Introduction to Hadronic Final State Reconstruction in Collider Experiments (Part II)
Introduction to Hadronic Final State Reconstruction in Collider Experiments (Part XII)
description
Transcript of Introduction to Hadronic Final State Reconstruction in Collider Experiments (Part XII)
Intr
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Introduction to Hadronic Final State Reconstruction in Collider Experiments
(Part XII)
Introduction to Hadronic Final State Reconstruction in Collider Experiments
(Part XII)
Peter LochPeter LochUniversity of ArizonaUniversity of Arizona
Tucson, ArizonaTucson, ArizonaUSAUSA
Peter LochPeter LochUniversity of ArizonaUniversity of Arizona
Tucson, ArizonaTucson, ArizonaUSAUSA
2P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Preliminaries
Plots for this sessionPlots for this session Most if not all plots shown in this session are meant as examples and for Most if not all plots shown in this session are meant as examples and for
illustration purposesillustration purposes Educational showcases to highlight certain features of energy scales and Educational showcases to highlight certain features of energy scales and
calorimeter responsecalorimeter response
They do not represent the up-to-date estimates for ATLAS jet They do not represent the up-to-date estimates for ATLAS jet reconstruction performancereconstruction performance In general much better than the (old) results shown here!In general much better than the (old) results shown here! Not many new plots can be shown in public yet!Not many new plots can be shown in public yet!
The performance plots shown are published The performance plots shown are published Reflection of state-of-art at a given moment in timeReflection of state-of-art at a given moment in time No experimental collision data available at that time!No experimental collision data available at that time!
3P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Summary Of Jet Inputs
Experiment and simulationExperiment and simulation Calorimeter towersCalorimeter towers
2-dim signal objects from all cells or only 2-dim signal objects from all cells or only cells surviving noise suppression cells surviving noise suppression (topological towers in ATLAS)(topological towers in ATLAS)
Calorimeter clustersCalorimeter clusters 3-dim signal objects with implied noise 3-dim signal objects with implied noise
suppression (topological clusters in ATLAS)suppression (topological clusters in ATLAS)
TracksTracks Reconstructed inner detector tracks – only Reconstructed inner detector tracks – only
charged particles with pT > pTcharged particles with pT > pTthresholdthreshold = 500 = 500 MeV – 1 GeV (typically)MeV – 1 GeV (typically)
Simulation onlySimulation only Generated stable particlesGenerated stable particles
Typically Typically ττlablab > 10 ps to be a signal source > 10 ps to be a signal source
towerstowers
clustersclusters
particlesparticles
trackstracks
4P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Image Of Jets In Calorimeter
5P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Calorimeter Jet Response
Calorimeter jet responseCalorimeter jet response Electromagnetic energy scaleElectromagnetic energy scale
Available for all signal Available for all signal definitionsdefinitions
No attempt to compensate or No attempt to compensate or correct signal for limited correct signal for limited calorimeter acceptancecalorimeter acceptance
Global hadronic energy scaleGlobal hadronic energy scale All signal definitions, but All signal definitions, but
specific calibrations for each specific calibrations for each definitiondefinition
Calibrations normalized to Calibrations normalized to reconstruct full true jet energy reconstruct full true jet energy in “golden regions” of in “golden regions” of calorimetercalorimeter
Local hadronic energy scaleLocal hadronic energy scale Topological clusters onlyTopological clusters only No jet context – calibration No jet context – calibration
insufficient to recover insufficient to recover calorimeter acceptance calorimeter acceptance limitations – no corrections for limitations – no corrections for total loss in dead material and total loss in dead material and magnetic field charged magnetic field charged particles losses)particles losses)
0,tower particletowers in particles in
jet jet0,jet
0,jet 0,tower particletowers in particles i
jet
reconstructed calorimeter jet
Unbiased and noise-suppressed towers:
E EEp p p
0,clusterclusters in
jet0,jet
0,jet 0,clusterclust
njet
matched particle
ers injet
reconstructed ca
jet(truth reference)
lorimeter jet
Topological cell clusters:
EEp p
particleparticles in
jet
particleparticles in
jet
matched particle
2 2jet jet jett owers clusters
jet(truth reference)
Note at any scale:
0 for , 1m E p N N
E
p
6P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Calorimeter Jet Response
Calorimeter jet responseCalorimeter jet response Electromagnetic energy scaleElectromagnetic energy scale
Available for all signal Available for all signal definitionsdefinitions
No attempt to compensate or No attempt to compensate or correct signal for limited correct signal for limited calorimeter acceptancecalorimeter acceptance
Global hadronic energy scaleGlobal hadronic energy scale All signal definitions, but All signal definitions, but
specific calibrations for each specific calibrations for each definitiondefinition
Calibrations normalized to Calibrations normalized to reconstruct full true jet energy reconstruct full true jet energy in “golden regions” of in “golden regions” of calorimetercalorimeter
Local hadronic energy scaleLocal hadronic energy scale Topological clusters onlyTopological clusters only No jet context – calibration No jet context – calibration
