF, Nijmegen, The NetherlandsajJoint Institute for Nuclear Research, Dubna, RussiaakInstitute for Theoretical and Experimental Physics, Moscow, RussiaalMoscow State University, Moscow, RussiaamInstitute for High Energy Physics, Protvino, RussiaanPetersburg Nuclear Physics Institute, St. Petersburg, RussiaaoLund University, Lund, and Royal Institute of Technology and Stockholm University, Stockholm, and Uppsala University, Uppsala, SwedenapPhysik Institut der Universität Zürich, Zürich, SwitzerlandaqLancaster University, Lancaster, United KingdomarImperial College, London, United KingdomasUniversity of Manchester, Manchester, United KingdomatUniversity of Arizona, Tucson, AZ 85721, USAauLawrence Berkeley National Laboratory and University of California, Berkeley, CA 94720, USAavCalifornia State University, Fresno, CA 93740, USAawUniversity of California, Riverside, CA 92521, USAaxFlorida State University, Tallahassee, FL 32306, USAayFermi National Accelerator Laboratory, Batavia, IL 60510, USAazUniversity of Illinois at Chicago, Chicago, IL 60607, USAbaNorthern Illinois University, DeKalb, IL 60115, USAbbNorthwestern University, Evanston, IL 60208, USAbcIndiana University, Bloomington, IN 47405, USAbdUniversity of Notre Dame, Notre Dame, IN 46556, USAbePurdue University Calumet, Hammond, IN 46323, USAbfIowa State University, Ames, IA 50011, USAbgUniversity of Kansas, Lawrence, KS 66045, USAbhKansas State University, Manhattan, KS 66506, USAbiLouisiana Tech University, Ruston, LA 71272, USAbjUniversity of Maryland, College Park, MD 20742, USAbkBoston University, Boston, MA 02215, USAblNortheastern University, Boston, MA 02115, USAbmUniversity of Michigan, Ann Arbor, MI 48109, USAbnMichigan State University, East Lansing, MI 48824, USAboUniversity of Mississippi, University, MS 38677, USAbpUniversity of Nebraska, Lincoln, NE 68588, USAbqPrinceton University, Princeton, NJ 08544, USAbrState University of New York, Buffalo, NY 14260, USAbsColumbia University, New York, NY 10027, USAbtUniversity of Rochester, Rochester, NY 14627, USAbuState University of New York, Stony Brook, NY 11794, USAbvBrookhaven National Laboratory, Upton, NY 11973, USAbwLangston University, Langston, OH 73050, USAbxUniversity of Oklahoma, Norman, OH 73019, USAbyOklahoma State University, Stillwater, OH 74078, USAbzBrown University, Providence, RI 02912, USAcaUniversity of Texas, Arlington, TX 76019, USAcbSouthern Methodist University, Dallas, TX 75275, USAccRice University, Houston, TX 77005, USAcdUniversity of Virginia, Charlottesville, VA 22901, USAceUniversity of Washington, Seattle, WA 98195, USA⁎Corresponding author.1

Visitor from Augustana College, Sioux Falls, SD, USA.

Visitor from The University of Liverpool, Liverpool, UK.

Fermilab International Fellow.

Visitor from II. Physikalisches Institut, Georg-August-University Göttingen, Germany.

Visitor from ICN-UNAM, Mexico City, Mexico.

Visitor from Helsinki Institute of Physics, Helsinki, Finland.

Visitor from Universität Zürich, Zürich, Switzerland.

✠

Deceased.

Editor: L. Rolandi

Abstract

We report results of a search for supersymmetry (SUSY) with gauge-mediated symmetry breaking in di-photon events collected by the D0 experiment at the Fermilab Tevatron Collider in 2002–2006. In 1.1 fb−1 of data, we find no significant excess beyond the background expected from the standard model and set the most stringent lower limits to date for a standard benchmark model on the lightest neutralino and chargino masses of 125 GeV and 229 GeV, respectively, at 95% confidence.

