Multijet Studies at CMS. Sunanda Banerjee Manjit Kaur Ruchi Gupta
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1 Multijet Studies at CMS Sunanda Banerjee Manjit Kaur Ruchi Gupta Thursday, June,
2 Motivation Multijet events have been studied in earlier experiments to validate important features of QCD. Various multijet studies in e + e - have determined spin of gluons and established non abelian nature of QCD. Similar studies at CDF and D have provided a good test of higher order perturbative QCD and finer understanding of QCD. At LHC energies, these can be studied for testing various Monte Carlo generators (Matrix Element Vs Parton Shower). Feasibility study was done using Monte Carlo at s= TeV. Thursday, June,
3 3-Jet variables: Variable definitions Invariant mass of 3-jet system Scaled energies: ordered in jet c.m. frame: 4-Jet variables: Scaled Energies: Bengtsson-Zerwas angle: Angle between planes containing the two leading jets and the two non leading jets Nachtmann-Reiter angle: Angle between the momentum vector difference of the two leading jets and the two non-leading jets: 3 Thursday, June, 3
4 TurnOn Curves ( data).8 HLT_Jet5U.8 HLT_Jet4U.6.4 Calo PF JPT.6.4 Calo PF JPT p (GeV) T p (GeV) T Obtained by dividing leading jet pt distributions of two consecutive triggers (HLT_Jet3U & HLT_Jet5U; HLT_JetU & HLT_4U) using the run-range in which both are unprescaled. Thursday, June, 4
5 Number of Good Primary Vertices (non-fake & ndof>4) > MET/SumE T <.3 Leading Jet p T > 4 GeV for HLT_Jet4U GeV for HLT_Jet5U Other Jets p T > 3GeV Leading Jet η <.5 Other Jets η < 3. Selection Criteria Select inclusive 3(4)-Jet samples Boost the leading (pt) 3(4)-Jets to their CM frame Order them according to their energies 5 Thursday, June, 5
6 Data/MC Comparison Data: runa & runb DecRereco MC: Winter Pythia6TuneZ, Pythia6TuneD6T & Herwig6 samples in various pt bins added according to cross-sections. Herwig++ sample with flat pt spectrum, each event added with weight. MadGraph & Alpgen samples combined with weights according to cross sections and matching efficiency. Thursday, June, 6
7 3Jet Mass pt> GeV HLT5 Herwig++ Pythia6TuneD6T Pythia6TuneZ Herwig6 MadGraph Alpgen Data Jet Mass Herwig++ Pythia6TuneD6T Pythia6TuneZ Herwig6 MadGraph Alpgen Data pt>4 GeV HLT Jet Mass Pythia D6T tune shows some difference wrt data for lower Jet pt threshold - the difference gets significantly reduced at higher pt threshold Thursday, June, 7
8 3Jets: x pt> GeV Herwig++ Pythia6TuneD6T Pythia6TuneZ Herwig6 MadGraph Alpgen Data HLT x 4 x Bump in Alpgen distribution due to low statistics ( events) HLT4 Herwig++ Pythia6TuneD6T Pythia6TuneZ Herwig6 MadGraph Alpgen Data pt>4 GeV and high weight in lowest pt bin Thursday, June, 8
9 4Jet Mass pt> GeV Herwig++ Pythia6TuneD6T Pythia6TuneZ Herwig6 MadGraph Alpgen Data HLT Jet Mass pt>4 GeV Herwig++ Pythia6TuneD6T Pythia6TuneZ Herwig6 MadGraph Alpgen Data HLT Jet Mass Difference among MC models for low pt threshold - greatly reduced for high pt threshold Thursday, June, 9
