Inclusive SUSY search strategies. SUSY-PAT All-hadronic SUSY search Inclusive leptonic SUSY search

Transcription

1 1 Inclusive SUSY search strategies Early analyses (Universität Hamburg) for the SUSY group SUSY-PAT All-hadronic SUSY search Inclusive leptonic SUSY search

2 Outline Introduction PAT Analysis Framework Trigger Studies QCD, tt, W, Z Extension to other, more specific final states QCD: ABCD - and Smearing -methods Z invisible: Using γ-, W and Z μμ templates tt: MET-template method, or MC- with lepton ID from data Backgrounds for the Inclusive Leptonic Search MET/MHT, HT, and Leptonic trigger paths Backgrounds for the All-hadronic Search Selectors, Cross-Cleaning, Example τ, b-tags, di-jet Conclusion Putting it all together 2

3 Introduction 1/2 3 SUSY cross section is dominated by squark and gluino pair-/associated production R-parity conservation Example diagram pair/associated SUSY production Stable LSP Cascade decay of primary produced SUSY particles missing ET, many jets, possibly leptons.

4 Introduction 2/2 PTDR2 plot, 4 reach for 10 TeV is reduced Reach vs luminosity Ratio parton luminosities 10 TeV/14TeV Sterling J.J.Sterling The inclusive searches have the best reach for SUSY With ~10 pb-1 reach can be beyond Tevatron limits If squark and gluino masses are below ~1 TeV SUSY can be discovered with ~1 fb-1

5 Intense amount of work 5 Starting in March: Dedicated SUSY workgroup meetings to Study the triggers Set up Analysis Framework Study data-driven background estimations 25 topical meetings, with more than 60 individual contributions in the past months Still a lot to do! More people are needed!

6 Outline Introduction PAT Analysis Framework Trigger Studies QCD, tt, W, Z Extension to other, more specific final states QCD: ABCD - and Smearing -methods Z invisible: Using γ-, W and Z μμ templates tt: MET-template method, or MC- with lepton ID from data Backgrounds for the Inclusive Leptonic Search MET/MHT, HT, and Leptonic trigger paths Backgrounds for the All-hadronic Search Selectors, Cross-Cleaning, Example τ, b-tags, di-jet Conclusion Putting it all together 6

7 SUSY PAT workflow 7

8 Central production of PAT Layer 1 8 All information collected on Available datasets: background samples (Gumbo, Chowder and Stew) *CMSSW_1_6_7-CSA07*PDJetMET_Skims1*susyHLTJetMET* *CMSSW_1_6_7-CSA07*PDElectron-Skim*susyHLTElectronPhoton* *CMSSW_1_6_7-CSA07*PDPhoton-Skim*susyHLTElectronPhoton* *CMSSW_1_6_7-CSA07*PDMuon-Skim*susyHLTMuon* standalone background sample *Znunu*CMSSW_1_6_7-CSA0* LM signal samples *LM*sftsdkpyt/CMSSW_1_6_7-* Plan: Publish data soon in DBS for access outside the CAF Need to run with crab Event content: Default PAT configuration, but: Loosen all acceptance cuts Super-cluster (e-jet cleaning) Generic tracks (lepton veto) weights

9 Cross-cleaning 1/2 Goal: implement event cleaning required by SUSY analyses, add and study at PAT-layer 2 reproduce SusyAnalyzer standards (F. Moortgat, L. Pape) mainly concentrating on cross-cleaning: remove/correct duplication across collections of Physics objects Implemented as a generic PatCrossCleaner takes all input collections (muons, electrons, photons, jets, taus) calls individual cleaners at the moment: electron/jets, muons/jets, photons/jets resolves conflicts (ignore duplication with removed object) produces cleaned and dropped collections Reference: 9

10 Cross-cleaning 2/2 10 Work in progress Cross-cleaning and Isolation algorithms are different in PAT and SusyAnalyzer Differences are expected and understood PAT electron-jet cross cleaning is validated w.r.t. SusyAnalyzer

