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Jieun Kim ( CMS Collaboration ) APCTP 2012 LHC Physics Workshop at Korea (Aug. 7-9, 2012). Search for SUSY in Events with Taus , Jets, and MET. Contents. Theoretical Motivation Search Strategy Event Selections Backgrounds Sensitivity for SUSY models Summary. SUSY Dark Matter.
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Jieun Kim ( CMS Collaboration ) APCTP 2012LHC Physics Workshop at Korea (Aug. 7-9, 2012) Search for SUSY in Events with Taus, Jets, and MET
Contents • Theoretical Motivation • Search Strategy • Event Selections • Backgrounds • Sensitivity for SUSY models • Summary
SUSY Dark Matter • Supersymmetrized Standard Model between Fermions and Bosons with unification of gauge couplings • Supergravity (mSUGRA or CMSSM) models, • the lightest neutralino is the stable LSP which escapes the detector • Cosmologically a natural dark matter (DM) candidate • ( stable neutralino ) • stau-neutralino co-annihilation processes may be sensitive to the amount of dark matter relic density observed by the Wilkinson Microwave Anisotropy Probe (WMAP)
SUSY Signature • SUSY signature at the LHC is involved with high multiplicity of energetic jets because squark and gluino pairs are dominant at the pp collisions, a large momentum imbalance in the detector (from LSP CDM candidate), and the Taus in the stau-neutralino co-annihilation region
SUSYSearch @ LHC Dark Matter Identity In large tan beta, Branch ratio to taus becoming dominant ~100%
pp@√s = 7TeV, 4.98 fb-1of data Particle Flow Jets clustered from identified particles reconstructed using all detector components with Anti-Kt (R=0.5) jet clustering algorithms • HT = scalar sum of Jet pT • MHT = negative vector sum of Jet pT
Tau lepton Reconstruction and Identification • Electromagnetic strips with ET>1 GeVfor neutral pions combined with PFJets to reconstruct the tau decay modes • Isolation: no charged hadrons with PT > 1.5 GeV/c or photons with ET > 2.0 GeV in Δ R < 0.3 • Muon ID efficiency 72.8%, tau ID efficiency 64.1% μ Pt = 23.1 GeV/c η = -1.31 Z → ττ→ μ + τh (one prong tau) τ Pt = 36.8 GeV/c η = 0.03 7
Event Selections MHT Baseline Selections: 2 Jets + MHT • ≥1 PFJet with pT > 30 GeV/c • 1st Leading Jet pT > 100 GeV/c and |η| < 3 • 2nd Leading Jet pT > 100 GeV/c and |η| < 3 • MHT > 250 GeV (with plateau “HLT_PFMHT150”) Tau Selections: 2τh • ≥ 2 τh’s with pT > 15 GeV/c and |η| < 2.1 • ≥ 2 τh’s passing the HPS ”tight” μ veto • ≥ 2 τh’s passing the HPS ”tight” e veto • ≥ 2 τh’s passing the HPS decay mode finding • ≥ 2 τh‘s passing the HPS ”very loose” isolation Topological Selections: • 1st Leading Jet separated from th’s (ΔR(j1, τh) > 0.3) • 2nd Leading Jet separated from th’s (ΔR(j2, τ) > 0.3) • ≥ 1 thth pair with ΔR(τh,1, τh,2) > 0.3 • Δφ(j2, MHT) > 0.5 pT(j1) pT(j2)
Background Estimation in data driven • Define control samples which are selected with most of the selections similar to those used in the main search but enriched with events from the background process • Measure selection efficiencies of jet->tau mistagrates in those control regions • Extrapolate to the region where we expect to observe our signal. • Estimate following equation for each background (ttbar, wjets, zjets, but except QCD) contribution Probability of(0,1,2) jets faking taus Correction factor
TTbar Two types of events in TTbar control region: • 1 real τh + 1 jet faking a τ • 2 jets faking 2 τ. • Aτ+j = fraction of t-tbar events with 1 real τh and 1 jet. • Aj+j= fraction of t-tbar events with 2 jets. • P(N) & P(M) are the probabilities to have N (M) jets that • can fake the τ in category (1) and (2). • f = “fake rate” • P(2b) = Probability of tagging 2-b-jets. • ετiso =Tau isolation efficiency. • C(N,n) = N choose n.
WJets Two types of events in W+Jets control region: • 1 real τh + 1 jet faking a τ. • 2 jets faking 2 taus. • Aτ+j = fraction of Wjet events with 1 real τh • and 1 jet faking τ • Aj+j= fraction of Wjet events with 2 jets faking τ’s • P(N) & P(M) are the probabilities to have N (M) jets • that can fake the τ in category (1) and (2) • f = “fake rate” • P(0b) = Probability of tagging zero jets as b-jets. • ετiso =Tau isolation efficiency. • C(N,n) = N choose n.
Invisible Z + Jets • Aμ= μ acceptance efficiency. • ɛμ = μ ID efficiency. • B(Z νν) = branching ratio for Z νν • B(Zμμ) = branching ratio for Z μμ • ɛTriggerMHT= efficiency of HLT_PFMHT150 (plateau) • εTriggerμτ = efficiency of μτ cross-trigger. • ɛMHT = efficiency of MHT (>250) • P(N) is the probability to have N jets that can fake • the τ in category (1) and (2). • f = “fake rate” • C(N,n) = N choose n.
Z->tau tau + Jets • Aμ= μ acceptance efficiency. • ɛμ = μ ID efficiency. • B(Z νν) = branching ratio for Z νν • B(Zμμ) = branching ratio for Z μμ • B(τ τh) = branching ratio for hadronicτ decay • ɛTriggerMHT= efficiency of HLT_PFMHT150 (plateau) • εTriggerμτ = efficiency of μτ cross-trigger. • ɛMHT = efficiency of MHT (>250) • P(N) & P(M) are the probabilities to have N (or M) jets that can fake τ • f = “fake rate” • C(N,n) = N choose n.
QCD multijets For QCD contribution, obtain a data-MC scale factor (SFQCD)
Sensitivity in SUSY models • Supergravity models (mSUGRA/CMSSM) • Simplified Model Scenarios (SMS) • Gauge Mediated Supersymmetry Breaking Models (GMSB)
CMSSM / mSUGRA • tanβ = 40, Ao= 500 GeV, μ > 0, Mtop = 173.8 GeV • Gaugino mass of < 495 GeV @95% C.L. • Gluino mass < 1.15 TeV @95% C.L.
CMSSM / mSUGRA • With Single Tau : • Better sensitivity in the case of very small ∆M (~5GeV) in the co-annihilation region, the low energy tau can’t be effectively detected and only the energetic tau from the decay of the neutralino can be observed
SMS Gluino mass < 775 GeV@95% C.L. for LSP mass up to 325 GeV
GMSB Gluino mass < 900 GeV @ 95% C.L.
Summary • SUSY (R-parity conserved) search results with up to ~5/fbof data, observed no significant excess. • SM background estimations done with data driven methods. • Setting the 95% exclusion limits on the constrained MSSM models, SUSY Simplified model, and GMSB. • Limits on Gluino mass reach to ~TeVwith the 2011 data of pp@√s = 7TeV