10 4Jets: x Herwig++ Pythia6TuneD6T Pythia6TuneZ Herwig6 MadGraph Alpgen Data HLT Herwig++ Pythia6TuneD6T Pythia6TuneZ Herwig6 MadGraph Alpgen Data HLT pt> GeV x pt>4 GeV x 3 Alpgen shows a bump in the distribution due to inadequate statistics and high weights. Thursday, June,
11 χbz Herwig++ Pythia6TuneD6T Pythia6TuneZ Herwig6 MadGraph Alpgen Data HLT5 pt> GeV BZ.8 Herwig++ Pythia6TuneD6T HLT4 pt>4 GeV Pythia6TuneZ Herwig6 MadGraph Alpgen Data BZ Bumps in Alpgen and Herwig6 distributions are observed due to inadequate statistics and high weights. Thursday, June,
12 Cos(θNR) Herwig++ Pythia6TuneD6T Pythia6TuneZ Herwig6 MadGraph Alpgen Data.7 Herwig++ Pythia6TuneD6T Pythia6TuneZ Herwig6.6 MadGraph Alpgen Data.5.4 HLT pt> GeV HLT cos( NR ) pt>4 GeV cos( NR ) Thursday, June,
13 TurnOn Curves (data ).8.6 Calo PF JPT HLT_Jet8.8.6 Calo PF JPT HLT_Jet (GeV) p T (GeV) p T Thresholds on pt of leading jet of GeV for HLT_Jet8 and 4 GeV for HLT_Jet9 are used. Above plots are obtained by dividing leading jet p T distributions from two consecutive triggers weighted according to their effective luminosities. Thursday, June, 3
14 LOffset vs LFastJet Effect of pile-up in has to be studied and LFastJet is to be used. LFastjet is validated against LOffset with data (DecRereco) Thursday, June, 4
15 3Jet Mass & x4 - - HLT5 Entries 4936 Mean RMS 9.6 Entries 4477 Mean RMS LOffset LFastjet HLT5 Entries 4936 Mean.78 RMS.3 Entries 4477 Mean.783 RMS.3-3 LOffset LFastjet Jet Mass x 4 LOffset/LFastJet HLT5 LOffset/LFastJet HLT Jet Mass x 4 No difference is observed between LOffset & LFastJet Thursday, June, 5
16 4jet Mass & x HLT5 Entries 6 Mean 66.5 RMS 6. Entries 596 Mean 65.8 RMS 6.5 LOffset LFastjet Entries 6 Mean.837 RMS.7 Entries 596 Mean.839 RMS.7 HLT LOffset LFastjet Jet Mass x 3 LOffset/LFastJet HLT5 LOffset/LFastJet HLT Jet Mass x 3 No difference is observed in LOffset & LFastJet Thursday, June, 6
17 Cos(θNR) & χbz Entries 6 Mean.556 RMS.98 Entries 596 Mean.556 RMS.98 HLT Entries 756 Mean.75 RMS.448 Entries 7889 Mean.74 RMS HLT LOffset.3.5 LOffset LFastjet..5 LFastjet cos( NR ) BZ LOffset/LFastJet HLT5 LOffset/LFastJet HLT cos( NR ) BZ No difference is observed in LOffset & LFastJet. LFastjet can Thursday, June, safely be used for and hopefully for also. 7
18 (DecRereco) Vs (PromptReco) Thursday, June, 8
19 Distribution of ngoodpv for and Entries Mean.5 RMS.48 Entries 974 Mean 4.47 RMS Data Data ngoodpv There will clearly be effects of increased pile up in data and we need to worry about this. Thursday, June, 9
20 HLT_Jet4U () vs HLT_Jet9 () Thursday, June,
21 3Jet Mass ngoodpv= ngoodpv=or ngoodpv> - - Entries 4387 Mean RMS 33.9 Entries 6484 Mean 88.6 RMS Entries 375 Mean 84.9 RMS 3.8 Entries 888 Mean RMS Entries 7348 Mean RMS 38.9 Entries 73 Mean RMS run:hlt4-4 run:hlt4-4 run:hlt4-4 run:hlt9 run:hlt9-5 run:hlt Jet Mass Jet Mass Jet Mass run/run.5 run:hlt4/run:hlt9 run/run.5 run:hlt4/run:hlt9 run/run.5 run:hlt4/run:hlt Jet Mass Jet Mass Jet Mass Distributions do not depend on number of good primary vertices and year of data taking. robust measurements can be made from the data. Thursday, June,