11 Event Selectors 11 Goal: Provide a modular and re-usable system of selectors All selectors run in one go, return boolean results Information: can check individual, cumulative, n-1 Perl script to add new selector Example: Shell-output: (on LM1 signal) total number of events = 7000 selected = 833 (11.9%) Selection Presel MET Jets HT METJet l-veto eff cumulative n-1 52% 66% 41% 83% 73% 70% 52% 39% 23% 23% 16% 12% 17% 15% 19% 12% 16% 16% Selector Library

12 Analysis Skeleton Goal: provide a starting point for SUSY analysis Implementation: EDAnalyzer built on the EventSelector interface configuration file with all selectors and standard cuts examples on how to retrieve and handle event selector decisions Plotting example Status: Skeleton based on the all-hadronic inclusive analysis Documentation under SusyPat twiki Tried out by beta-testers, Answered how end user friendly this framework is: Pretty good! 12

13 Outline Introduction PAT Analysis Framework Trigger Studies QCD, tt, W, Z Extension to other, more specific final states QCD: ABCD - and Smearing -methods Z invisible: Using γ-, W and Z μμ templates tt: MET-template method, or MC- with lepton ID from data Backgrounds for the Inclusive Leptonic Search MET/MHT, HT, and Leptonic trigger paths Backgrounds for the All-hadronic Search Selectors, Cross-Cleaning, Example τ, b-tags, di-jet Conclusion Putting it all together 13

14 Trigger requirements High signal efficiency Redundant triggers for data-driven efficiency measurement Well calibrated for best performance Robust in the face of varied detector and beam conditions Triggers to collect control samples 14

15 Hadronic Triggers 1/2 Aim to have simple redundant trigger paths based on MET and HT Proposed 1032 trigger menu fulfills requirements but concern about robustness Study another path based on MHT Level 1 implementation of MHT agreed with the trigger group Studies with emulator very promising but depend on what corrections are used for L1 jets More studies necessary on thresholds and corrections 15

16 Hadronic Triggers 2/2 MHT trigger at HLT proposed Studies presented to the TSG Accepted with the request that the thresholds be tuned on latest samples 16 L1: 2.0 khz HLT: 3.2 Hz SUSY LM1 eff: 84% Reference: Talk by A. Bhatti, TSG, 14. May 2008 Started also to think about triggers for control samples for background studies Generally need to work on data-driven efficiency studies

17 Leptonic Triggers 17 Work so far concentrated on efficiencies for the signal processes Studies of efficiencies for muon and electron triggers Room for optimization Shows improved efficiency due to lower PT leptons trigger efficiency Also study using the hadronic triggers for leptonic signals Comparison: Leptonic Hadronic Trigger events with at least 2 isolated leptons with pt > 10 GeV

18 Outline Introduction PAT Analysis Framework Trigger Studies QCD, tt, W, Z Extension to other, more specific final states QCD: ABCD - and Smearing -methods Z invisible: Using γ-, W and Z μμ templates tt: MET-template method, or MC- with lepton ID from data Backgrounds for the Inclusive Leptonic Search MET/MHT, HT, and Leptonic trigger paths Backgrounds for the All-hadronic Search Selectors, Cross-Cleaning, Example τ, b-tags, di-jet Conclusion Putting it all together 18

19 QCD: ABCD -method (1/4) QCD background distribution signal region Extended method: Need not to be entirely uncorrelated! Determine the correlation of NB/NA w.r.t. one variable Fit this ratio in control-region Extrapolate to signal-region, and correct NC accordingly Extra 19

20 QCD: ABCD -method (2/4) 20 Correlation causes non-constant dependence of the ratio B / A A fit of this ratio in the control region is used to extrapolate to the signal region Signal contamination in the background regions influence the extrapolation. This effect leads generally to overestimation. Δφmin(MET, jets), MHT Hemispheres, MET All analysis cuts were applied, except on Δφmin, MHT, or Hemispheres & MET respectively.

