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Analysis of Jet Finding Algorithms in Run II Cone Methodology

This document explores the configurations and algorithms used for jet finding in particle physics, specifically focusing on the Run II cone algorithm with preclustering. It details the various parameters like jet energy scale corrections, the specific naming convention for algorithms, and differences between primary data sources including calorimeter data and Monte Carlo simulations. The standardized prefixes and parameter sets are elaborated for efficient data categorization. Additionally, it investigates the efficiency of QCD inclusive processes while addressing quality cuts applied to jets.

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Analysis of Jet Finding Algorithms in Run II Cone Methodology

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  1. D0 Jets

  2. In Top_analyze or Athena / rcp / D0ChunkAnalyze.rcp // Select the jet finding algorithm // (Run II 0.5 cone algorithm with preclustering) string JetAlgo_type = "PreSCilcone" string JetAlgo_names = ( "towers" "coneSize" "Radius_of_Cone" "Min_Jet_ET") float JetAlgo_values = ( 0. 0.3 0.5 8. ) // // Parameter for Jet Energy Scale Correction bool JetEnergyScale = true bool JetEnergyScale_muontag = true change to : partons particles then these must be changed to false

  3. # Standard block names for reco_analyze There are some standard rcp used in reco_analyze for the jet algorithms ran in d0reco in which we have defined a scheme for the naming of the prefix: JAXY, where * A is the algorithm: o K for kT o C for cone o S for simple cone o N for CellNN o E for Emnn * X represent the type of data used: o C for calorimeter data o M for Monte Carlo particles o P for Monte Carlo partons * Y represents a parameter set That translates into : * JCCG : RUN I cone on cal towers R=0.7, with NN preclustering * JCCH : RUN I cone on cal towers R=0.5, with NN preclustering * JCCI : RUN I cone on cal towers R=0.3, with NN preclustering * JCC7 : RUN I cone on cal towers R=0.7, with simple cone preclustering * JCM7 : RUN I cone on MC particles R=0.7, with simple cone preclustering

  4. JAXY * A is the algorithm: o K for kT o C for cone o S for simple cone o N for CellNN o E for Emnn * X represent the type of data used: o C for calorimeter data o M for Monte Carlo particles o P for Monte Carlo partons * Y represents a parameter set * JCCA : RUN II cone on cal towers R=0.7 * JCMG : idem on MC particles * JCPG : idem on MC partons * JCCB : RUN II cone on cal towers R=0.5 * JCMB : idem on MC particles * JCPB : idem on MC partons * JCCC : RUN II cone on cal towers R=0.3 * JCMC : idem on MC particles * JCPC : idem on MC partons * JKC1 : kT RUN I on cal towers D=1 * JKM1 : idem on MC particles * JKCA : kT RUN II on cal towers D=1 * JKMA : idem on MC particles * JKCB : kT RUN II on cal towers D=0.4 * JKMB : idem on MC particles

  5. // Select the jet finding algorithm // (Run II 0.5 cone algorithm with preclustering) string JetAlgo_type = "PreSCilcone" string JetAlgo_names = ( "towers" "coneSize" "Radius_of_Cone" "Min_Jet_ET") float JetAlgo_values = ( 0. 0.3 0.5 8. ) JetAlgo_types cone PreNNcone PreSCcone ilcone PreNNilcone PreSCilcone scone EMNN ConePreKT PreKT GeomPreKT From : JetAlgoInfo package

  6. Extracting QCD - inclusive from Event # is 0 id 21 E 669.206 pt 0.653522 parent id 0 - gluon id 21 E 190.604 pt 0.416215 parent id 0 diff 478.602 id 1 E 34.8521 pt 9.71758 parent id 21 - down & antidown quark id -1 E 68.2385 pt 12.6132 parent id 21 total 103.091 diff 87.5 id 23 E 103.091 pt 15.7099 parent id 0 Z id 23 E 103.091 pt 15.7099 parent id 0 id 11 E 48.6631 pt 38.0618 parent id 23 - electron id 22 E 0.337637 pt 0.265241 parent id 23 id -11 E 54.0895 pt 54.0027 parent id 23 - positron id 22 E 0.000384438 pt 0.000384364 parent id 23 total 103.09 id -1 E 19.7874 pt 1.09119 parent id 21 id 21 E 7.58414 pt 0.473604 parent id 21 id 21 E 21.8103 pt 0.749341 parent id 21 total 49.1818 id 21 E 504.602 pt 2.03176 parent id 21 from 478.602 and diff in 87.5-49.1818 id 1 E 20.8546 pt 0.439262 parent id 0 id 1 E 102.435 pt 1.97383 parent id 21 id -1 E 62.6756 pt 0.329602 parent id 0 id 2203 E 288.84 pt 0.846207 parent id 0 id 21 E 64.4004 pt 1.10593 parent id 21 id 21 E 0.358559 pt 0.341552 parent id 21 etc...

  7. The QCD - Inclusive mc p13 sample QCD (u d s g) - Pythia requested by the New Phenomena group in the following pt regions 5 <pt<10 5K events 10<pt<20 5K events pt range 20<pt<40 5K events definition name : p13.05.00_qcd_incl_pt10-20_mb-0.5_tmb Top Analyze was run over the thumbnails with all quality cuts on the jets removed The partons were selected by being the first generation of u,d,s,or gluon The QCD - Inclusive mc p14 sample A mc p14 QCD(u d s g) in Pythia has been requested by the New Phenomena group the file have not been generated yet Used: pythia mc p14.03.01 Athena was run over the thumbnails and the partons were selected by having pt>11.0 and being formed at the Z decayed

  8. MCP 13 QCD Reco Efficiency

  9. MCP 14 RECO EFF

  10. Overlay of QCD MCP13 and MCP14 RECO Effici

  11. QCD MCP14 Parton Efficiency and Particle Efficiency

  12. MC P14 Higgs Parton Effic and Particle Effic

  13. Higgs Reco Effic with all quality cuts

  14. Ratio of b jet reco eff / qcd jete reco eff Central Region -0.7 < eta < 0.7 Fit function tanh ( p0 * x + p1) parton pt GeV

  15. Ratio b jet reco eff / qcd jet reco eff middle and central region Middle Region -1.7<eta<-0.7 or 0.7<eta<1.7 tanh( p0*x + p1) parton pt GeV Forward Region -2.5<eta<-1.6 or 1.6<eta<2.5 tanh( p0*x + p1) Parton pt GeV

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