PACS

14.80.Ly12.60.Jv13.85.Rm

Low-scale SUSY is one of the most promising solutions to the hierarchy problem associated with the intrinsic disparity between the electroweak and Planck scales. It postulates that for each known particle there exists a superpartner, thereby stabilizing the radiative corrections to the Higgs boson mass. Bosons have fermion superpartners, and vice versa. None of the superpartners have yet been observed, and superpartner masses must therefore be much larger than those of their partners, i.e., SUSY is a broken symmetry. Experimental signatures of supersymmetry are determined through the manner and scale of SUSY breaking. In models with gauge-mediated supersymmetry breaking (GMSB) [1,2], it is achieved through the introduction of new chiral supermultiplets, called messengers that couple to the ultimate source of supersymmetry breaking and to the SUSY particles. At colliders, assuming R-parity conservation [3], superpartners are produced in pairs (χ˜1+χ˜1− and χ˜1±χ˜20 production dominates in most cases) and decay to the standard model particles and next-to-lightest SUSY particle (NLSP), which can be either a neutralino or a slepton. In the former case, which is considered in this note, the NLSP decays into a photon and a gravitino (the lightest superpartner in GMSB SUSY models, with mass less than ≈1 keV). The gravitino is stable, and escapes detection, creating an apparent imbalance in transverse momentum (E̸T) in the event. GMSB SUSY final states are therefore characterized by two energetic photons and large missing transverse momentum. The differences in event kinematics between particular GMSB SUSY models result in slightly different experimental sensitivities [4], and to obtain a quantitative measure of limits on SUSY we consider a model referred to as “Snowmass Slope SPS 8”[5]. This model has only a single dimensioned parameter: an energy scale Λ that determines the effective scale of SUSY breaking. The minimal GMSB parameters correspond to a messenger mass Mm=2Λ, the number of messengers N5=1, the ratio of the vacuum expectation values of the two Higgs fields tanβ=15, and the sign of the Higgsino mass term μ>0. The neutralino lifetime is not defined within the model. For this analysis, it is assumed to be sufficiently short to yield decays with prompt photons.Searches for GMSB SUSY were carried out by collaborations at the CERN LEP collider [6] and at the Fermilab Tevatron collider in both Run I [7] and early in Run II [4,8]. The initial limits from CDF and D0 for Run II, based on the SPS 8 model, were combined [9] to yield Λ>84.6 TeV corresponding to the limit on the chargino mass of 209 GeV, at 95% confidence. Complementary searches for GMSB SUSY with R-parity violation were performed by the H1 experiment at HERA [10].This analysis is an update of that described in Ref. [4], with about a factor of three more data and improved photon identification based on: (i) an electromagnetic (EM) cluster “pointing” algorithm that predicts the origin of a photon with a resolution of about 2 cm along the beam axis, thereby eliminating the largest instrumental background associated with mis-reconstruction of the primary interaction vertex, and (ii) an improved track veto requirement that suppresses sources of background with electrons in the final state. We also use an improved likelihood fitter [11] to set limits on the scale parameter Λ.The data in this analysis were recorded using single EM triggers with the D0 detector [12], the main components of which are an inner tracker, liquid-argon/uranium calorimeters, and a muon spectrometer. The inner tracker consists of silicon microstrip and central scintillating-fiber trackers located in a 2 T superconducting solenoidal magnet, providing measurements up to pseudorapidities88

Pseudorapidity is defined as −log(tan(θ2)), where θ is the angle between the particle and the proton beam direction.

