Jets In ATLAS Week of Jets FNAL, Aug. 24-28, 2009 Jets In ATLAS Peter Loch University of Arizona...

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Jets In ATLASJets In ATLAS

Peter LochPeter Loch

University of ArizonaUniversity of Arizona

Tucson, ArizonaTucson, Arizona

USAUSA

Peter LochPeter Loch

University of ArizonaUniversity of Arizona

Tucson, ArizonaTucson, Arizona

USAUSA

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2P. LochP. Loch

U of ArizonaU of Arizona

Aug. 27, 2009Aug. 27, 2009Preliminaries

This talkThis talk Focus on explanation of algorithms, methods, and Focus on explanation of algorithms, methods, and

measureable jet featuresmeasureable jet features Including some pointers to underlying principles, motivations, Including some pointers to underlying principles, motivations,

and expectationsand expectations Some reference to physicsSome reference to physics

Restricted to published or blessed materialRestricted to published or blessed material Most performance expectations from “The ATLAS Experiment Most performance expectations from “The ATLAS Experiment

at the Large Hadron Collider” (G.Aad et al., 2008 JINST 3 at the Large Hadron Collider” (G.Aad et al., 2008 JINST 3 S08003)S08003)

Most results shown >1 year oldMost results shown >1 year old Everything is based on simulationsEverything is based on simulations

Experiments may tell a (very?) different story in some casesExperiments may tell a (very?) different story in some cases LHC beam conditions used for most studies are not LHC beam conditions used for most studies are not

appropriate for first dataappropriate for first data Center of mass 14 TeVCenter of mass 14 TeV

Mostly a phase space limitation in the first data for basic jet performance studies

No pile-up effects included except where especially statedNo pile-up effects included except where especially stated

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3P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009Roadmap

1.1. Jets at LHCJets at LHCa.a. Where do they come from?Where do they come from?

Selected hadronic final statesSelected hadronic final states

b.b. Physics collision environmentPhysics collision environment Underlying event and pile-upUnderlying event and pile-up

2.2. Hadronic signals in ATLASHadronic signals in ATLASa.a. The ATLAS detectorThe ATLAS detector

Focus on calorimetersFocus on calorimeters General response issuesGeneral response issues

b.b. Signals for jet reconstructionSignals for jet reconstruction Unbiased and biased towersUnbiased and biased towers Topological clustersTopological clusters

3.3. Jet measurementJet measurementa.a. Jet input objectsJet input objects

TowersTowers Topological clustersTopological clusters Particles Particles

b.b. Jet reconstruction and calibrationJet reconstruction and calibration Reconstruction sequenceReconstruction sequence Calibration schemesCalibration schemes

4.4. Jet reconstruction performanceJet reconstruction performancea.a. QCD di-jetsQCD di-jetsb.b. Photon/z + jet(s)Photon/z + jet(s)c.c. W mass spectroscopyW mass spectroscopyd.d. Jet vertices and track jetsJet vertices and track jets

5.5. Conclusions & OutlookConclusions & Outlook

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4P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

1. Jets at LHC 1. Jets at LHC

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5P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009Where do Jets come from at LHC?

t bW jjj

t bW l jj

t bW jjj

t bW l jj

1.8 TeVs

14 TeVs

(TeV)Tp

inclusive jet cross-section

qq q q WW Hjj qq q q WW Hjj

2

0

nb

TeVT

d

d dp

Fragmentation of gluons and Fragmentation of gluons and (light) quarks in QCD (light) quarks in QCD scatteringscattering Most often observed interaction at Most often observed interaction at

LHCLHC

Decay of heavy Standard Decay of heavy Standard Model (SM) particles Model (SM) particles Prominent example:Prominent example:

Associated with particle Associated with particle production in Vector Boson production in Vector Boson Fusion (VBF)Fusion (VBF) E.g., HiggsE.g., Higgs

Decay of Beyond Standard Decay of Beyond Standard Model (BSM) particlesModel (BSM) particles E.g., SUSYE.g., SUSY