insufficient to recover insufficient to recover calorimeter acceptance calorimeter acceptance limitations – no corrections for limitations – no corrections for total loss in dead material and total loss in dead material and magnetic field charged magnetic field charged particles losses)particles losses)
cell cell 0,cell DMcells in
jetrec,jet
0,jetrec,jetcell cell 0,cell DM
cells in 0,jetjet
Cell based calibration for all calorimeter signals and jets in "golden spot":
( , )
( , )
w E E
Epp w p Ep
reconstructed calorimeter jet
particleparticles in
jet
particleparticles in
jet
matched particle jet(truth reference)
(cells are extracted fr
E
p
om unbiased or noise suppressed
towers or topological clusters forming the jet)
7P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Calorimeter Jet Response
Calorimeter jet responseCalorimeter jet response Electromagnetic energy scaleElectromagnetic energy scale
Available for all signal Available for all signal definitionsdefinitions
No attempt to compensate or No attempt to compensate or correct signal for limited correct signal for limited calorimeter acceptancecalorimeter acceptance
Global hadronic energy scaleGlobal hadronic energy scale All signal definitions, but All signal definitions, but
specific calibrations for each specific calibrations for each definitiondefinition
Calibrations normalized to Calibrations normalized to reconstruct full true jet energy reconstruct full true jet energy in “golden regions” of in “golden regions” of calorimetercalorimeter
Local hadronic energy scaleLocal hadronic energy scale Topological clusters onlyTopological clusters only No jet context – calibration No jet context – calibration
insufficient to recover insufficient to recover calorimeter acceptance calorimeter acceptance limitations – no corrections for limitations – no corrections for total loss in dead material and total loss in dead material and magnetic field charged magnetic field charged particles losses)particles losses)
rec,cluster particleclusters in particles in
jet jetrec,jet
rec,jet rec,cluster particletowers in p
jet
reconstructed calorimeter jet
Locally calibrated clusters only:
E EEp p p
articles in
jet
matched particle jet(truth reference)
8P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Jet Energy Scale
Final Jet Energy Scale (JES)Final Jet Energy Scale (JES) Final jet calibrationFinal jet calibration
All corrections appliedAll corrections applied
Best estimate of true (particle) jet energyBest estimate of true (particle) jet energy Flat response as function of pTFlat response as function of pT Uniform response across whole calorimeterUniform response across whole calorimeter
Relative energy resolutionRelative energy resolution Depends on the calorimeter jet response – calibration applies compensation correctionsDepends on the calorimeter jet response – calibration applies compensation corrections
Resolution improvements by including jet signal featuresResolution improvements by including jet signal features Requires corrections sensitive to measurable jet variablesRequires corrections sensitive to measurable jet variables Can use signals from other detectorsCan use signals from other detectors
Determination with simulationsDetermination with simulations Measure residual deviations of the calorimeter jet response from truth jet energyMeasure residual deviations of the calorimeter jet response from truth jet energy
Derive corrections from the calorimeter response at a given scale as function of pT (linearity) Derive corrections from the calorimeter response at a given scale as function of pT (linearity) and pseudorapidity (uniformity) for all particle jetsand pseudorapidity (uniformity) for all particle jets
Use numerical inversion to parameterize correctionsUse numerical inversion to parameterize corrections Conversion from truth variable dependence of response to reconstructed variable responseConversion from truth variable dependence of response to reconstructed variable response
9P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Signal Linearity
From simulations From simulations Compare calorimeter response with particle Compare calorimeter response with particle
jet energy as function of the particle jet jet energy as function of the particle jet energyenergy
All jets, all regions, full kinematic coverageAll jets, all regions, full kinematic coverage Residual deviation from linearityResidual deviation from linearity
Depend on calorimeter energy scale – large Depend on calorimeter energy scale – large for electromagnetic energy scale and local for electromagnetic energy scale and local calibration due to missing jet level calibration due to missing jet level correctionscorrections
Small for global calibration due to jet Small for global calibration due to jet energy normalizationenergy normalization
Corrections can be extracted from residualsCorrections can be extracted from residuals A bit tricky – need to use numerical A bit tricky – need to use numerical
inversion (see later)inversion (see later)
From experimentFrom experiment Validate and extract calibrations from collision Validate and extract calibrations from collision
datadata W boson mass in hadronic decay is jet W boson mass in hadronic decay is jet
energy scale referenceenergy scale reference pT balance of electromagnetic signal (Z pT balance of electromagnetic signal (Z
boson, photon) and jetboson, photon) and jet Note change of reference scaleNote change of reference scale
In-situ channels provide interaction In-situ channels provide interaction (parton) level truth reference!(parton) level truth reference!
