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Jet Energy Scale

Jet Energy Scale. March 31, 2009. Jet energy vs parton energy. Eta-dependent corrections : even calorimeter response Multiple interactions : garbage from extra ppbar events in the same BC Absolute energy scale : conversion from calo measurement to underlying jet

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Jet Energy Scale

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  1. Jet Energy Scale March 31, 2009

  2. Jet energy vs parton energy Eta-dependent corrections: even calorimeter response Multiple interactions: garbage from extra ppbar events in the same BC Absolute energy scale: conversion from calo measurement to underlying jet Underlying event and out-of-cone corrections: independent of detector

  3. CDF detector • Calorimeters: • CEM: central electromagnetic calorimeter • CEH: central hadronic calorimeter • PEM: plug electromagnetic calorimeter • PEH: plug hadronic calorimeter • WHA: wall hadronic calorimeter • Tracking: • Silicon detectors near beam pipe • COT (drift chamber) beyond • In central region, near-100% efficiency • Excellent momentum measurement

  4. Jet clustering • Jets are formed in cones of R=0.4, 0.7, 1.0 • Start with calo towers with ET>1GeV (seeds) • Compute energy and position of cluster candidates: The sum is over all towers within radius R with ET>1GeV • Repeat, using cluster centers as new seeds • Merge final (stable) list of clusters if overlap>50% • For MC particle jets: use stable FS particles instead

  5. 5. Calorimeter simulation • Absolute energy scale is determined from MC • Need very good understanding of calorimeter MC simulation • GFLASH parameterizes EM and hadronic shower profiles • Energy deposited by a shower in calorimeter volume: • L(z) and T(r) contain several dozen parameters • Hadronic parameters are tuned to CDF data using: • Single isolated tracks from minbias data (p=0.5 – 5 GeV) • Test beam data (p=7 – 220 GeV) • Prior experiments (H1 collaboration) • EM shower parameters: • Tuned in test beam • Cross-checked in-situ via Z->ee

  6. Response to hadrons • ~70% of jets are charged & stable neutral hadrons • Do tracking on isolated charged particle (get p) • Extrapolate where it hits calorimeters (“target”) • Define signal and BG regions that contain E • Veto on tracks & deposits in 7x7 block

  7. Response to central hadrons This is using single particles in CDF data. Beyond 20 GeV, pions from test beam data are used

  8. Response to central hadrons Good agreement with MC

  9. Response to EM particles • 30% of jets are neutral pions->photons • Study EM response on electrons & positrons: Better than 1% accuracy

  10. Uncertainties in calorimetry: hadronic Low pt: limited performance of calo simulation High pt: test beam momentum scale & shorter integration time in CDF –vs- test beam This is for inner 81% of the calo towers Performance near tower edges is shoved into systematic uncertainty ?

  11. Uncertainties in calorimetry: EM Again, effects near edges of towers are added to systematics “instrumentation between tower phi-boundaries”

  12. Summary: uncertainties

  13. 6. Eta corrections • Calo simulation is most reliable in central • This is thanks to excellent tracking there • Thus, forward calo is calibrated wrt central • Eta differences arise because: • Two halves of central calo meet at eta=0 • Crack near eta=1.1 where central and plug join • Dijet balancing: • Apply many cuts to reduce QCD contamination • Define “trigger” jet with 0.2<|eta|<0.6 • Balance against “probe” jet (can be across any eta) 1/beta is correction factor =

  14. Dijet balance: cone=0.4 After correction: Before correction:

  15. Dijet balance: cone=0.7

  16. Dijet balance: cone=1.0

  17. Systematic uncertainty • Remaining discrepancies are due to limitations of parametrization of eta and pt dependence • Event selection and fitting procedures are varied to further define systematic uncertainty

  18. 7. Absolute JES • Entirely MC-based & tuned to central calo • That’s why calo simulation was carefully studied • Probability to find jet pt, given particle jet pt: Are these formulas supposed to be obvious?

  19. Derived absolute energy scale

  20. Uncertainties on absolute scale • Method depends on MC modeling of: • Multiplicity and Pt spectrum of particles in a jet • Calo response to each of these particles

  21. Uncertainties summary

  22. 8. Multiple pp (pileup) • N is Poisson-distributed ~ luminosity • Estimated as # z vertices

  23. Et in a cone -vs- # z vertices Using minbias data. 0.2<|eta|<0.6

  24. Uncertainty • Uncertainty comes from: • Vertex reco efficiency • Vertex fake rate (esp. with many tracks) • These effects are studies with: • W->eν • Minbias • 100 GeV jets • Found little dependence on lumi or event topology

  25. Out-of-cone and underlying • Determined solely from MC using Pythia dijets • Small cone dominated by out-of-cone losses • Large cone dominated by UE pollution • Uncertainties studied via gamma+jets

  26. OOC correction

  27. Summary of systematics

  28. Gam+jets: eta correction

  29. Gam+jets: abs correction

  30. Gam+jets: all correction Data = MC within 2%

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