Search for associated production of charginos and neutralinos in the trilepton final state using 2.3 fb-1 of data
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Search for associated production of charginos and neutralinos in the trilepton finalstate using 2.3 fb − of data V.M. Abazov , B. Abbott , M. Abolins , B.S. Acharya , M. Adams , T. Adams , E. Aguilo ,M. Ahsan , G.D. Alexeev , G. Alkhazov , A. Alton ,a , G. Alverson , G.A. Alves , M. Anastasoaie ,L.S. Ancu , T. Andeen , B. Andrieu , M.S. Anzelc , M. Aoki , Y. Arnoud , M. Arov , M. Arthaud ,A. Askew ,b , B. ˚Asman , A.C.S. Assis Jesus , O. Atramentov , C. Avila , J. BackusMayes , F. Badaud ,L. Bagby , B. Baldin , D.V. Bandurin , P. Banerjee , S. Banerjee , E. Barberis , A.-F. Barfuss ,P. Bargassa , P. Baringer , J. Barreto , J.F. Bartlett , U. Bassler , D. Bauer , S. Beale , A. Bean ,M. Begalli , M. Begel , C. Belanger-Champagne , L. Bellantoni , A. Bellavance , J.A. Benitez , S.B. Beri ,G. Bernardi , R. Bernhard , I. Bertram , M. Besan¸con , R. Beuselinck , V.A. Bezzubov , P.C. Bhat ,V. Bhatnagar , G. Blazey , F. Blekman , S. Blessing , K. Bloom , A. Boehnlein , D. Boline , T.A. Bolton ,E.E. Boos , G. Borissov , T. Bose , A. Brandt , R. Brock , G. Brooijmans , A. Bross , D. Brown ,X.B. Bu , N.J. Buchanan , D. Buchholz , M. Buehler , V. Buescher , V. Bunichev , S. Burdin ,c ,T.H. Burnett , C.P. Buszello , P. Calfayan , B. Calpas , S. Calvet , J. Cammin , M.A. Carrasco-Lizarraga ,E. Carrera , W. Carvalho , B.C.K. Casey , H. Castilla-Valdez , S. Chakrabarti , D. Chakraborty ,K.M. Chan , A. Chandra , E. Cheu , D.K. Cho , S. Choi , B. Choudhary , L. Christofek , T. Christoudias ,S. Cihangir , D. Claes , J. Clutter , M. Cooke , W.E. Cooper , M. Corcoran , F. Couderc ,M.-C. Cousinou , S. Cr´ep´e-Renaudin , V. Cuplov , D. Cutts , M. ´Cwiok , H. da Motta , A. Das ,G. Davies , K. De , S.J. de Jong , E. De La Cruz-Burelo , C. De Oliveira Martins , K. DeVaughan ,F. D´eliot , M. Demarteau , R. Demina , D. Denisov , S.P. Denisov , S. Desai , H.T. Diehl , M. Diesburg ,A. Dominguez , T. Dorland , A. Dubey , L.V. Dudko , L. Duflot , S.R. Dugad , D. Duggan , A. Duperrin ,S. Dutt , J. Dyer , A. Dyshkant , M. Eads , D. Edmunds , J. Ellison , V.D. Elvira , Y. Enari , S. Eno ,P. Ermolov , ‡ , M. Escalier , H. Evans , A. Evdokimov , V.N. Evdokimov , A.V. Ferapontov , T. Ferbel , ,F. Fiedler , F. Filthaut , W. Fisher , H.E. Fisk , M. Fortner , H. Fox , S. Fu , S. Fuess , T. Gadfort ,C.F. Galea , C. Garcia , A. Garcia-Bellido , V. Gavrilov , P. Gay , W. Geist , W. Geng , , C.E. Gerber ,Y. Gershtein ,b , D. Gillberg , G. Ginther , B. G´omez , A. Goussiou , P.D. Grannis , H. Greenlee ,Z.D. Greenwood , E.M. Gregores , G. Grenier , Ph. Gris , J.-F. Grivaz , A. Grohsjean , S. Gr¨unendahl ,M.W. Gr¨unewald , F. Guo , J. Guo , G. Gutierrez , P. Gutierrez , A. Haas , N.J. Hadley , P. Haefner ,S. Hagopian , J. Haley , I. Hall , R.E. Hall , L. Han , K. Harder , A. Harel , J.M. Hauptman , J. Hays ,T. Hebbeker , D. Hedin , J.G. Hegeman , A.P. Heinson , U. Heintz , C. Hensel ,d , K. Herner , G. Hesketh ,M.D. Hildreth , R. Hirosky , T. Hoang , J.D. Hobbs , B. Hoeneisen , M. Hohlfeld , S. Hossain , P. Houben ,Y. Hu , Z. Hubacek , N. Huske , V. Hynek , I. Iashvili , R. Illingworth , A.S. Ito , S. Jabeen , M. Jaffr´e ,S. Jain , K. Jakobs , C. Jarvis , R. Jesik , K. Johns , C. Johnson , M. Johnson , D. Johnston ,A. Jonckheere , P. Jonsson , A. Juste , E. Kajfasz , D. Karmanov , P.A. Kasper , I. Katsanos ,V. Kaushik , R. Kehoe , S. Kermiche , N. Khalatyan , A. Khanov , A. Kharchilava , Y.N. Kharzheev ,D. Khatidze , T.J. Kim , M.H. Kirby , M. Kirsch , B. Klima , J.M. Kohli , J.-P. Konrath , A.V. Kozelov ,J. Kraus , T. Kuhl , A. Kumar , A. Kupco , T. Kurˇca , V.A. Kuzmin , J. Kvita , F. Lacroix , D. Lam ,S. Lammers , G. Landsberg , P. Lebrun , W.M. Lee , A. Leflat , J. Lellouch , J. Li , ‡ , L. Li , Q.Z. Li ,S.M. Lietti , J.K. Lim , J.G.R. Lima , D. Lincoln , J. Linnemann , V.V. Lipaev , R. Lipton , Y. Liu , Z. Liu ,A. Lobodenko , M. Lokajicek , P. Love , H.J. Lubatti , R. Luna-Garcia ,e , A.L. Lyon , A.K.A. Maciel ,D. Mackin , R.J. Madaras , P. M¨attig , A. Magerkurth , P.K. Mal , H.B. Malbouisson , S. Malik ,V.L. Malyshev , Y. Maravin , B. Martin , R. McCarthy , M.M. Meijer , A. Melnitchouk , L. Mendoza ,P.G. Mercadante , M. Merkin , K.W. Merritt , A. Meyer , J. Meyer ,d , J. Mitrevski , R.K. Mommsen ,N.K. Mondal , R.W. Moore , T. Moulik , G.S. Muanza , M. Mulhearn , O. Mundal , L. Mundim , E. Nagy ,M. Naimuddin , M. Narain , H.A. Neal , J.P. Negret , P. Neustroev , H. Nilsen , H. Nogima , S.F. Novaes ,T. Nunnemann , D.C. O’Neil , G. Obrant , C. Ochando , D. Onoprienko , N. Oshima , N. Osman , J. Osta ,R. Otec , G.J. Otero y Garz´on , M. Owen , M. Padilla , P. Padley , M. Pangilinan , N. Parashar ,S.