Global CalibrationGlobal Calibration
Local CalibrationLocal Calibration
tower jet closure test for calibrated calorimeter response
cluster jet closure test
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10P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Signal Uniformity
SimulationsSimulations Compare calorimeter response Compare calorimeter response
with particle jet energy as with particle jet energy as function of the jet directionfunction of the jet direction All jets in full kinematic rangeAll jets in full kinematic range
Residual non-uniformities Residual non-uniformities expected in cracksexpected in cracks Only jets in “golden regions” Only jets in “golden regions”
used for calibrationused for calibration
From experimentFrom experiment Di-jet pT balanceDi-jet pT balance
Balance pT of well calibrated jet Balance pT of well calibrated jet in “golden region” with jet in in “golden region” with jet in other calorimeter regions other calorimeter regions
Can also use photon pT balance Can also use photon pT balance with jets outside of “golden with jets outside of “golden region”region”
Global CalibrationGlobal Calibration
Local CalibrationLocal Calibration
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11P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Relative Jet Energy Resolution
SimulationsSimulations Measure fluctuations of Measure fluctuations of
calorimeter jet energy as calorimeter jet energy as function of truth jet energyfunction of truth jet energy All jets in full kinematic range All jets in full kinematic range
and in various regions of and in various regions of pseudo-rapiditypseudo-rapidity
From experimentFrom experiment Di-jet final statesDi-jet final states
Measure relative fluctuations Measure relative fluctuations of jet energies in back-to-back of jet energies in back-to-back (pT) balanced di-jets(pT) balanced di-jets
Global CalibrationGlobal Calibration
Local CalibrationLocal Calibration
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12P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
JES Calibration Parameterizations
Golden rule of calorimetric energy measurementGolden rule of calorimetric energy measurement The fully calibrated calorimeter signal is most probably the true jet (or particle) The fully calibrated calorimeter signal is most probably the true jet (or particle)
energyenergy Interpretation holds only for symmetrically distributed fluctuations – mean value is Interpretation holds only for symmetrically distributed fluctuations – mean value is
identical to average value identical to average value
The resolution of the measurement is given by the characteristics of the signal The resolution of the measurement is given by the characteristics of the signal fluctuationsfluctuations Can only be strictly and correctly understood in case of Gaussian response distributionsCan only be strictly and correctly understood in case of Gaussian response distributions
We need a normally distributed response!We need a normally distributed response!
Problem for all calibration techniquesProblem for all calibration techniques Residual deviations from expected jet reconstruction performance must be measure Residual deviations from expected jet reconstruction performance must be measure
as function of true quantitiesas function of true quantities Only then is the fluctuation of the response Only then is the fluctuation of the response RR = = EErecoreco//EEtruetrue really Gaussian after calibration really Gaussian after calibration
But need to apply corrections to measured jetsBut need to apply corrections to measured jets Need parameterization as function of reconstructed quantitiesNeed parameterization as function of reconstructed quantities Simple re-binning does not maintain the Gaussian characteristics of the fluctuations – hard Simple re-binning does not maintain the Gaussian characteristics of the fluctuations – hard
to control error!to control error!
