Download - Jet Energy Scale
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Jet Energy Scale
March 31, 2009
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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
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CDF detectorCalorimeters:•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
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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:
• 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
The sum is over all towers within radius R with ET>1GeV
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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
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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
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Response to central hadrons
This is using single particles in CDF data.
Beyond 20 GeV, pions from test beam data are used
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Response to central hadrons
Good agreement with MC
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Response to EM particles
• 30% of jets are neutral pions->photons• Study EM response on electrons & positrons:
Better than 1% accuracy
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Uncertainties in calorimetry: hadronicLow 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
?
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Uncertainties in calorimetry: EM
Again, effects near edges of towers are added to systematics
“instrumentation between tower phi-boundaries”
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Summary: uncertainties
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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
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Dijet balance: cone=0.4Before correction: After correction:
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Dijet balance: cone=0.7
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Dijet balance: cone=1.0
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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
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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?
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Derived absolute energy scale
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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
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Uncertainties summary
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8. Multiple pp (pileup)
• N is Poisson-distributed ~ luminosity– Estimated as # z vertices
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Et in a cone -vs- # z vertices
Using minbias data.
0.2<|eta|<0.6
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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
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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
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OOC correction
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Summary of systematics
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Gam+jets: eta correction
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Gam+jets: abs correction
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Gam+jets: all correction
Data = MC within 2%