-J. Park ,d , S.K. Park , J. Parsons , R. Partridge , N. Parua , A. Patwa , G. Pawloski , B. Penning ,M. Perfilov , K. Peters , Y. Peters , P. P´etroff , M. Petteni , R. Piegaia , J. Piper , M.-A. Pleier ,P.L.M. Podesta-Lerma ,f , V.M. Podstavkov , Y. Pogorelov , M.-E. Pol , P. Polozov , B.G. Pope ,A.V. Popov , C. Potter , W.L. Prado da Silva , H.B. Prosper , S. Protopopescu , J. Qian , A. Quadt ,d ,B. Quinn , A. Rakitine , M.S. Rangel , K. Ranjan , P.N. Ratoff , P. Renkel , P. Rich , M. Rijssenbeek ,I. Ripp-Baudot , F. Rizatdinova , S. Robinson , R.F. Rodrigues , M. Rominsky , C. Royon , P. Rubinov ,R. Ruchti , G. Safronov , G. Sajot , A. S´anchez-Hern´andez , M.P. Sanders , B. Sanghi , G. Savage ,L. Sawyer , T. Scanlon , D. Schaile , R.D. Schamberger , Y. Scheglov , H. Schellman , T. Schliephake ,S. Schlobohm , C. Schwanenberger , R. Schwienhorst , J. Sekaric , H. Severini , E. Shabalina , M. Shamim ,V. Shary , A.A. Shchukin , R.K. Shivpuri , V. Siccardi , V. Simak , V. Sirotenko , P. Skubic , P. Slattery ,D. Smirnov , G.R. Snow , J. Snow , S. Snyder , S. S¨oldner-Rembold , L. Sonnenschein , A. Sopczak ,M. Sosebee , K. Soustruznik , B. Spurlock , J. Stark , V. Stolin , D.A. Stoyanova , J. Strandberg ,S. Strandberg , M.A. Strang , E. Strauss , M. Strauss , R. Str¨ohmer , D. Strom , L. Stutte ,S. Sumowidagdo , P. Svoisky , A. Sznajder , A. Tanasijczuk , W. Taylor , B. Tiller , F. Tissandier ,M. Titov , V.V. Tokmenin , I. Torchiani , D. Tsybychev , B. Tuchming , C. Tully , P.M. Tuts , R. Unalan ,L. Uvarov , S. Uvarov , S. Uzunyan , B. Vachon , P.J. van den Berg , R. Van Kooten , W.M. van Leeuwen ,N. Varelas , E.W. Varnes , I.A. Vasilyev , P. Verdier , L.S. Vertogradov , M. Verzocchi , D. Vilanova ,F. Villeneuve-Seguier , P. Vint , P. Vokac , M. Voutilainen ,g , R. Wagner , H.D. Wahl , M.H.L.S. Wang ,J. Warchol , G. Watts , M. Wayne , G. Weber , M. Weber ,h , L. Welty-Rieger , A. Wenger ,i , N. Wermes ,M. Wetstein , A. White , D. Wicke , M.R.J. Williams , G.W. Wilson , S.J. Wimpenny , M. Wobisch ,D.R. Wood , T.R. Wyatt , Y. Xie , C. Xu , S. Yacoob , R. Yamada , W.-C. Yang , T. Yasuda ,Y.A. Yatsunenko , Z. Ye , H. Yin , K. Yip , H.D. Yoo , S.W. Youn , J. Yu , C. Zeitnitz , S. Zelitch ,T. Zhao , B. Zhou , J. Zhu , M. Zielinski , D. Zieminska , L. Zivkovic , V. Zutshi , and E.G. Zverev (The DØ Collaboration) Universidad de Buenos Aires, Buenos Aires, Argentina LAFEX, Centro Brasileiro de Pesquisas F´ısicas, Rio de Janeiro, Brazil Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil Universidade Federal do ABC, Santo Andr´e, Brazil Instituto de F´ısica Te´orica, Universidade Estadual Paulista, S˜ao Paulo, Brazil University of Alberta, Edmonton, Alberta, Canada,Simon Fraser University, Burnaby, British Columbia,Canada, York University, Toronto, Ontario, Canada,and McGill University, Montreal, Quebec, Canada University of Science and Technology of China, Hefei, People’s Republic of China Universidad de los Andes, Bogot´a, Colombia Center for Particle Physics, Charles University, Prague, Czech Republic Czech Technical University, Prague, Czech Republic Center for Particle Physics, Institute of Physics,Academy of Sciences of the Czech Republic, Prague, Czech Republic Universidad San Francisco de Quito, Quito, Ecuador LPC, Universit´e Blaise Pascal, CNRS/IN2P3, Clermont, France LPSC, Universit´e Joseph Fourier Grenoble 1, CNRS/IN2P3,Institut National Polytechnique de Grenoble, Grenoble, France CPPM, Aix-Marseille Universit´e, CNRS/IN2P3, Marseille, France LAL, Universit´e Paris-Sud, IN2P3/CNRS, Orsay, France LPNHE, IN2P3/CNRS, Universit´es Paris VI and VII, Paris, France CEA, Irfu, SPP, Saclay, France IPHC, Universit´e Louis Pasteur, CNRS/IN2P3, Strasbourg, France IPNL, Universit´e Lyon 1, CNRS/IN2P3, Villeurbanne, France and Universit´e de Lyon, Lyon, France III. Physikalisches Institut A, RWTH Aachen University, Aachen, Germany Physikalisches Institut, Universit¨at Bonn, Bonn, Germany Physikalisches Institut, Universit¨at Freiburg, Freiburg, Germany Institut f¨ur Physik, Universit¨at Mainz, Mainz, Germany Ludwig-Maximilians-Universit¨at M¨unchen, M¨unchen, Germany Fachbereich Physik, University of Wuppertal, Wuppertal, Germany Panjab University, Chandigarh, India Delhi University, Delhi, India Tata Institute of Fundamental Research, Mumbai, India University College Dublin, Dublin, Ireland Korea Detector Laboratory, Korea University, Seoul, Korea SungKyunKwan University, Suwon, Korea CINVESTAV, Mexico City, Mexico FOM-Institute NIKHEF and University of Amsterdam/NIKHEF, Amsterdam, The Netherlands Radboud University Nijmegen/NIKHEF, Nijmegen, The Netherlands Joint Institute for Nuclear Research, Dubna, Russia Institute for Theoretical and Experimental Physics, Moscow, Russia Moscow State University, Moscow, Russia Institute for High Energy Physics, Protvino, Russia Petersburg Nuclear Physics