Energy deposition in dependence on p T
description
Transcript of Energy deposition in dependence on p T
Energy deposition in dependence on pT
Lukáš Malina
Datasets
• Real data: data11_7TeV.*.physics_JetTauEtmiss.merge.NTUP_SMQCD.*_p621/– Integral luminosity 1.031 fb-1 – Trigger EF_j240_a4tc_EFFS is used
• Monte Carlo: mc10_7TeV.*.J*_pythia_jetjet.merge.NTUP_SMQCD.*_p621/• MC histograms merged by hadd.C – different JX
samples (1-8) are weighted• Jet reconstruction algorithm AntiKT4 is used
Energy plots
• Data are split by rapidity and by reconstructed pT of jets– pT bins are 20 GeV/c wide
• Mean values of jet energy deposition in parts of calorimeter are calculated for every bin
TileBar1• Comparison of real data to simulation
TileBar1• Ratio of energy deposition from real data and from Monte Carlo
TileBar2• Comparison of real data to simulation
TileBar2• Ratio of energy deposition from real data and from Monte Carlo
TileExt1• Comparison of real data to simulation
TileExt1• Ratio of energy deposition from real data and from Monte Carlo
TileExt2• Comparison of real data to simulation
TileExt2• Ratio of energy deposition from real data and from Monte Carlo
HEC2• Comparison of real data to simulation
HEC2• Ratio of energy deposition from real data and from Monte Carlo
HEC3• Comparison of real data to simulation
HEC3• Ratio of energy deposition from real data and from Monte Carlo
pT distribution
Real Data Monte Carlo J1-8
φ distributionReal Data Monte Carlo J1-8
Conclusions
• It is necessary to fix a pileup bug in Monte Carlo (peaks about 200 GeV/c)– By cuting the pT interval of Jx sample
– By cuting the distance between truth and real primary vertex position