21 QCD: ABCD -method (3/4) Inherent overestimation due to signal contamination in control region (Signal: LM1) Conservative for searches! Outlook: Study better separating variables, α? Δφmin(MET, jets), MHT Hemispheres, MET 21

22 QCD: ABCD -method (4/4) Robustness test (cut on deltar was not applied, here) 22

23 QCD: Smearing -method 1. From data events: jet 2 MET ν or σjet smearing pt pt MET f pt =1 function: pt MET 2 smearing function jet 1 Either from data or MC-truth (ν pt) Create new QCD sample Need high statistic of QCD events with low MET Smear jet energies, recalculate MET Normalize sample, e.g. using the ABCD method

24 Z invisible: methods 24 Z νν is an important irreducible background for the SUSY MET+jets search Methods: γ+jets: Production of high-et photons and W is very similar to the production of Z Theoretical uncertainties are expected to be under control (Reference: CMS PAS SUS ) W lν: The advantage is that more statistics are available Therefore the entire hadronic event selection can be applied, avoiding using MC predictions Z μμ: The advantage of this standard candle method is the robustness of the selection of leptons from Z

25 Z invisible: from γ+jets 25

26 Z invisible: from γ+jets 26 QCD background: Photon Isolation: Estimated using Photon Conversion Tag-&-Probe with electrons looking like photons plot: ratio of the conversion track sum pt to the supercluster ET tag electron: low pt, isolated and ID'd -> suppresses backgrounds probe electron: high pt but no isolation or ID applied Z mass window further suppresses backgrounds Electron Track Inefficiency: Tag-&-Probe on the Z resonance Use it to estimate γ-fakes analysis approved for ICHEP

27 Z invisible: from Z μμ Measure MET in the Z μμ+jets sample Select a muon data set (trigger efficiency to be studied, but high eff. expected) Apply the all-hadronic SUSY selection Scale dn/dmet to the Z νν + jets expectation Correct for the acceptance: factor of 1/AZ BR(Z νν) / BR(Z μμ): factor of RXS=5.95 To gain statistics, it might be necessary to loosen some cuts. Measure the MET spectrum in GeV region in 3-jet bin and extrapolate beyond 200 GeV. Use 1-jet and 2-jet bins as control regions to understand the extrapolation procedure. 27

28 Z invisible: from Z μμ Work in progress 28

29 ttbar background 29 The dominant ttbar-background channel to the all-hadronic search is the semi-leptonic decay channel, where the lepton is lost. Reasons for the failed Indirect Lepton Veto (ILV): τ

30 ttbar Method 1 30 Data-driven Method: 1. Apply SUSY selection, but revert lepton-veto MET template 2. Normalize MET template to data tt-background number of MET template at MET 200 GeV events at low MET bin, e.g GeV Works nearly perfect if - correct normalization window - no signal contamination MET [GeV]

31 ttbar Method 1 31

32 ttbar Method 2 32

33 ttbar Method 2 33 Separating SUSY Studied reconstructed top-mass and the total transverse mass (MT). Tough but promising! total transverse mass MT [GeV]

34 Outline Introduction PAT Analysis Framework Trigger Studies QCD, tt, W, Z Extension to other, more specific final states QCD: ABCD - and Smearing -methods Z invisible: Using γ-, W and Z μμ templates tt: MET-template method, or MC- with lepton ID from data Backgrounds for the Inclusive Leptonic Search MET/MHT, HT, and Leptonic trigger paths Backgrounds for the All-hadronic Search Selectors, Cross-Cleaning, Example τ, b-tags, di-jet Conclusion Putting it all together 34

35 Z estimation from W 1/2 Absolute shape likely to be wrong; but same for W and Z So use relative shape Z and W tagged events versus jet multiplicity: Filip Now enhance signal by introducing MET cut 35