of |η|≈3.0 and |η|≈1.8, respectively. The calorimeters are finely segmented and consist of a central section (CC) covering |η|<1.2 and two endcap calorimeters extending coverage to |η|≈4, all housed in separate cryostats [13]. The electromagnetic section of the calorimeter has four longitudinal layers and transverse segmentation of 0.1×0.1 in η–ϕ space (where ϕ is the azimuthal angle), except in the third layer, where it is 0.05×0.05. The central preshower (CPS) system is placed between the solenoid and the calorimeter cryostat and covers |η|≲1.2. The CPS provides precise measurement of positions of EM showers. The axes of EM showers are reconstructed by fitting straight lines to shower positions measured in the four longitudinal calorimeter layers and the CPS (EM “pointing”). The data for this study were collected between 2002 and summer 2006, using inclusive single EM triggers that are almost 100% efficient to select signal data. The integrated luminosity [14] of the sample is 1100±70 pb−1.Photons and electrons are identified based on reconstructed EM clusters using calorimetric information and further classified into electron and photon candidates, based on tracking information. The EM clusters are selected from calorimeter clusters using the simple cone method (of radius R=(Δη)2+(Δϕ)2=0.4) by requiring that (i) at least 90% of the energy is deposited in the EM section of the calorimeter, (ii) the calorimeter isolation variable I=[Etot(0.4)−EEM(0.2)]/EEM(0.2) is less than 0.07, where Etot(0.4) is the total shower energy in a cone of radius R=0.4, and EEM(0.2) is the EM energy in a cone of radius R=0.2, (iii) the transverse, energy-weighted, width of the EM cluster in the third EM calorimeter layer is smaller than 0.04 rad, and (iv) the scalar sum of the transverse momenta (pT) of all tracks originating from the primary vertex in an annulus of 0.05<R<0.4 around the cluster is less than 2 GeV. The isolation criteria are tuned so that photons that convert in the tracker material are not rejected. The EM cluster is further defined as an electron candidate if it is spatially matched to activity in the tracker, and as a photon candidate otherwise. The tracker activity can be either a reconstructed track or a density of hits in the silicon microstrip and central fiber trackers consistent with a track, i.e., an electron. The latter requirement allows for increasing electron track-matching efficiency, ϵtrk, measured in Z→ee data, from (93.0±0.1)% to (98.6±0.1)% by identifying electrons with lost tracks due to hard bremsstrahlung and/or inefficiency of the inner trackers. This reduces electron backgrounds to photons by a factor of five, while keeping the efficiency of anti-track activity requirement high. We measure that (91±3)% of photon candidates in Z→eeγ data satisfy the anti-track activity requirement.Jets are reconstructed using the iterative, midpoint cone algorithm [15] with a cone size of R=0.5. The missing transverse energy is determined from the energy deposited in the calorimeter for |η|<4 and is corrected for the EM and jet energy scales.We select γγ candidates by requiring events to have two photon candidates, each with transverse energy ET>25 GeV identified in the CC with |η|<1.1. We require that at least one of the photon candidates be matched to a CPS cluster, and that the primary vertex be consistent with that of the photon candidate (obtained from the EM pointing). The accuracy of the determination of the photon vertex is measured using photons from final state radiation in Z→eeγ data sample and found to be 2.3±0.3 cm. The requirement of consistency between the photon and primary vertices ensures correct calculation of the transverse energies and tracking isolation requirements. The accuracy of primary vertex association is studied in GMSB SUSY Monte Carlo simulated events, where the primary vertex is identified correctly in (98.5±0.1)% of the events while the photon vertex matches the primary vertex in (95.8±0.1)%.To reduce potential bias in the measurement of E̸T from mis-measurement of jet transverse momentum, we also require that the jet with the highest ET (if jets are present in the event) be separated from the E̸T in azimuth by no more than 2.5 radians. This selection yields 2341 events (the γγ sample).All instrumental backgrounds arise from standard model processes, with either genuine E̸T (Wγ, W+jet, and tt¯ production) or without inherent E̸T (direct photon, multi-jet, and Z→ee production). All these backgrounds are measured using data.The former source always has an electron in the final state which is misidentified as a photon. The contribution of this background to the E̸T distribution in data can be estimated using an eγ sample (selected by requiring an electron and a photon candidate and using the same kinematical requirements as for the γγ sample) scaled by the probability of an electron–photon misidentification which is measured using Z→ee data. First, the E̸T distribution in the eγ sample must be corrected for the contribution from events with no real E̸T. The contribution from Drell–Yan events is taken into account by obtaining the E̸T distribution for the ee sample (selected by requiring two electron candidates and applying the same kinematical requirements as for the γγ sample) which is dominated by Drell–Yan events. The Drell–Yan E̸T distribution is further normalized to the number of Z boson events in the eγ sample (the latter is determined by fitting the eγ invariant mass spectrum to the Z boson mass peak).The contribution from the multi-jet processes is estimated from a data sample (referred to as the QCD sample) selected by requiring two EM clusters that (a) satisfy all the kinematic selection used to select γγ sample and (b) satisfy all the photon identification criteria but fail the shower shape requirement. The E̸T distribution in the QCD sample is normalized to the number of the events in the eγ sample with E̸T<12 GeV after subtraction of the Drell–Yan contribution as determined above. The expected number of Wγ, W+jet, and tt¯ events with E̸T<12 GeV is negligible.After the Drell–Yan and multi-jet contributions to the eγ sample are subtracted, the resulting E̸T distribution is scaled by (1−ϵtrk)/ϵtrk, where ϵtrk is the efficiency of the track-matching requirement to obtain the estimate of E̸T distribution for the background with genuine E̸T.The background from events with no inherent E̸T is divided into multi-jet events with two real isolated photons and events where one or both photons are misidentified jets. Since the E̸T resolution for both sources is dominated by the photon energy resolution, the E̸T distributions for the two sources are very similar. However, misidentified jets have a different energy response compared with that of real photons which leads to a slight difference in the shapes of the E̸T distributions. For the real di-photon events, the E̸T is assumed to have the same shape as that of the Drell–Yan events. For misidentified jets, the shape of the E̸T distribution is taken from the QCD sample. Relative normalization of the two sources is obtained using a fit to the E̸T distribution in the γγ sample. We check that the fit is not sensitive to possible signal contribution, and cross-check with a method that estimates the γγ sample purity using the measured shower shape in the CPS. The relative fraction of di-photons is (60±20)% and this uncertainty is propagated as a systematic uncertainty for the limit setting. Absolute normalization of the E̸T distributions from both sources is determined so that the number of events with E̸T<12 GeV matches that in the γγ sample.The largest physics backgrounds are from Zγγ→ννγγ and Wγγ→ℓγγν processes. Contributions from these backgrounds are estimated as 0.15±0.06 and 0.10±0.04 events, respectively, using CompHep[16] Monte Carlo simulation, cross-checked with MadGraph[17]. The contribution of these backgrounds to the E̸T distribution is taken from Monte Carlo simulation, with number of events normalized to the integrated luminosity of the data sample.The E̸T distribution for the γγ sample, with contributions from physics background (W/Z+γγ), and instrumental background with genuine E̸T (processes with mis-identified electrons) and no inherent E̸T (γγ and multi-jet) is given in Fig. 1

