Download presentation
Presentation is loading. Please wait.
Published byLucas Cameron Modified over 8 years ago
1
Jieun Kim ( CMS Collaboration ) APCTP 2012 LHC Physics Workshop at Korea (Aug. 7-9, 2012) 1
2
Contents Theoretical Motivation Search Strategy Event Selections Backgrounds Sensitivity for SUSY models Summary 2
3
Supersymmetrized Standard Model between Fermions and Bosons with unification of gauge couplings SUSY Dark Matter Cosmologically a natural dark matter (DM) candidate ( stable neutralino ) ( stable neutralino ) 3 Supergravity (mSUGRA or CMSSM) models, the lightest neutralino is the stable LSP which escapes the detector the lightest neutralino is the stable LSP which escapes the detector stau-neutralino co-annihilation processes may be sensitive to the amount of dark matter relic density observed by the Wilkinson Microwave Anisotropy Probe (WMAP)
4
4 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 SUSY Signature
5
SUSY Search @ LHC Dark Matter Identity 5 In large tan beta, Branch ratio to taus becoming dominant ~100%
6
pp@√s = 7TeV, 4.98 fb -1 of data 6 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 p T MHT = negative vector sum of Jet p T
7
Tau lepton Reconstruction and Identification Electromagnetic strips with E T >1 GeV for neutral pions combined with PFJets to reconstruct the tau decay modes Isolation: no charged hadrons with P T > 1.5 GeV/c or photons with E T > 2.0 GeV in Δ R < 0.3 Muon ID efficiency 72.8%, tau ID efficiency 64.1% 7 7 Single Hadron + Zero Strips Single Hadron + One (two) Strip Single Hadron + Two Strips Three Hadrons ρ(770) Z → → + Z → τ τ → μ + τ h (one prong tau) μ Pt = 23.1 GeV/c η = -1.31 τ Pt = 36.8 GeV/c η = 0.03
8
Event Selections 8 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: 2τ h ≥ 2 τ h ’s with pT > 15 GeV/c and |η| < 2.1 ≥ 2 τ h ’s passing the HPS ”tight” μ veto ≥ 2 τ h ’s passing the HPS ”tight” e veto ≥ 2 τ h ’s passing the HPS decay mode finding ≥ 2 τ h ‘s passing the HPS ”very loose” isolation Topological Selections: 1st Leading Jet separated from th’s (ΔR(j 1, τ h ) > 0.3) 2nd Leading Jet separated from th’s (ΔR(j 2, τ) > 0.3) ≥ 1 t h t h pair with ΔR(τ h,1, τ h,2 ) > 0.3 Δφ(j 2, MHT) > 0.5
9
Backgrounds 9
10
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 mistag rates 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 10 Probability of (0,1,2) jets faking taus Correction factor
11
Background Control Samples 11
12
TTbar 12 Two types of events in TTbar control region: 1.1 real τ h + 1 jet faking a τ 2.2 jets faking 2 τ. A τ+j = fraction of t-tbar events with 1 real τ h and 1 jet. A j+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. ε τ iso =Tau isolation efficiency. C(N,n) = N choose n.
13
WJets 13 Two types of events in W+Jets control region: 1. 1 real τ h + 1 jet faking a τ. 2. 2 jets faking 2 taus. A τ+j = fraction of Wjet events with 1 real τ h and 1 jet faking τ A j+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. ε τ iso =Tau isolation efficiency. C(N,n) = N choose n.
14
Invisible Z + Jets 14 A μ = μ acceptance efficiency. ɛ μ = μ ID efficiency. B(Z νν) = branching ratio for Z νν B(Z μμ) = branching ratio for Z μμ ɛ Trigger MHT = efficiency of HLT_PFMHT150 (plateau) ε Trigger μτ = efficiency of μτ cross-trigger. ɛ MHT = 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.
15
15 A μ = μ acceptance efficiency. ɛ μ = μ ID efficiency. B(Z νν) = branching ratio for Z νν B(Z μμ) = branching ratio for Z μμ B(τ τ h ) = branching ratio for hadronic τ decay ɛ Trigger MHT = efficiency of HLT_PFMHT150 (plateau) ε Trigger μτ = efficiency of μτ cross-trigger. ɛ MHT = 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. Z->tau tau + Jets
16
QCD multijets 16 For QCD contribution, obtain a data-MC scale factor (SF QCD )
17
Search for New Physics 17
18
The Highest H T Event 18
19
19
20
Sensitivity in SUSY models Supergravity models (mSUGRA/CMSSM) Simplified Model Scenarios (SMS) Gauge Mediated Supersymmetry Breaking Models (GMSB) 20
21
tanβ = 40, A o = 500 GeV, μ > 0, M top = 173.8 GeV Gaugino mass of < 495 GeV @ 95% C.L. Gluino mass < 1.15 TeV @ 95% C.L. CMSSM / mSUGRA 21
22
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 eff ectively detected and only the energetic tau from the dec ay of the neutralino can be observed CMSSM / mSUGRA 22
23
SMS 23 Gluino mass < 775 GeV @ 95% C.L. for LSP mass up to 325 GeV
24
GMSB 24 Gluino mass < 900 GeV @ 95% C.L.
25
Summary SUSY (R-parity conserved) search results with up to ~5/fb of 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 ~TeV with the 2011 data of pp@√s = 7TeV 25
26
Systematic Uncertainty 26
27
27 The Highest H T Event
Similar presentations
© 2024 SlidePlayer.com. Inc.
All rights reserved.