Use numerical inversion to transfer the calibrations from true to measured Use numerical inversion to transfer the calibrations from true to measured parametersparameters Maintains Gaussian character Maintains Gaussian character
13P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Understanding Response Fluctuations
Toy model Toy model Generate flat jet energy Generate flat jet energy
spectrumspectrum Uniform energy distribution for Uniform energy distribution for
EEjetjet in [ in [EEminmin,,EEmaxmax]]
Smear true jet energy with Smear true jet energy with GaussianGaussian Assume perfect average Assume perfect average
calibrationcalibration Width of distribution follows Width of distribution follows
calorimetric energy resolution calorimetric energy resolution function function
Calculate the response Calculate the response In bins of In bins of EEtruetrue and in bins of and in bins of
EEsmearsmear = = EErecoreco
Repeat exercise with steeply Repeat exercise with steeply falling energy spectrumfalling energy spectrum
smear reco true
22
true
smear true
2
Calibrated response:
Calorimeter resolution function (no noise):
Smeared energy:
is a random number following the Gaussian PD
1 1(
F:
) exp2
e2
i.
E
E
E E E
ac
E E
E E r
g r
r
r
smear true
true
. distributed around 0 with a width of 1Response fluctuations:
with 0E E
R RE
14P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Response Distributions
true( )p E const 4true true( )p E E
Lower edge of Lower edge of EE spectrum spectrum
Center of Center of EE spectrum spectrum
High end of High end of EE spectrum spectrum
smea
t
r
rue
binned in binned in
EE
15P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Response Distributions
true( )p E const 4true true( )p E E
Lower edge of Lower edge of EE spectrum spectrum
Center of Center of EE spectrum spectrum
High end of High end of EE spectrum spectrum
smea
t
r
rue
binned in binned in
EE
16P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Numerical Inversion
( )trueR E
( )recR E
( )true trueR E E
trueE
Transfer of response function from dependence on true variable to dependence on measured variable
rec true true( ) ( )R E R R E E
rec true true( )E R E E
17P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Numerical Inversion Functions
Often simple functionsOften simple functions Address residual energy (pT) Address residual energy (pT)
and direction dependence of and direction dependence of calorimeter jet responsecalorimeter jet response Determine response Determine response
functions functions RR in bins of true jet in bins of true jet pT and reconstructed pT and reconstructed pseudo-rapidity pseudo-rapidity ηηrec,jetrec,jet
Apply numerical inversion to Apply numerical inversion to determine calibration determine calibration functions in reconstructed functions in reconstructed variable space (variable space (ppT,rec,jetT,rec,jet,, η ηrec,jetrec,jet ) )
Use calibration functions to Use calibration functions to get jet energy scaleget jet energy scale Technique can be applied to Technique can be applied to
locally or globally calibrated locally or globally calibrated jet response, with likely jet response, with likely different calibration different calibration functions functions
truth,jet1T,truth,jet r
1T,truth
eco,jet T,truth,jet reco,jet
,jet r
reco
eco,jet T,truth,jet reco,jet
T,
,jett ruth,
truth,jet re
rec,jet
jet
( , ) (
with and
then apply numerical inversio
( , ) ( ,
, )
(
n
,
)
f p R p
f p
ER p p
E
numericalinversion
co,jet T,reco,jet reco,jet) ( , )f p
T,truth,jet rec,jet( , )f p
T,rec,jet rec,jet( , )f p
T,trT,r uthec,jet ,jet(GeV) ( Vor Ge )p p
18P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Numerical Inversion Functions
Often simple functionsOften simple functions Address residual energy (pT) Address residual energy (pT)
and direction dependence of and direction dependence of calorimeter jet responsecalorimeter jet response Determine response Determine response
functions functions RR in bins of true jet in bins of true jet pT and reconstructed pT and reconstructed pseudo-rapidity pseudo-rapidity ηηrec,jetrec,jet
Apply numerical inversion to Apply numerical inversion to determine calibration determine calibration functions in reconstructed functions in reconstructed variable space (variable space (ppT,rec,jetT,rec,jet,, η ηrec,jetrec,jet ) )
Use calibration functions to Use calibration functions to get jet energy scaleget jet energy scale Technique can be applied to Technique can be applied to
locally or globally calibrated locally or globally calibrated jet response, with likely jet response, with likely different calibration different calibration functions functions
reco,jet
reco,jet
calib,jet
calib,jet
cell cell 0,cell DMcells in
jet
T,reco,jet reco,jet 0,jetcell cell 0,cell DM
cells in 0,jetjet
, wi
global cal
( , )
( , )( ,
ibration
)
:
E
p
Ep
w E E
f p pw p E
p
2T,reco,jet reco,jet reco,jet
rec,clusterclusters in
jetcalib,jetT,reco,jet reco,jet
calib,jet rec,
th 1 ta
clustertower
nh
s inje
local cali
( , )
bration:
p p
EE
f pp p
t
19P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Erec,jet Versus Etruth,jet
Why not use direct relation Why not use direct relation between reconstructed and true between reconstructed and true energy?energy? Same simulation data inputSame simulation data input
Has been used in some Has been used in some experimentsexperiments
Dependence on truth energy Dependence on truth energy spectrumspectrum Need to make sure calibration Need to make sure calibration
sample is uniform in truth sample is uniform in truth energyenergy
Alternatively, unfold driving Alternatively, unfold driving truth energy spectrum truth energy spectrum
Residual non-gaussian behaviour Residual non-gaussian behaviour of truth energy distributionof truth energy distribution Error on reconstructed energy Error on reconstructed energy
hard to understandhard to understand Could still use response Could still use response
distribution → same issues as distribution → same issues as discussed on previous slide!discussed on previous slide!