Institute, St. Petersburg, Russia Lund University, Lund, Sweden, Royal Institute of Technology and Stockholm University,Stockholm, Sweden, and Uppsala University, Uppsala, Sweden Lancaster University, Lancaster, United Kingdom Imperial College, London, United Kingdom University of Manchester, Manchester, United Kingdom University of Arizona, Tucson, Arizona 85721, USA Lawrence Berkeley National Laboratory and University of California, Berkeley, California 94720, USA California State University, Fresno, California 93740, USA University of California, Riverside, California 92521, USA Florida State University, Tallahassee, Florida 32306, USA Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA University of Illinois at Chicago, Chicago, Illinois 60607, USA Northern Illinois University, DeKalb, Illinois 60115, USA Northwestern University, Evanston, Illinois 60208, USA Indiana University, Bloomington, Indiana 47405, USA University of Notre Dame, Notre Dame, Indiana 46556, USA Purdue University Calumet, Hammond, Indiana 46323, USA Iowa State University, Ames, Iowa 50011, USA University of Kansas, Lawrence, Kansas 66045, USA Kansas State University, Manhattan, Kansas 66506, USA Louisiana Tech University, Ruston, Louisiana 71272, USA University of Maryland, College Park, Maryland 20742, USA Boston University, Boston, Massachusetts 02215, USA Northeastern University, Boston, Massachusetts 02115, USA University of Michigan, Ann Arbor, Michigan 48109, USA Michigan State University, East Lansing, Michigan 48824, USA University of Mississippi, University, Mississippi 38677, USA University of Nebraska, Lincoln, Nebraska 68588, USA Princeton University, Princeton, New Jersey 08544, USA State University of New York, Buffalo, New York 14260, USA Columbia University, New York, New York 10027, USA University of Rochester, Rochester, New York 14627, USA State University of New York, Stony Brook, New York 11794, USA Brookhaven National Laboratory, Upton, New York 11973, USA Langston University, Langston, Oklahoma 73050, USA University of Oklahoma, Norman, Oklahoma 73019, USA Oklahoma State University, Stillwater, Oklahoma 74078, USA Brown University, Providence, Rhode Island 02912, USA University of Texas, Arlington, Texas 76019, USA Southern Methodist University, Dallas, Texas 75275, USA Rice University, Houston, Texas 77005, USA University of Virginia, Charlottesville, Virginia 22901, USA and University of Washington, Seattle, Washington 98195, USA (Dated: January 6, 2009)We report the results of a search for associated production of charginos and neutralinos using adata set corresponding to an integrated luminosity of 2.3 fb − collected with the D0 experimentduring Run II of the Tevatron proton-antiproton collider. Final states containing three charged lep-tons and missing transverse energy are probed for a signal from supersymmetry with four dedicatedtrilepton event selections. No evidence for a signal is observed, and we set limits on the product ofproduction cross section and leptonic branching fraction. Within minimal supergravity, these limitstranslate into bounds on m and m / that are well beyond existing limits. PACS numbers: 14.80.Ly, 13.85.Rm, 12.60.Jv
Supersymmetry (SUSY) [1] is one of the most popularextensions of the standard model (SM). SUSY can solvethe hierarchy problem, allows the unification of gaugecouplings, and provides a dark matter candidate. Theanalyses presented in this Letter are based on the su-persymmetric extension of the SM with minimal fieldcontent, the so-called minimal supersymmetric standardmodel (MSSM), which requires the addition of a SUSYpartner for each SM particle, differing by half a unit inspin. The supersymmetric partners of charged and neu-tral Higgs and gauge bosons form two chargino ( ˜ χ ± ) andfour neutralino ( ˜ χ ) mass eigenstates. Experiments atthe CERN e + e − Collider (LEP) have set lower limits onthe masses of SUSY particles. In particular, charginoswith mass lower than 103.5 GeV and sleptons (˜ ℓ ) withmass below 95 GeV are excluded [2]. The results pre-sented here are the extensions of an earlier search forcharginos and neutralinos by the D0 collaboration basedon 0.3 fb − of data [3]. The CDF collaboration has pub-lished limits for charginos and neutralinos using 2.0 fb − of data [4].In p ¯ p collisions, charginos and neutralinos can be pro-duced in pairs via an off-shell W boson or the exchangeof squarks. They decay into fermions and the lightestneutralino ˜ χ , which is assumed to be the lightest super-symmetric particle (LSP) and to escape undetected. ThisLetter describes the search for p ¯ p → ˜ χ ± ˜ χ in purely lep-tonic decay modes in final states with missing transverseenergy E T and three charged leptons ( e, µ or τ ). Thissignature of three leptons can be particularly challeng-ing in regions of parameter space where lepton