. We also illustrate the E̸T distribution expected from GMSB SUSY for two values of Λ. The number of observed events, as well as expected background and signal from GMSB SUSY for E̸T>30 GeV and >60 GeV are given in Table 1

The expected GMSB signal efficiency is estimated from Monte Carlo simulation generated for several points on the Snowmass Slope (see Table 2

), covering the neutralino mass range from 170 GeV to 280 GeV. Although χ˜1+χ˜1− and χ˜1±χ˜20 processes dominate, we consider all GMSB SUSY production channels. We used ISAJET 7.58[18] to determine SUSY interaction eigenstate masses and couplings. PYTHIA 6.319[19] is used to generate the events after determining the sparticle masses, branching fractions and leading order (LO) production cross sections using CTEQ6L1 parton distributions [20]. The generated events are processed through a full GEANT-based [21] detector simulation and the same reconstruction code as used for data. The LO signal cross sections are scaled to match the next-to-leading order (NLO) prediction using k-factor values (see Table 2), extracted from Ref. [22].

The systematic error on the expected number of signal events comes from the uncertainties in photon identification efficiency (10%), statistics in MC samples (5%), track veto requirement (3%), and trigger efficiency (4%). These were obtained using Z→e+e− and Z→e+e−γ decays in data and in MC simulation. Variation of parton distribution functions and uncertainty in the total integrated luminosity result in additional 4% and 6.1% errors in signal yield respectively. The total uncertainty on the background is dominated by statistics.As the observed number of events for all values of E̸T is in good agreement with the standard model prediction, we conclude that there is no evidence for GMSB SUSY in the data. We set limits on the production cross section by utilizing a likelihood fitter [11] that incorporates a log-likelihood ratio (LLR) test statistic method. This method utilizes binned E̸T distributions rather than a single-bin (fully-integrated) value, and therefore accounts for the shapes of the distributions, leading to greater sensitivity. The value of the confidence level for the signal CLs is defined as CLs=CLs+b/CLb, where CLs+b and CLb are the confidence levels for the signal plus background hypothesis and the background-only (null) hypothesis, respectively. These confidence levels are evaluated by integrating corresponding LLR distributions populated by simulating outcomes via Poisson statistics. Systematic uncertainties are treated as uncertainties on the expected numbers of signal and background events, not the outcomes of the limit calculations. The degrading effects of systematic uncertainties are reduced by introducing a maximum likelihood fit to the missing transverse energy distribution. A separate fit is performed for both the background-only and signal-plus-background hypotheses for each data or pseudo-data distribution.The limits are shown in Fig. 2

together with expected signal cross sections. The observed limits are statistically compatible with the expected limits. The observed upper limit on the signal cross section is below the prediction of the Snowmass Slope model for Λ<91.5 TeV, or in terms of gaugino masses, mχ˜10<125 GeV and mχ˜1+<229 GeV. These represent the most stringent limits on this particular GMSB SUSY model to date.

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); CAPES, CNPq, FAPERJ, FAPESP and FUNDUNESP (Brazil); DAE and DST (India); Colciencias (Colombia); CONACyT (Mexico); KRF and KOSEF (South Korea); CONICET and UBACyT (Argentina); FOM (The Netherlands); Science and Technology Facilities Council (United Kingdom); MSMT and GACR (Czech Republic); CRC Program, CFI, NSERC and WestGrid Project (Canada); BMBF and DFG (Germany); SFI (Ireland); The Swedish Research Council (Sweden); CAS and CNSF (China); Alexander von Humboldt Foundation; and the Marie Curie Program.

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