rec,jet(GeV)E
truth,jet(GeV)E
4truth,jetcross-section E
4truth,jetweight E
truth,jet(GeV)E
20P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Erec,jet Versus Etruth,jet
Why not use direct relation Why not use direct relation between reconstructed and true between reconstructed and true energy?energy? Same simulation data inputSame simulation data input
Has been used in some Has been used in some experimentsexperiments
Dependence on truth energy Dependence on truth energy spectrumspectrum Need to make sure calibration Need to make sure calibration
sample is uniform in truth sample is uniform in truth energyenergy
Alternatively, unfold driving Alternatively, unfold driving truth energy spectrum truth energy spectrum
Residual non-gaussian behaviour Residual non-gaussian behaviour of truth energy distributionof truth energy distribution Error on reconstructed energy Error on reconstructed energy
hard to understandhard to understand Could still use response Could still use response
distribution → same issues as distribution → same issues as discussed on previous slide!discussed on previous slide!
truth,jet(GeV)E
rec,jet(GeV)E
truth,jet(GeV)E
4truth,jetcross-section E
4truth,jetweight E
21P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Erec,jet Versus Etruth,jet
Why not use direct relation Why not use direct relation between reconstructed and true between reconstructed and true energy?energy? Same simulation data inputSame simulation data input
Has been used in some Has been used in some experimentsexperiments
Dependence on truth energy Dependence on truth energy spectrumspectrum Need to make sure calibration Need to make sure calibration
sample is uniform in truth sample is uniform in truth energyenergy
Alternatively, unfold driving Alternatively, unfold driving truth energy spectrum truth energy spectrum
Residual non-gaussian behaviour Residual non-gaussian behaviour of truth energy distributionof truth energy distribution Error on reconstructed energy Error on reconstructed energy
hard to understandhard to understand Could still use response Could still use response
distribution → same issues as distribution → same issues as discussed on previous slide!discussed on previous slide!
truth,jet(GeV)E
rec,jet(GeV)E
truth,jet(GeV)E
truth,jet rec,jet 1( ), [ , [i ih E E E E
rec,jett ruth,jet 1( ), [ , [i ih E E E E
4truth,jett ruth,jet
rec,jet 1
( ) ,
[ , [i i
h E E
E E E
22P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Systematic Error
Strategy from simulationsStrategy from simulations Determine all calibrations with fixed conditionsDetermine all calibrations with fixed conditions
Ideal detector model – everything is alignedIdeal detector model – everything is aligned Fixed (best) GEANT4 shower model – from testbeam evaluationsFixed (best) GEANT4 shower model – from testbeam evaluations Fixed calorimeter signal definition – e.g., towersFixed calorimeter signal definition – e.g., towers Fixed jet definition – like seeded cone with size 0.7Fixed jet definition – like seeded cone with size 0.7 Fixed final state – QCD di-jets preferredFixed final state – QCD di-jets preferred
Study change in performance for changing conditions with ideal calibration Study change in performance for changing conditions with ideal calibration appliedapplied Detector misalignment and changes in material budgetsDetector misalignment and changes in material budgets Different shower GEANT4 modelDifferent shower GEANT4 model Different calorimeter signal definitions – e.g., clustersDifferent calorimeter signal definitions – e.g., clusters Different jet definitions – e.g., kT, AntikT, different cone or cone sizes…Different jet definitions – e.g., kT, AntikT, different cone or cone sizes… Different physics final state – preferably more busy ones like SUSY, ttbar,…Different physics final state – preferably more busy ones like SUSY, ttbar,…
Use observed differences as systematic error estimatesUse observed differences as systematic error estimates Use of collision dataUse of collision data
Compare triggered final states with simulationsCompare triggered final states with simulations Level of comparison represents understanding of measurement – systematic Level of comparison represents understanding of measurement – systematic
error (at least for standard final states)error (at least for standard final states) Use in-situ final states to validate calibrationUse in-situ final states to validate calibration
Careful about biases and reference levels (see session 9)Careful about biases and reference levels (see session 9)
23P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Performance Evaluation