36 Z estimation from W 2/2 36 Cut on MET > 200 GeV applied Jet-multiplicity for SM W- and Z- production is still similar W and Z normalized to first bin SM+ Work in progress (signal: LM4)

37 Global approach 1/2 37

38 Global approach 2/2 Work in progress 38

39 Outline Introduction PAT Analysis Framework Trigger Studies QCD, tt, W, Z Extension to other, more specific final states QCD: ABCD - and Smearing -methods Z invisible: Using γ-, W and Z μμ templates tt: MET-template method, or MC- with lepton ID from data Backgrounds for the Inclusive Leptonic Search MET/MHT, HT, and Leptonic trigger paths Backgrounds for the All-hadronic Search Selectors, Cross-Cleaning, Example τ, b-tags, di-jet Conclusion Putting it all together 39

40 Putting it all together: Hadronic Analysis 1. Perform the Analysis t a 40

41 Putting it all together: Hadronic Analysis 2. Estimate QCD t a 41

42 Putting it all together: Hadronic Analysis 3. Estimate Z invisible t a 42

43 Putting it all together: Hadronic Analysis Estimate ttbar / W t a MET [GeV]

44 Extension to b-final state 44 Basis: Standard jets + MET analysis Inclusive: counting of tagged b (search for squark decays) Peak search: study invariant mass of two b-tagged two tagged b-jets (pt > 30; η< 2.4) jets (eg. h0->bb decays) b-tagging algorithm Robust (track-counting) Secondary vertex algorithm (could work with early data) =7 Work in progress Optimised for signal significance of SUSY events over background with early data

45 Extension to τ-final state Reference: CMS-NOTE LM1 σ =55 pb M g =611 M q =559 g q q χ 02 q q 0 B χ ℓ ℓ = R 45 LM2 σ =7 pb M g =831 M q =780 g q q χ 02 q q B χ 02 τ 1 τ =96 Plans: Move to SUSY-PAT Adding particle flow to improve tau-id and signal + SM reconstruction and MET SM Explore control/signal regions to substract SM contributions from possible SUSYl Implement the control of W, Z and top background by direct reconstruction

46 Di-jet analysis PAT di-jet analysis No usage of MET di-jets ET>150 GeV alpha-variable α < 0.5 for QCD Randall, Tucker-Smith, arxiv: expected for 1fb-1: QCD: 12±6 (stat) evts LM1: 240 events Z invs: 41±8(stat) evts 46

47 Conclusion 47 Thanks to everybody who contributed! Many methods and studies have been developed and some done for the first time at CMS Topical work-group meetings have been useful: The SUSY signal and the SUSY background have been studied w.r.t. robustness & efficiency Data-driven background estimation methods: Significant process in last months! More can be done, i.e. compare orthogonal methods. These inclusive studies can be used as basis for more detailed and more specific searches SUSY-Workgroup meetings will continue, Contributions from everyone are welcome!

48 Backup 48

49 msugra plane: Reach & x-section 49

50 Search strategies Large variety of BSM-theories Large variety of Search strategies: this talk Signature SUSY Scenario All-hadronic msugra, AMSB, split-susy,... msugra, UED, AMSB, splitsusy, LSCP, RPV, little Higgs jets + 1 lepton... jets + 2 lepton msugra, AMSB, GMSB ττ GMSB, large tanβ γγ GMSB 50

51 QCD: ABCD -method (5/4) 51

52 Z invisible: from γ+jets 52 Electron Track Inefficiency: Tag-&-Probe on the Z resonance Use electron tracking inefficiency to Real electron/photon is estimated from μ's, but not substracted (conservative) estimate fake contribution to γ + jets MC Truth Measurement Linear fit (>30 GeV)

53 ttbar background 3/6 53

54 ttbar background 5/6 Normalization Deviation MET 54 ttbar estimation MET MET

55 All-hadronic analysis in PAT 55

56 ttbar in 1-lepton final state most tricky background: ttbar 1l final state: dominated by semileptonic ttbar 56