momentaare very soft due to small mass differences of the SUSYparticles. The analyses are based on p ¯ p collision dataat a center-of-mass energy of 1.96 TeV recorded withthe D0 detector at the Fermilab Tevatron Collider be-tween March 2002 and June 2007 corresponding to anintegrated luminosity of 2.3 fb − , with the exception ofthe analysis using identified hadronic τ lepton decays,which is based on 1 fb − of data.The D0 detector [5] consists of a central tracking sys-tem surrounded by a liquid-argon sampling calorimeterand a muon system. The inner tracking systems, a sili-con microstrip tracker and a central fiber tracker, residein an axial magnetic field of 2 T. The η coverage of thecalorimeter extends down to pseudorapidities of | η | ≈ η = − ln [tan( θ/ θ is the polar angle withrespect to the proton beam direction. Muons are identi-fied in the inner tracking system as well as in the outermuon system, which consists of three layers of trackingdetectors and scintillator counters. An iron toroidal mag-net providing a field of 1.8 T is located between the twoinnermost layers. The muon system provides coveragefor muon identification up to | η | ≈
2. A three-stage real-time trigger system reduces the total rate from 2.5 MHzto about 100 Hz. Events for the offline analyses are col-lected by a combination of single lepton, di-lepton, and lepton plus track triggers. Electrons and muons are se-lected by their specific energy deposition in the calorime-ter and hits in the muon chambers, respectively. In ad-dition, high momentum tracks matched to the objectsin the calorimeter and muon system help to reduce thetrigger rates.Standard model and SUSY processes are simulatedwith the event generators pythia [6] (Drell-Yan, di-boson, Υ, and t ¯ t events) and alpgen [7] ( W +jet/ γ events). The simulation of the detector geometry andresponse is based on geant [8]. Detector noise and ad-ditional interactions are included using randomly trig-gered events recorded throughout the duration of thedata-taking period. The predictions for the SM back-grounds are normalized using the next-to-leading (NLO)and, for Drell-Yan production, next-to-NLO theoreticalcross sections, calculated using CTEQ6.1M parton dis-tribution functions [9].The contributions from multijet background are esti-mated using D0 data. For each analysis, samples domi-nated by multijet background are defined that are identi-cal to the search samples except for reversed lepton iden-tification requirements. In case of the electrons, jet-likeelectrons are selected based on the likelihood criterion(see below) while for the muons the isolation criteria (seebelow) are inverted. The normalization of these samplesis performed at an early stage of the selection in a regionof phase space that is dominated by multijet production.The optimization of the analysis is done using mini-mal supergravity (mSUGRA) [10] as a reference model,in regions of parameter space with chargino, neutralino,and slepton masses ranging from 100 to 200 GeV. ThemSUGRA scenario can be described by five independentparameters: the unified scalar and gaugino masses m and m / , the ratio of the vacuum expectation values ofthe two Higgs doublets, tan β , the unified trilinear cou-pling A , and the sign of the Higgs mass parameter µ .The SUSY spectra are calculated using softsusy [11].The selection criteria are optimized to achieve the bestaverage expected limit under the assumption that no sig-nal is present in the data. A modified frequentist ap-proach [12] is used to calculate limits at the 95% C.L.for each different final state and selection. Two choicesof mSUGRA parameters ( m = 150 GeV and m / =250 (170) GeV, with tan β = 3, A = 0 and µ >
0) areused as a reference for a high- p T (low- p T ) signal, labeledSUSY1 (SUSY2) in the plots shown in the following.The reconstruction of isolated electrons exploits theircharacteristic energy deposition in the calorimeter. Allelectromagnetic clusters with | η | < . | η | < .
0. Isolation criteria are imposed inboth the tracker and the calorimeter in order to suppressbackground contributions from jets. Two different typeof muons, referred to as “loose” and “tight”, are used inthe analyses. The classification of loose and tight muonsdepends on the level of calorimeter and tracker isolationof the candidate. The isolation in the calorimeter is basedon the cell energies in a hollow cone of 0 . < ∆ R < . R = p (∆ η ) + (∆ φ ) . The tracker isolation isdefined as the scalar sum of the transverse momenta ofall tracks in a cone of ∆ R < . e and µ are measured using Z → ℓℓ events, and the efficienciesin the Monte Carlo (MC) simulation are corrected forknown differences according to the measurements in thedata.The reconstruction of hadronically decaying τ lep-tons is seeded by calorimeter clusters or tracks [13] with | η | < .
