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Status Reports 05/08/13

Status Reports 05/08/13. Kittikul Kovitanggoon Texas Tech. Event Filter Efficiency. - The number of differential cross section in function jet multiplicity is 2-6% off from main analysis. - Checking the filter efficiency in order to correct the luminosity of data.

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Status Reports 05/08/13

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  1. Status Reports 05/08/13 Kittikul Kovitanggoon Texas Tech

  2. Event Filter Efficiency - The number of differential cross section in function jet multiplicity is 2-6% off from main analysis. - Checking the filter efficiency in order to correct the luminosity of data. - Taking the ratio between with and without filters process.scrapingVeto* process.primaryVertexFilter* process.HBHENoiseFilter* - Without filters, we have 4125.7 events/pb-1 - With filters, we have 4091.581 event/pb-1 - The efficiency is 0.991730131 - Also, fixed the misplace background.

  3. Njets

  4. Njets Bayes n jet=1 dSigma/dN=59.7235 n jet=2 dSigma/dN=12.461 n jet=3 dSigma/dN=2.44284 n jet=4 dSigma/dN=0.45098 n jet=5 dSigma/dN=0.0903426 n jet=6 dSigma/dN=0.0118748 n jet=7 dSigma/dN=0.00256435

  5. Analysis Note - Analysis note is on the process of writing. - Add some sections + plots.

  6. Jet PU MVA Data No MVA njet=0 events=6.73389e+06 njet=1 events=1.09789e+06 njet=2 events=237604 njet=3 events=47987 njet=4 events=9727 njet=5 events=1922 njet=6 events=328 njet=7 events=54 Loose MVA njet=0 events=6.77538e+06 njet=1 events=1.06871e+06 njet=2 events=228155 njet=3 events=45752 njet=4 events=9270 njet=5 events=1808 njet=6 events=308 njet=7 events=53 Tight MVA njet=0 events=6.84967e+06 njet=1 events=1.01825e+06 njet=2 events=210566 njet=3 events=41115 njet=4 events=8021 njet=5 events=1525 njet=6 events=252 njet=7 events=41

  7. Jet PU MVA Signal MC No MVA njet=0 events=2.98548e+06 njet=1 events=469430 njet=2 events=97152.6 njet=3 events=18260.1 njet=4 events=3532.94 njet=5 events=561.383 njet=6 events=94.5587 njet=7 events=14.576 Loose MVA njet=0 events=2.99982e+06 njet=1 events=458895 njet=2 events=94003.9 njet=3 events=17645.4 njet=4 events=3407.08 njet=5 events=539.343 njet=6 events=91.344 njet=7 events=13.5019 Tight MVA njet=0 events=3.02228e+06 njet=1 events=443081 njet=2 events=88882.6 njet=3 events=16295.8 njet=4 events=3113.08 njet=5 events=472.248 njet=6 events=82.402 njet=7 events=13.1739

  8. Back Up

  9. pT 1st jet

  10. pT 1st jet Bayes jet pT=30-40 dSigma/dpT=2.54153 jet pT=40-52 dSigma/dpT=1.451 jet pT=52-68 dSigma/dpT=0.808864 jet pT=68-88 dSigma/dpT=0.41331 jet pT=88-113 dSigma/dpT=0.194021 jet pT=113-144 dSigma/dpT=0.0883231 jet pT=144-184 dSigma/dpT=0.0357432 jet pT=184-234 dSigma/dpT=0.0137341 jet pT=234-297 dSigma/dpT=0.00523787 jet pT=297-377 dSigma/dpT=0.00162346 jet pT=377-480 dSigma/dpT=0.000493253