22 3Jet: x4 ngoodpv= ngoodpv=or ngoodpv> Entries 4387 Mean.7468 RMS. Entries 6484 Mean.7456 RMS.4.6 Entries 375 Mean.747 RMS..5.4 Entries 888 Mean.7484 RMS.5.6 Entries 7348 Mean RMS.9 Entries 73 Mean.755 RMS run:hlt4. run:hlt4. run:hlt4 run:hlt9. run:hlt9. run:hlt x x x 4 run/run.5 run:hlt4/run:hlt9 run/run.5 run:hlt4/run:hlt9 run/run.5 run:hlt4/run:hlt x x x 4 Thursday, June,
23 4Jet Mass ngoodpv= ngoodpv=or ngoodpv> - - Entries 676 Mean RMS 356. Entries 377 Mean 46 RMS Entries 7733 Mean 99.9 RMS Entries 455 Mean 36 RMS Entries 3386 Mean 99.9 RMS 35.7 Entries 983 Mean 34 RMS run:hlt4 run:hlt Jet Mass -4 run:hlt4 run:hlt Jet Mass -4 run:hlt4 run:hlt Jet Mass run/run.5 run:hlt4/run:hlt9 run/run.5 run:hlt4/run:hlt9 run/run.5 run:hlt4/run:hlt Jet Mass Jet Mass Jet Mass Distributions do not depend on number of good primary vertices and year of data taking. robust measurements can be made from the data. Thursday, June, 3
24 4Jet: x Entries 676 Mean.848 RMS.96 Entries 377 Mean.838 RMS.9656 ngoodpv= run:hlt4 run:hlt ngoodpv=or Entries 7733 Mean.844 RMS.97 Entries 455 Mean.847 RMS.94 run:hlt4 run:hlt9.9 Entries 3386 Mean RMS.93 Entries 983 Mean.849 RMS.994 run:hlt4 run:hlt9 ngoodpv> x x x 3 run/run.5 run:hlt4/run:hlt9 run/run.5 run:hlt4/run:hlt9 run/run.5 run:hlt4/run:hlt x x x 3 Thursday, June, 4
25 Cos(θNR) ngoodpv= ngoodpv=or ngoodpv> Entries 676 Mean.57 RMS.96 Entries 377 Mean.537 RMS Entries 7733 Mean.533 RMS.98 Entries 455 Mean.533 RMS Entries 3386 Mean.598 RMS.99 Entries 983 Mean.536 RMS run:hlt run:hlt9.3.5 run:hlt4 run:hlt9.3.5 run:hlt4 run:hlt cos( NR ) cos( NR ) cos( NR ) run/run.5 run:hlt4/run:hlt9 run/run.5 run:hlt4/run:hlt9 run/run.5 run:hlt4/run:hlt cos( NR ) cos( NR ) cos( NR ) Thursday, June, 5
26 χbz ngoodpv= ngoodpv=or ngoodpv>.6 Entries 3694 Mean.6858 RMS.4349 Entries Mean.687 RMS.4338 run:hlt4 run:hlt9.55 Entries 965 Mean RMS.44 Entries 7364 Mean.755 RMS.44 run:hlt4 run:hlt run:hlt4 run:hlt9 Entries 8453 Mean.78 RMS.4393 Entries 5484 Mean.7 RMS BZ BZ BZ run/run.5 run:hlt4/run:hlt9 run/run.5 run:hlt4/run:hlt9 run/run.5 run:hlt4/run:hlt BZ BZ BZ Thursday, June, 6
27 Summary data are compared with different Monte Carlo samples Sensitivity to different models decreases at higher pt threshold. Alpgen and Herwig6 samples don t have sufficient statistics. Measurements from data look fine. Thursday, June, 7
28 Plan of Work More recent data needs to be investigated. Comparison of 3-Jet distributions with NLL calculations has to be done. Detector Unfolding has to be done for the distributions. Also working on Measurement of Single Particle Response for JetMET group. Studies for Hcal Sampling Factors. Shift schedule at CERN: TRG-Offline from 4 Sep, to 6 Oct, RPC-CAF shifts from 3 Nov, upto 3 Nov, Thursday, June, 8
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