Substructure at CMS:

Transcription

1 Substructure at CMS: Experimental Perspective (SUNY Buffalo) Terajets 2013: Using Jet Substructure 1

2 Introduction Use one example analysis (Z tt all hadronic) to bring up some experimental discussion topics Data/MC scale factors Subjet energy scale Background estimation Overview of where CMS is headed - Substructure has taken over! High pt, high pileup - Snowmass studies Terajets 2013: Using Jet Substructure 2

3 Z tt all-hadronic First use of top tagging and W-tagging using jet substructure at CMS - JHEP09(2012)029 Top tag with CMS/JHU top tagger W tag with jet pruning Updated results Thursday! (Justin) Terajets 2013: Using Jet Substructure 3

4 CMS Top Tagger Based on JHU Top Tagger (Kaplan et al.) Cluster a jet using a sequential recombination algorithm ( default: CA R=0.8) Decluster in two stages in order to find up to 4 subjets A Jet B A` B` B`` A`` Subjets must satisfy two requirements - Momentum fraction criterion: p T subjet > 0.05 p T jet - Adjacency criterion: ΔR(C 1, C 2 ) > pt(c) Iterative process - throw out subjets that fail momentum fraction cut and try to decluster again - Jet cleaning is built in 4

5 CMS Top Tagger Tagging variables Generated top decay products: pairwise mass - Jet mass (m jet ) - Number of subjets (N sub ) - Minimum pairwise mass (m min ) of subjets Defined using the leading 3 subjets CMS PAS JME Probability Z` t t QCD Top Tagging Algorithm CMS Simulation s = 7 TeV Probability Z` t t QCD Top Tagging Algorithm CMS Simulation s = 7 TeV Probability Z` t t QCD Top Tagging Algorithm CMS Simulation s = 7 TeV (GeV/c ) m jet N subjets (GeV/c ) m min 5

6 Top mistag rate - 7 TeV Anti-tag and probe with signal like kinematics Jet masses are correlated - Can t anti-tag with jet mass Choose a signal like event topology (1+2) but reverse the substructure cuts (mass drop) Subtract standard model ttbar Probe Jet 3 Antitag Top mass Mistag probability = Number of top-tagged probe jets Number of probe jets Terajets 2013: Using Jet Substructure 6

7 Top mistag rate - 8 TeV Switch to 1+1 topology for better statistics at high pt Requirement: anti-tagged jet must have mass in the top mass window Anti-tag with minmass - minmass <30 Signal can contaminate this measurement - Account for this in the limit setting procedure Anti-tag Probe Mistag probability = Number of top-tagged probe jets Number of probe jets Terajets 2013: Using Jet Substructure 7

8 Data Driven Background Estimation Goal: measure the expected QCD multi-jet background from data Weight a sideband sample with the mistag probability Type Select dijet events, randomly select one jet and require a top tag Top Tag Type 1+1 bkgd estimation Probe - For each event, weight the 2-jet invariant mass distribution by the probability that the opposite jet is tagged Type Select trijet events, with one hemisphere type 2 tagged Probe Type 1+2 bkgd estimation Jet 3 W tag Top mass - For each event, weight the 3-jet invariant mass distribution by the probability that the opposite jet is tagged Sideband sample is biased! Probe jet may not have signal like mass. Correct this bias using modified mass procedure (next slide). 8

9 Data Driven Background Estimation Correct for bias The probe jets are kinematically different than signal jets Mass modified procedure - Artificially set the probe jet mass to a value randomly chosen from a QCD Monte Carlo distribution - The invariant mass is therefore modified: Check procedure with a closure test Assign a systematic uncertainty - Half the difference between corrected and uncorrected distributions 9

10 Semi-leptonic sample Semi-leptonic top pair events provide a very pure sample of boosted top and W jets - Require a muon with p T >40 and a high p T jet (p T >200) in the opposite hemisphere. The event must contain one b-tag. Provides a handle for measuring: - Top tagging and W tagging efficiency in data - Data/MC scale factors - Subjet energy scale Events / CMS, L = 5 fb at s = 7 TeV Data tt W+Jets Non-W MJ Subjet Mass Drop (µ = m 1 / m jet ) Terajets 2013: Using Jet Substructure 10

11 Tagging Efficiency Scale Factor Compare the efficiency of tagging cuts in data and Monte Carlo - Scale factor: S = ε data /ε MC Type 2 scale factor (S 2 ) based on μ cut (μ<0.4) and mass cut (60<m leading jet <130) - S 2 = S μ S mass Scale factor is applied twice per event in the MC - 7 TeV analysis: limited fully merged tops - use S 2 for 1+1 and

12 Tagging Efficiency Scale Factor Analyses using type 2 scale factor (S 2 ) but must extrapolate to higher p T Boosted top analyses - switch to using type 1 scale factor (S 1 ) - 8 TeV analysis has a sizable sample of merged tops Type 1 scale factor based on the 140<jet mass<250 and minmass>50 cuts: - S 11 = S minmass S mass 12

13 Subjet energy scale Fit two Gaussians to the W peak in the semi-leptonic sample SES Scale factor - measured W mass / predicted W mass ± 0.01 This measurement is influenced by the non-top backgrounds (single top starts to play a role at 8 TeV) and also by the non merged tops There are really two probabilities (how to separate?) : - Probability that a boosted W will be merged - Probability merged W will be tagged 13

14 Current substructure work With the 8 TeV dataset we now have a sizable sample of fully merged top quarks from the semi-leptonic selection Allows us to study new algorithms in data - Subjet b-tagging - Nsubjetiness, HEP Top Tagger, Qjets etc. Also study some parts of the JHU top tagger that were left out of the CMS tagger - Helicity cut, shrinking jets, groomed jet mass 14

15 Substructure at high p T Increased radiation - Result: find subjets from radiation instead of top decay products - Substructure variables become less efficient at high pt - Very high pt: Radiated tops and W s inside jets Very collimated - Detector segmentation limits our ability to resolve subjets from high p T tops CMS EXO Take advantage of ECAL granularity, track jets, particle flow - Small angle tracks - decreased track efficiency There are also CPU limitations CMS Jet Substructure Workshop - April 15,

16 Snowmass Studies Using preliminary Snowmass samples ( - TTbar 13TeV - 0 PU and 140 PU - Delphes CMS-like detector - Jets reconstructed from EFlow objects Towers, tracks and muons - Re-cluster jets with FastJet Cambridge Aachen Pileup 140 Pileup Prune jets then find subjets Jet p T Terajets 2013: Using Jet Substructure 16

17 Number of Jets Jet Mass at very high PU Select high p T leading jets (p T >300) W peak is visible in 0 PU TTbar jet mass distribution Peak washed out in 140 PU sample Pruning recovers the peak More studies ongoing - Suggestions? - Volunteers? PU - no grooming PU - no grooming 140 PU - pruned Terajets 2013: Using Jet Substructure Jet mass (GeV/c ) 17

18 Conclusion Substructure is an important tool used in many CMS analysis groups - Even more important at 14 TeV Use the shutdown period to test and optimize new algorithms Prepare for a very new environment (140 PU) Terajets 2013: Using Jet Substructure 18