  11. pT 2nd jet

  12. pT 2nd jet Bayes jet pT=30-40 dSigma/dpT=0.681495 jet pT=40-52 dSigma/dpT=0.310099 jet pT=52-68 dSigma/dpT=0.139994 jet pT=68-88 dSigma/dpT=0.0613579 jet pT=88-113 dSigma/dpT=0.027411 jet pT=113-144 dSigma/dpT=0.0119028 jet pT=144-184 dSigma/dpT=0.00466968 jet pT=184-234 dSigma/dpT=0.00178095 jet pT=234-297 dSigma/dpT=0.000701831 jet pT=297-377 dSigma/dpT=0.00023195

  13. Eta 1st jet

  14. Eta 1st jet Bayes jet eta=-2.4 - -2.2 dSigma/deta=7.90703 jet eta=-2.2 - -2 dSigma/deta=9.30543 jet eta=-2 - -1.8 dSigma/deta=10.7622 jet eta=-1.8 - -1.6 dSigma/deta=12.1829 jet eta=-1.6 - -1.4 dSigma/deta=13.7685 jet eta=-1.4 - -1.2 dSigma/deta=15.5961 jet eta=-1.2 - -1 dSigma/deta=17.1706 jet eta=-1 - -0.8 dSigma/deta=18.3575 jet eta=-0.8 - -0.6 dSigma/deta=19.4455 jet eta=-0.6 - -0.4 dSigma/deta=19.8732 jet eta=-0.4 - -0.2 dSigma/deta=20.7432 jet eta=-0.2 - 0 dSigma/deta=20.6351 jet eta=0 - 0.2 dSigma/deta=20.8275 jet eta=0.2 - 0.4 dSigma/deta=20.5311 jet eta=0.4 - 0.6 dSigma/deta=19.8683 jet eta=0.6 - 0.8 dSigma/deta=19.4114 jet eta=0.8 - 1 dSigma/deta=18.3719 jet eta=1 - 1.2 dSigma/deta=17.4825 jet eta=1.2 - 1.4 dSigma/deta=15.6802 jet eta=1.4 - 1.6 dSigma/deta=13.6064 jet eta=1.6 - 1.8 dSigma/deta=12.4261 jet eta=1.8 - 2 dSigma/deta=10.8392 jet eta=2 - 2.2 dSigma/deta=9.69227 jet eta=2.2 - 2.4 dSigma/deta=7.95701

  15. Eta 2nd jet

  16. Eta 2nd jet Bayes jet eta=-2.4 - -2.2 dSigma/deta=2.10667 jet eta=-2.2 - -2 dSigma/deta=2.22449 jet eta=-2 - -1.8 dSigma/deta=2.57891 jet eta=-1.8 - -1.6 dSigma/deta=2.66274 jet eta=-1.6 - -1.4 dSigma/deta=2.96945 jet eta=-1.4 - -1.2 dSigma/deta=3.18708 jet eta=-1.2 - -1 dSigma/deta=3.46698 jet eta=-1 - -0.8 dSigma/deta=3.68425 jet eta=-0.8 - -0.6 dSigma/deta=3.88112 jet eta=-0.6 - -0.4 dSigma/deta=3.81791 jet eta=-0.4 - -0.2 dSigma/deta=4.00887 jet eta=-0.2 - 0 dSigma/deta=3.88695 jet eta=0 - 0.2 dSigma/deta=4.05213 jet eta=0.2 - 0.4 dSigma/deta=3.81493 jet eta=0.4 - 0.6 dSigma/deta=3.87524 jet eta=0.6 - 0.8 dSigma/deta=3.71031 jet eta=0.8 - 1 dSigma/deta=3.80595 jet eta=1 - 1.2 dSigma/deta=3.39447 jet eta=1.2 - 1.4 dSigma/deta=3.24747 jet eta=1.4 - 1.6 dSigma/deta=2.96745 jet eta=1.6 - 1.8 dSigma/deta=2.85722 jet eta=1.8 - 2 dSigma/deta=2.62035 jet eta=2 - 2.2 dSigma/deta=2.3338 jet eta=2.2 - 2.4 dSigma/deta=2.08618

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