1. Study of the Subjet Multiplicity at CMS Manuk Zubin Mehta Prof. Manjit Kaur Panjab University Chandigarh 12/21/2015Inida CMS-Meeting

2. 12/21/2015Inida CMS-Meeting Introduction The jet shape study could provide the tool for quark-gluon jets separation: The internal structure of a jet is expected to depend on the type of parton creating the jet (quark or gluon) and E T of the jet. the study of jet shapes can help to test the models of underlying events.

3. Jet Structure * Number of variables that has been proposed to study jet structure of jets. - Jet transverse momentum distribution measured as a function of distance from jet axis. - Jet mass. Etc. * We have used Subjet analysis to study jet structure, which is useful for discriminating between quarks and gluon jets and for calculating ratio of color charges C A /C F = 9/4 12/21/2015Inida CMS-Meeting

4. SubJets *The Subjet multiplicity is a natural observable of a K T algorithm. *Subjets are defined by reapplying the K T algorithm, this time starting with a constituents of a jet. *Number of Subjets within the jet is the Subjet multiplicity M. *Jet initiated by gluons are significantly different than jets initiated by quarks. As compared to quark jets, gluon jets had more particles, a softer momentum distribution and are more spread out. 12/21/2015Inida CMS-Meeting

5. Standard Event Selection For Data Single Jet Trigger P T >30GeV Technical Trigger Bits – 0 AND (40 OR 41) AND NOT (36 OR 37 OR 38 OR 39) Scraping veto Primary vertex: – >= 4 DOF – |z| < 15 cm { The Trigger 0 Bit and Beam Halo (36 OR 37 OR 38 OR 39) are dropped for MC} 5 12/21/2015Inida CMS-Meeting

6. Jet Selection Criteria Selecting Di Jet (Leading in E T ) Jet Quality Criteria :: Loose Jet ID criteria (EMF > 0.01, n 90 hits > 1, f HPD < 0.98) | – ℿ | < 1.0 P T > 50 GeV |eta | < 3.0 K T,D=0.6 algorithm used 12/21/2015Inida CMS-Meeting

7. Data Samples 12/21/2015Inida CMS-Meeting Runs < 135808 /MinimumBias/Commissioning10-SD_JetMETTau-Jun14thSkim_v1/RECO Runs >= 135808 /JetMETTau/Run2010A-Jun14thReReco_v2/RECO Runs > 137437 upto 139790 /JetMETTau/Run2010A-PromptReco-v4/RECO Integrated Lumi for Analyzed Data = 78.49 nb -1 MC Samples /QCD_Pt30/Spring10-START3X_V26_S09-v1/GEN-SIM-RECO /QCD_Pt30-herwig/Spring10-START3X_V26_S09-v1/GEN-SIM-RECO /QCD_Pt30-herwigjimmy/Spring10-START3X_V26_S09-v1/GEN-SIM- RECO

8. 12/21/2015Inida CMS-Meeting Monte Carlo used: Herwig++, Pythia 6, Herwig6+Jimmy Herwig and Pythia use different hadronization model Also using different Underlying Event models (UE is used to tune MC generators to data and measured in transverse region)

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15. 12/21/2015Inida CMS-Meeting Plan of the near future We will derive systematic uncertainties using Different MC, as different models of fragmentation lead to different shape and ratio of quark & gluon jets. We will also analyze the 2009+2010 900GeV Data and different tuned MC Sample. Comments and suggestions are welcome!

16. 12/21/2015Inida CMS-Meeting Back Up Slide

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19. 12/21/2015Inida CMS-Meeting The k t algorithm for hadron-hadron collision exists in two main forms, inclusive and exclusive. They use the same interparticle (d ij ) and particle-beam (d iB ) distance measures: where k ti, y i and φ i are the transverse momentum, rapidity and azimuth of particle i and R is a jet-radius parameter.

20. 12/21/2015Inida CMS-Meeting Inclusive algorithm 1. In the inclusive k t > algorithm all particles end up in a jet. The recombination procedes as follows: 2. Find the minimum d min of all the d ij,d iB. 3. If d min is a d ij merge particles i and j into a single particle, summing their four- momenta (this is E-scheme recombination); if it is a d iB then declare particle i to be a final jet and remove it from the list. Repeat from step 1 until no particles are left. Exclusive algorithm 1. The exclusive algorithm introduces a squared transverse momentum scale d cut, which acts as a threshold for separating out jets. 2. Find the minimum d min of all the d ij,d iB. If d min > d cut stop the clustering; all remaining particles are the final jets. Sometimes, instead of using an explicit d cut, the clustering is stopped when one reaches a given number