5. According to their signature in the detec-tor, they are classified into three types. The signatureof τ -type 1 ( τ -type 2) consists of a single track with en-ergy deposit in the hadronic (and the electromagnetic)calorimeter typically arising from π ± -like ( ρ ± -like) de-cays. Three-prong decays ( τ -type 3) are not consideredhere, since the background contribution from jets in thischannel does not allow one to improve the sensitivity toa signal. The separation of hadronic τ leptons and jets isbased on a set of neural networks (NN), one for each τ -type, exploiting the differences in longitudinal and trans-verse shower shapes as well as differences in the isolationin the calorimeter and the tracker [13]. Z → τ τ MCevents are used as the signal training sample for the neu-ral networks, while multijet events from data serve as thebackground training sample. In order to ensure high effi-ciency for low τ lepton transverse momenta, the selectionon the NN output varies depending on the transverse mo-menta of the τ candidates to keep a constant efficiency of60%. At a small rate, muons can be misidentified as one-prong hadronic τ lepton decays, and thus τ candidatesto which a muon can be matched are rejected.Jets are reconstructed with an iterative midpoint conealgorithm [14] with cone radius of 0.5 and must be within | η | < .
5. The E T is calculated from the vector sum ofthe transverse components of the energy deposited in thecalorimeter cells and is corrected for electron, τ and jetenergy calibrations as well as the transverse momentumof muons.In the following, four different channels are defined,distinguished by the lepton content of the final state.For the di-electron plus lepton channel ( eeℓ ) two identi-fied electrons are required using the electron identifica-tion criteria described above. In the di-muon plus lep- ton channel ( µµℓ ), one tight and one loose muon are re-quired, while the selection in the electron, muon plus lep-ton channel ( eµℓ ) starts from one electron and one tightmuon. Finally, the muon, τ lepton plus lepton channel( µτ ) requires one tight muon and one hadronically de-caying τ lepton in the final state. In all cases, unlessexplicitly specified otherwise, the third lepton is recon-structed as an isolated track without using the standardlepton identification criteria.For each of the eeℓ , µµℓ and eµℓ channels, one “low- p T ” and one “high- p T ” selection is designed to exploitthe different kinematic properties for various parameterpoints in the m – m / plane. The µτ channel is sepa-rated into two distinct selections based on the propertiesof the third object. One selection requires only an iso-lated track as third object, as in the other three analyses( µτ ℓ selection). For the second selection, a fully recon-structed hadronic τ lepton is required ( µτ τ selection).Both µτ selections are identical over the whole m – m / plane.Each selection requires two identified leptons stemmingfrom the primary vertex with minimum transverse mo-menta of p ℓ T = 12 GeV and p ℓ T = 8 GeV. Due to higherthresholds in the single muon triggers used for the µτ channel, the p T cut on the muon is tightened to 15 GeVfor this channel. If more than two leptons are identifiedthat satisfy the p T criteria, the two leptons with the high-est p T are considered. In case of the eµℓ analysis, eventsare removed if two electrons or muons with an invari-ant mass compatible with that of the Z boson mass arefound. This is called the preselection. To further reducethe background, differences in the kinematics and eventtopology compared to signal are exploited. All selectioncriteria are summarized in Tables I and II.The dominant background from Drell-Yan and Z bo-son production in the µµℓ and eeℓ channels as well asmultijet background can be reduced by selecting on theinvariant mass m ℓ ℓ of the identified di-lepton systemand the opening angle ∆ φ ℓ ℓ of the same two leptons inthe transverse plane. As shown in Fig. 1, a major fractionof the di-lepton events from Z boson decays can be re-jected by requiring the invariant mass m ℓ ℓ to be belowthe Z resonance. A substantial fraction of the Drell-Yanevents as well as the major part of events from multijetproduction are back-to-back in the transverse plane andcan be rejected by removing events with large openingangle ∆ φ ℓ ℓ .Another striking feature of the signal is the presence oflarge E T due to the escaping neutralinos and neutrinosin the final state. Thus selecting events with large E T is expected to further enhance the signal, which is illus-trated in Fig. 2. However, backgrounds without true E T can potentially satisfy this selection criterion, because ofmismeasurements of the objects in the event or by failingto reconstruct them. If E T is caused by mismeasurementof an object, the direction of the E T tends to be aligned (GeV) mm m E ve n t s / . G e V -2
10 1 (GeV) mm m E ve n t s / . G e V -2
