1. Current Analysis Activity/Results (Only brief overview) Sunil Bansal (Panjab University, Chandigarh) Approved results marked

2. 1) Responsible for taking care of Data Quality Monitoring code for UE analysis. This code is in CVS and included in standard reconstruction sequence. DQM/Physics/src/QcdUeDQM.cc 2) Participating very actively in UE analysis for LHC runs @ 900 GeV to 7 TeV; Main responsibility is track validation, event and determination of track selection efficiencies and optimization. Approved for ICHEP!! Some plots in next slides PAS-010-010: CMS AN-2010/112 -- The underlying event in proton - proton collisions at 7 TeV PAS-010-001: CMS AN-2010/018 -- The underlying event in proton - proton collisions at 900 GeV 3) Activity in JetMET group: Code maintenance and improvement for Offline JetMET HLT Determination of Jet related trigger efficiencies. Underlying Event Analysis

3. Data and MC samples, Events/Tracks Selection Vertex Selection:  Exactly one vertex  vtx != bs  |z(vtx) – z(bs)| < 10 cm  ndof > 4 Track Selection:  pT > 0.5 GeV, || < 2.0  d xy /σ dxy, d dz /σ dz < 3  σ/pt < 5%  high quality tracks Data: /MinimumBias/Commissioning10-May6thPDSkim_GOODCOLL-v1/RAW-RECO (using JSON file for good LS and run selection) MC: /MinBias_TuneD6T_7TeV-pythia6/Spring10-START3X_V26B-v1/GEN-SIM-RECO /MinBias_TuneP0_7TeV-pythia6/Spring10-START3X_V26B-v1/GEN-SIM-RECO /MinBias_7TeV-pythia8/Spring10-START3X_V26B-v1/GEN-SIM-RECO /MinBias_TuneCW_7TeV-pythia6/Summer10-START36_V10-v1/GEN-SIM- RECODEBUG 1/30/20163Sunil Bansal  dz = sqrt((  dz track) 2 + (  dz vertex) 2 )  dxy = sqrt((  dxy track) 2 + (  dxy vertex) 2 )

4. PAS:010-010 Event Selection Efficiency Good agreement between data and MC (within few %) Cut “ndof > 4” show different efficiency for data and MC Systematic because of this is ~2%. Cut on leading track jet also give different efficiency for data and MC. This is because of different pT and multiplicity spectrum in data and MC. (MC tuning is required)

5. Track Selection Efficiency PAS:010-010 Good agreement between data and MC (within few %) Cut on track pT give different efficiency for data and MC. This is because of different pT and multiplicity Spectrum in data and MC. (MC tuning is required) Events with leading track jet pT > 3 GeV, |eta| < 2.0

6. Charged Particle Density PAS:010-010 Large discrepancy between data and MC. Data is described better by MC ( with tunes, Like CW, DW) after asking for a hard scale in the event (track jet pT > 20 GeV) Same observation as during 900 GeV analysis

7. pT sum density vs azimuth No tune describes data well, agreement improves after requiring hard scale in the event

8. Activity in JetMET group 1)Responsible (with Shabnam Jabeen) for taking care Offline DQM code of HLT triggers for Jet and MET. This code is in CVS and included in standard reconstruction sequence and output can be seen in Offline GUI. DQMOffline/Trigger/src/JetMETHLTOfflineSource.cc This code include the analysis of L1, HLT and reco objects. All possible plots (always chances to improve further) in place to debug the problem in HLT (if it is there). This code also includes the function to calculate the Jet and MET trigger efficiency using 3 independent methods. 2)Studying in detail the performance of Jet triggers. Plots are approved for ICHEP!! See in next slides.

9. Data samples & Selections Data: /MinimumBias/Commissioning10-GOODCOLL-May27thSkim_v5/RAW-RECO Using JSON file: Cert_132440136297_7TeV_StreamExpress_Collisions10_JSON.txt Run 135149, 135175 (”tower scheme 6”) L ~ 1.7 nb -1 MC: /QCD_Pt-15_7TeV-pythia6/Spring10-START3X_V26B-v1/GEN-SIM-RECO TPG Skim: Atleast two jets with eT > 4 GeV and |eta| < 2 Atleast one jet within |eta| < 1 Jet ID: e.m.f > 0.01 n90Hits > 1 fHPD < 0.98 http://indico.cern.ch/conferenceDisplay.py?confId=81393 Many plots approved by collaboration

10. Efficiency estimations  Select unbiased event samples Many options available with data already collected: 1) Inclusive sample: no trigger requirement, skimming based on the jet pT with threshold lower than HLT threhold i.e. HLT_Jet15 -- 6 GeV HLT_Jet30 -- 15 GeV HLT_Jet50 -- 30 GeV 2) MinBias triggered sample: skimming based on HLT_MinBias_BSC 3)Muon triggered sample: skimming based on HLT_L1MuOpen  Take the selected sample, check how many them fire the trigger (under study) and leading jet (satisfying loose jet ID) have matching HLT object (dR < 0.1)

11. Comparison of efficiency estimated using different unbiased samples data Trigger efficiency estimated w.r.t. different samples are in good agreement for HLT_Jet15, HLT_Jet30 and HLT_Jet50. This statement holds for MC as well. Next plots are w.r.t. sample selected using Muon trigger (HLT_L1MuOpen)

12. Trigger efficiency in data

13. Data vs MC

15. Summary Active participation in data analysis and service work during last 7/8 months. Very happy to contribute towards ICHEP results from CMS, felt the pulse! Here presented brief overview of some of the contributions. Also working (with Kalanand Mishra @LPC) on the Jet Energy Correction using Z(ee) + 1 jet balance technique. Mainly concentrating in the evaluation of systematic effect and including the PF and JPT jets in the machinery (No slides here).