Calibration functions determined with “perfect” detector description and Calibration functions determined with “perfect” detector description and one reference jet definitionone reference jet definition Validate performance in perfect detector Validate performance in perfect detector
Signal linearity & resolutionSignal linearity & resolution Quality of calibration for a real detectorQuality of calibration for a real detector
A priori unknown real detector A priori unknown real detector Absolute and relative alignments, inactive material distributions Absolute and relative alignments, inactive material distributions
Estimate effect of distorted (real) detectorEstimate effect of distorted (real) detector Implement realistic assumptions for misalignment in simulationsImplement realistic assumptions for misalignment in simulations Small variations of inactive material thicknesses and locationsSmall variations of inactive material thicknesses and locations But use “perfect” calibration for reconstructionBut use “perfect” calibration for reconstruction
Change jet signalsChange jet signals Tower or clustersTower or clusters
E.g, change from reference calorimeter signalE.g, change from reference calorimeter signal Different jet finderDifferent jet finder
E.g., use kT instead of cone E.g., use kT instead of cone Different configurationDifferent configuration
E.g., use narrow jets (cone size 0.4) instead of wide jets (0.7)E.g., use narrow jets (cone size 0.4) instead of wide jets (0.7)
24P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Signal Linearity & Resolution
Response Response Linear within +/-1% after calibration applied Linear within +/-1% after calibration applied
for pT>100 GeVfor pT>100 GeV Clear improvement compared to basic signal Clear improvement compared to basic signal
scalescale Problems with low pT regimeProblems with low pT regime
ATLAS limit pT>20-40 GeV, depending on ATLAS limit pT>20-40 GeV, depending on luminosityluminosity
May be resolution bias – under studyMay be resolution bias – under study
ResolutionResolution Jet energy resolution clearly improved by Jet energy resolution clearly improved by
calibration as wellcalibration as well Slight dependence on calibration strategySlight dependence on calibration strategy
Close to required performanceClose to required performance
65%3%
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25P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Characterizes “real” detector jet Characterizes “real” detector jet response response Variation of response with directionVariation of response with direction Changing inactive material Changing inactive material
distributiondistribution Cracks between calorimeter Cracks between calorimeter
modulesmodules
Variations Variations No strong dependence on No strong dependence on
calorimeter signal definitioncalorimeter signal definition Towers/clustersTowers/clusters
ATLAS cone jet performs better in ATLAS cone jet performs better in crack region at low pT crack region at low pT
Signal Uniformity
narrow jetsnarrow jets
narrow jetsnarrow jets
Rel
ativ
e T
ower
Jet
Res
pon
sep T
(G
eV)
Clu
ster
-Tow
er D
iffe
ren
ce (
%)
η
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26P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Deviation From Signal Linearity
Estimated effect of a distorted detector Estimated effect of a distorted detector
Effect of detector distortion depends on jet size, calo signal choice, and kinematic domain
Effect of detector distortion depends on jet size, calo signal choice, and kinematic domain
ATLAS MC(preliminary)
rec,jett ruth,jet distorted
rec,jett ruth,jet ideal
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27P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Resolution Direction Dependence
Larger fluctuations for kT jets at Larger fluctuations for kT jets at low pTlow pT Vacuum effect for tower jets?Vacuum effect for tower jets? Less pronounced for cluster jetsLess pronounced for cluster jets
Noise suppression important in Noise suppression important in this domainthis domain
Very similar resolutions at high pTVery similar resolutions at high pT No strong dependence on jet No strong dependence on jet
definitiondefinition No strong dependence on No strong dependence on
calorimeter signal definitioncalorimeter signal definition No significant noise contribution No significant noise contribution
anymoreanymore
η
narrow jetsnarrow jets
2 2
cluster tower
for 0
for 0
E E
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28P. LochP. Loch
U of ArizonaU of ArizonaApril 15, 2010April 15, 2010
Different Final States: Quark Jets
tt qqb tt qqb
(high mulitplicity jets)SUSY
q
(high mulitplicity jets)SUSY
q
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