10 1 Data *, Y g Z/Multijet g W+jet/WW,ZZWZData *, Y g Z/Multijet g W+jet/WW,ZZWZttSUSY 1SUSY 2 -1 DØ, 2.3 fbl selection mm FIG. 1: Invariant mass m µµ ( µµℓ channel) for data (points),SM backgrounds (shaded histograms), and SUSY signal (openhistograms) after cut I (see Table I) for the low- p T selection. (GeV) T E E ve n t s / G e V -2 -1 (GeV) T E E ve n t s / G e V -2 -1 Data * g Z/Multijet g W+jet/WW,ZZWZData * g Z/Multijet g W+jet/WW,ZZWZttSUSY 1SUSY 2 -1 DØ, 1 fbl selection tm FIG. 2: Missing transverse energy E T ( µτ ℓ selection) for data(points), SM backgrounds (shaded histograms), and SUSYsignal (open histograms) after cut I (see Table II). with this object. For events with at least one jet, Sig( E T )is defined asSig( E T ) = E T qP jets σ ( E jT ||6 E T ) , where σ ( E jT ||6 E T ) is the jet energy resolution pro-jected on the E T direction. As a result, Sig( E T )is expected to be small for events with poorly mea-sured jets. Rejecting events with small minimal trans-verse mass m min T = min( m ℓ T , m ℓ T ), where m ℓT = q p ℓT E T [1 − cos ∆ φ ( ℓ, E T )], removes events with mis- (GeV) minT m E ve n t s / G e V -1 (GeV) minT m E ve n t s / G e V -1 Data * g Z/Multijet g W+jet/WW,ZZWZData * g Z/Multijet g W+jet/WW,ZZWZttSUSY 1SUSY 2 -1 DØ, 2.3 fbl selection m e FIG. 3: Minimum transverse mass m min T ( eµℓ channel) fordata (points), SM backgrounds (shaded histograms), andSUSY signal (open histograms) before applying the cut on m min T (see Table I) for the low- p T selection. measured leptons as illustrated in Fig. 3. Other eventswith large jet activity, in particular t ¯ t production, can beremoved with a cut on H T , the scalar sum of the p T ofall jets with p T >
15 GeV.Unlike most SM backgrounds, signal events containthree charged leptons. This can be exploited to removemost of the remaining background, which is dominatedby W +jet production at this stage of the selection. The eeℓ , µµℓ , eµℓ , and µτ ℓ selections only require an addi-tional track that must be isolated in both the trackingsystem and the calorimeter as indication of this thirdlepton. Dropping the lepton identification criteria inthis case increases the signal efficiency and includes allthree lepton flavors in the selection. The distribution ofthe transverse momentum of this additional track is pre-sented in Fig. 4 after E T , Sig( E T ) and m min T cuts areapplied. Selection of tracks with high transverse momen-tum clearly enhances signal over background. For the µτ τ channel, a well-identified second τ lepton is requiredinstead of the track. Since the τ lepton selection imposesdifferent criteria than the track selection, some signal lossdue to the third track criterion can be regained using thisselection. In particular at high tan β , this selection is fa-vored, since most of the leptons in the final state areexpected to be τ leptons. Figure 5 shows the distribu-tion of the transverse momentum for the second τ leptoncandidate.After the third object selection, the remaining back-ground consists mainly of W and Z boson as well asdi-boson production. These backgrounds are addressedin the following. The remaining Z boson backgroundmainly consists of events where one of the leptons fromthe Z boson decay is not reconstructed in the calorime- (GeV) trT p E ve n t s / G e V -2 -1 (GeV) trT p E ve n t s / G e V -2 -1 Data * g Z/Multijet g W+jet/WW,ZZWZData * g Z/Multijet g W+jet/WW,ZZWZttSUSY 1SUSY 2 -1 DØ, 2.3 fbl selection m e FIG. 4: Transverse momentum of the track ( eµℓ channel)for data (points), SM backgrounds (shaded histograms), andSUSY signal (open histograms) after all E T related cuts areapplied (cut III, see Table I) for the low- p T selection. (GeV) t T p
10 20 30 40 50 E ve n t s / . G e V -2 -1 (GeV) t T p
10 20 30 40 50 E ve n t s / . G e V -2 -1 Data * g Z/Multijet g W+jet/WW,ZZWZData * g Z/Multijet g W+jet/WW,ZZWZttSUSY 1SUSY 2 -1 DØ, 1 fb selection ttm
FIG. 5: Transverse momentum of the second τ lepton can-didate ( µτ τ selection) for data (points), SM backgrounds(shaded histograms), and SUSY signal (open histograms) af-ter cut III (see Table II). ter or muon system, but instead a jet or photon frominitial or final state radiation is misidentified as one ofthe two initially selected leptons. However, the missedlepton from the Z boson decay is then selected as thethird track. This unique feature provides two handles toreject this background. Due to the non-reconstruction ofone of the leptons, the E T tends to point into the direc-tion of the track. Thus the transverse mass calculatedfrom the track and E T should be small due to the smallopening angle ∆ φ tr, E T . In addition, the invariant mass of the track and one of the leptons, m ℓ , ,tr , is expected tobe consistent with the Z boson mass. The same is truefor W Z production, where again one of the leptons fromthe Z decay is reconstructed in the tracking system.For W boson production, only one real lepton is ex-pected from the decay of the W boson, the second leptonis mimicked by a jet or a photon. In the case of jets, theidentification criteria for that lepton tend to be of worsequality, while in case of photon conversions, no hits in theinnermost layers of the tracking detector are expected forthe track corresponding to the converted photon. Thus,requiring high quality leptons (tight likelihood for elec-trons and very tight track isolation for muons) or hits inthe first two layers of the tracking system is expected toreduce W +jet/ γ background. To keep signal efficiencieshigh, these requirements are only used if the event prop-erties and kinematics are similar to expectations from W boson production (see Table I). In case of the µτ ℓ selec-tion, a dedicated likelihood discriminant is developed toremove the background from W boson production. Thislikelihood uses the transverse masses calculated for all ofthe three leptons as well as products of E T and leptontransverse momenta. In case of the µτ τ selection, theproduct of the two NN outputs for τ lepton identifica-tion is used to remove events containing misidentified τ candidates.Finally, the different event kinematics for signal andbackground are exploited to obtain better signal sensi-tivity. Since background is expected to have low trans-verse momentum for the third track or small E T , a cuton the product of track p T and E T effectively rejects anyremaining background contributions. In addition, thevectorial sum of the lepton transverse momenta and E T should equal the transverse momentum of the third trackin case of signal events. Thus the p T balance p bal T = | ~p ℓ T + ~p ℓ T + ~E T | p trT is expected to peak at 1 for a signal, while for backgrounda broad distribution is expected.After all selection criteria are applied, the expectedbackground is dominated by irreducible background from W Z production, as is evident from the marginal distribu-tion of the di-electron invariant mass in the eeℓ selectionshown in Fig. 6. A detailed comparison of background ex-pectation and events observed in data together with effi-ciency expectations from a typical SUSY signal are shownin Tables III and IV for the low- p T and high- p T selection,respectively, while Table V presents the results for the µτ selections. In general, good agreement between dataand expectation from SM processes is observed. Combin-ing all low- p T and µτ selections, a background of 5 . ± . ± . (GeV) ee m E ve n t s / G e V -2 -1 (GeV) ee m E ve n t s / G e V -2 -1 Data *, Y g Z/Multijet g W+jet/WW,ZZWZData *, Y g Z/Multijet g W+jet/WW,ZZWZttSUSY 1SUSY 2 -1 DØ, 2.3 fbeel selection
FIG. 6: Distribution of the invariant mass m ee ( eeℓ channel)for data (points), SM backgrounds (shaded histograms), andSUSY signal (open histograms) with all cuts applied exceptthe m ee requirement for the low- p T selection. background is 10%. The expectation for the referencesignal point SUSY2 is 9 . ± . ± . p T selection yields 3 . ± . ± . . ± . ± . τ energy cal-ibration in signal (2%–6%) and background events (2%–9%), PDF uncertainties (3%–4%), and modeling of themultijet background (2%–30%). All uncertainties, exceptthe last one, are correlated among the different channels.No evidence for a signal is observed. The search re-sults can be translated into upper limits on the productof cross section and branching fraction into three chargedleptons, σ × BR(3 ℓ ). Limits are based on the combina-tion of all low- and high- p T selections. Events appearingin multiple analyses are uniquely assigned to the chan-nel with the best signal to background ratio. Correlatedsystematic uncertainties are taken into account.To calculate the limits, the mass relations between theparticles involved in the decay chain of chargino and neu-tralino have to be known. The mSUGRA model is usedto calculate the mass differences between ˜ χ ± , ˜ χ , and˜ χ , which approximately corresponds to the assumption m ˜ χ ± ≈ m ˜ χ ≈ m ˜ χ . For slepton and sneutrino masses,several scenarios are taken into account.Figure 7 shows the limit on σ × BR(3 ℓ ) as a function ofchargino mass assuming that sleptons and sneutrinos areheavier than the lightest chargino and the second-lightest Chargino Mass (GeV)
100 110 120 130 140 150 160 BR ( l ) ( pb ) · ) c~ –c~ ( s ) c~ )>M(l~); M( c~ » ) c~ M( » ) – c~ M( >0, no slepton mixing m =3, b tan -1 DØ, 2.3 fbLEP l - m a x l a r ge - m Observed LimitExpected Limit
Chargino Mass (GeV)
100 110 120 130 140 150 160 BR ( l ) ( pb ) · ) c~ –c~ ( s FIG. 7: Upper limit at the 95% C.L. on σ × BR(3 ℓ ) as afunction of ˜ χ ± mass, in comparison with the expectationfor two SUSY scenarios (see text). PDF and renormaliza-tion/factorization scale uncertainties on the predicted crosssection are shown as shaded bands. neutralino, and assuming that slepton mixing can be ne-glected. In this case, both ˜ χ ± and ˜ χ decay via three-body decays, and branching fractions do not depend onthe lepton flavor. The limit is compared with the NLOcross section [16] multiplied by branching fractions calcu-lated in the limit of heavy sleptons (“large- m ” scenario)and for slepton masses just above the mass of the ˜ χ , inwhich case the leptonic branching fraction for three-bodydecays is maximized (“3l-max” scenario). For the latter,an observed (expected) lower limit at the 95% C.L. onthe chargino mass is set at 138 GeV (148 GeV).Alternatively, the results can be interpreted withinmSUGRA. To obtain the efficiency for any given point inthe m – m / plane, selection efficiencies are first deter-mined separately for three-body decays of chargino andneutralino as well as two-body decays via sleptons andsneutrinos. The variation of these efficiencies throughoutthe plane can then be parametrized for each selection asa function of the chargino, slepton and sneutrino masses.Using the mSUGRA prediction of branching fractionsand masses [6] [11] [17], the parametrized efficiencies areused to calculate the total efficiency for each point in the m – m / plane. Figure 8 shows the region excluded inthe m – m / plane for tan β = 3, A = 0 and µ > χ mass, one of the leptons from the ˜ χ decayhas very small momentum, rendering the trilepton selec-tions inefficient. For sneutrinos lighter than the ˜ χ ± and˜ χ , two-body decays into sneutrinos open up, leading toa smaller branching fraction into three charged leptons TABLE I: Selection criteria for the µµℓ , eeℓ and eµℓ analyses (all energies, masses and momenta in GeV, angles in radians) forthe low- p T selection and high- p T selection, see text for further details.Selection µµℓ eeℓ eµℓ low p T high p T low p T high p T low p T high p T I p ℓ T , p ℓ T > > > > > > > > > > a > > m ℓ ℓ b ∈ [20 , ∈ [0 , ∈ [18 , ∈ [0 ,
75] – –II ∆ φ ℓ ℓ < < < < E T > > > > > > E T ) > > > > > > m min T > > > > > > H T – <
80 – – – –IV p trT > > > > > > m trT > > > > > > m ℓ , ,tr / ∈ [80 , < < W – – tight likelihood c – tight likelihood d hit in 2 inner layers d very tight muon isolation e P . < ∆ R < . p track T < E T × p trT > > >
220 – – –VII p bal T < < < < < < a p ℓ T and p ℓ T are electron and muon p T , respectively. b ℓ refers to the two identified leptons c for p trT <
15 GeV d for m µT ∈ [40 ,
90] GeV e for m eT ∈ [40 ,
90] GeV
TABLE II: Criteria for the µτ ℓ and µτ τ selections (all en-ergies, masses and momenta in GeV, angles in radians), seetext for further details.Selection µτ ℓ µτ τ I p ℓ T , p ℓ T > > a II ∆ φ ℓ ℓ < E T > E T ) > m µT > H T < p trT > p τ T > φ tr, E T > φ τ , E T > m ℓ , ,tr < < W likelihood likelihoodVI NN τ × NN τ > E T × p trT > p bal T < a p ℓ T and p ℓ T are muon and τ lepton p T , respectively. as well as a reduced selection efficiency due to the smallmass difference between sneutrino and chargino. For theintermediate region at m / ≈
245 GeV, chargino decaysvia W bosons compete with decays via sleptons, lead-ing to a reduction in leptonic branching fraction withincreasing m / both below and above the threshold for (GeV) m ( G e V ) / m (GeV) m ( G e V ) / m DØ observed limitDØ expected limitCDF observed) -1 limit (2.0 fb LEP Chargino LimitLEPSleptonLimit -1 DØ, 2.3 fb mSUGRA > 0 m = 0, = 3, A b tan c~ – c~ Search for ) c~ M ( » ) l ~ M ( ) – c~ M ( » ) n~ M ( (GeV) m ( G e V ) / m FIG. 8: Region in the m – m / plane excluded by the com-bination of the D0 analyses (green), by LEP searches forcharginos (light grey) and sleptons (dark grey) [2] and CDF(black line) [4]. The assumed mSUGRA parameters aretan β = 3, A = 0 and µ > production of a real W boson.The excluded region in the m – m / plane depends onthe choice of tan β , as the branching fraction into τ lep-tons increases as a function of tan β . Figure 9 shows thelimit on σ × BR(3 ℓ ) as a function of tan β for a charginomass of 130 GeV and fixing m such that the lightest stau0 TABLE III: Numbers of events observed in data and expected for background and reference signal efficiency (SUSY2, see text)in percent at various stages of the selection with statistical uncertainties for the low- p T selection. Each row corresponds to agroup of cuts, as detailed in Table I.Selection µµℓ eeℓ eµℓ Data Backgrd. Eff. (%) Data Backgrd. Eff. (%) Data Backgrd. Eff. (%)I 194006 195557 ±
177 19.9 ± ±
202 15.5 ± ±
75 10.5 ± ±
88 14.6 ± ±
64 11.0 ± ± ± ±
12 6.8 ± ±
20 5.8 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± p T selection. Each row corresponds to agroup of cuts, as detailed in Table I.Selection µµℓ eeℓ eµℓ Data Backgrd. Eff. (%) Data Backgrd. Eff. (%) Data Backgrd. Eff. (%)I 140417 141781 ±
120 19.6 ± ±
175 18.1 ± ±
23 11.5 ± ±
51 15.3 ± ±
39 12.8 ± ± ± ±
10 10.8 ± ±
11 8.9 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± b tan BR ( l ) ( pb ) · ) c~ –c~ ( s m S U G R A ) = 1 GeV c~ ) - M( t~ )= 130 GeV; M( – c~ M( -1 DØ, 2.3 fb
Observed LimitExpected Limit b tan BR ( l ) ( pb ) · ) c~ –c~ ( s FIG. 9: Upper limit at the 95% C.L. on σ × BR(3 ℓ ) as a func-tion of tan β in comparison with the prediction for a charginomass of 130 GeV and m ˜ τ − m ˜ χ = 1 GeV. ( ˜ τ ) is heavier than the ˜ χ by 1 GeV. The latter choice re-sults in three-body decays with maximal leptonic branch-ing fraction. The leptonic branching fraction into three τ leptons increases as a function of tan β , reaching val-ues above 50% for tan β >
15. Because all selectionshave been designed to be efficient for τ leptons, the limitremains stable within a factor of two for tan β .
10, al-lowing one to exclude charginos with a mass of 130 GeVup to tan β of 9.6. To summarize, a data set collected with the D0 detec-tor corresponding to an integrated luminosity of 2.3 fb − has been analyzed in search of the associated productionof charginos and neutralinos in final states with threecharged leptons and E T . No evidence for a signal isobserved, and upper limits on the product of produc-tion cross section and leptonic branching fraction havebeen set. Within the reference model of mSUGRA withtan β = 3, A = 0, and µ >
0, this result translates intoexcluded regions in the m – m / plane that significantlyextend beyond all existing limits from direct searches forsupersymmetric particles.We thank the staffs at Fermilab and collaboratinginstitutions, and acknowledge support from the DOEand 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 (UnitedKingdom); MSMT and GACR (Czech Republic); CRCProgram, CFI, NSERC and WestGrid Project (Canada);BMBF and DFG (Germany); SFI (Ireland); The SwedishResearch Council (Sweden); CAS and CNSF (China);and the Alexander von Humboldt Foundation (Ger-many).1 TABLE V: Numbers of events observed in data and expected for background and reference signal efficiency (SUSY2 for the µτ ℓ selection and SUSY1 for the µτ τ selection, see text) in percent at various stages of the selection with statistical uncertaintiesfor the µτ selections. Each row corresponds to a group of cuts, as detailed in Table II.Selection µτ ℓ µτ τ Data Backgrd. Eff. (%) Data Backgrd. Eff. (%)I 6251 6238 ±
30 8.1 ± ±
30 12.4 ± ±
17 6.9 ± ±
17 10.8 ± ±
14 4.5 ± ±
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