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6P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

t bW jjj

t bW l jj

t bW jjj

t bW l jj


top mass reconstruction


LHCLHC




Where do Jets come from at LHC?C

ER

N-O

PEN

-20

08

-02

0

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7P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009


LHCLHC




t bW jjj

t bW l jj

t bW jjj

t bW l jj



ER

N-O

PEN

-20

08

-02

0

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8P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009


LHCLHC




t bW jjj

t bW l jj

t bW jjj

t bW l jj


electrons or muons

jets

missing transverse

energy

,jets

,leptons

Te f Tjf T ppM p


ER

N-O

PEN

-20

08

-02

0

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9P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

Collisions of other partons in Collisions of other partons in the protons generating the the protons generating the signal interactionsignal interaction Unavoidable in hadron-hadron Unavoidable in hadron-hadron

collisionscollisions Independent soft to hard multi-Independent soft to hard multi-

parton interactions parton interactions No real first principle No real first principle calculationscalculations

Contains low pT (non-Contains low pT (non-pertubative) QCDpertubative) QCD

Tuning rather than calculationsTuning rather than calculations Activity shows some correlation Activity shows some correlation

with hard scattering (radiation)with hard scattering (radiation) pTmin, pTmax differencespTmin, pTmax differences

Typically tuned from data in Typically tuned from data in physics generatorsphysics generators

Carefully measured at Carefully measured at TevatronTevatron Phase space factor applied to Phase space factor applied to

LHC tune in absence of dataLHC tune in absence of data One of the first things to be One of the first things to be

measured at LHCmeasured at LHC

Underlying Event

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10P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

Δφ

“toward”|Δφ|<60°

“away”|Δφ|>120°

“transverse”60°<|Δφ|<120°

“transverse”60°<|Δφ|<120°

leading jet

Rick Field’s (CDF) view on di-Rick Field’s (CDF) view on di-jet eventsjet events










measured at LHCmeasured at LHCLook at activity (pT, # charged Look at activity (pT, # charged

tracks) as function of leading jet tracks) as function of leading jet pT in transverse regionpT in transverse region

Underlying Event

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11P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

CDF data (√s=1.8 TeV)CDF data (√s=1.8 TeV)

LHC prediction: x2.5 the activity measured at Tevatron!

pT leading jet (GeV)

Nu

mb

er

ch

arg

ed

tra

cks in

tra

nsvers

e r

eg

ion

CDF data: Phys.Rev, D, 65 (2002)

2ln

ln

s

s

PYTHIA

Model depending extrapolation to LHC:

for

for but both agree Tevatron/SppS

PHOJETdata!










measured at LHCmeasured at LHC

Underlying Event

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12P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009Multiple Proton Interactions

Expect ~<20> additional proton collisions at Expect ~<20> additional proton collisions at each bunch crossing at LHC design luminosityeach bunch crossing at LHC design luminosity Statistically independentStatistically independent

Actual number at given bunch crossing Poisson distributed Actual number at given bunch crossing Poisson distributed Mostly soft to semi-hard collisionsMostly soft to semi-hard collisions

Very similar dynamics as underlying eventVery similar dynamics as underlying event Generate 100’s-1000’s particles in addition to hard scatterGenerate 100’s-1000’s particles in addition to hard scatter

High occupancy in inner detector is experimentally High occupancy in inner detector is experimentally challengingchallenging

High ionization rate in calorimetersHigh ionization rate in calorimeters Signal collection time versus bunch crossing an issueSignal collection time versus bunch crossing an issue

Experimental handlesExperimental handles Energy flow and track distributions in minimum bias events Energy flow and track distributions in minimum bias events

Help to understand physics features of pile-up eventsHelp to understand physics features of pile-up events Feedback for modelersFeedback for modelers

Multiple primary verticesMultiple primary vertices Explicit reconstruction of MPVs indicates event-by-event pile-Explicit reconstruction of MPVs indicates event-by-event pile-

up activityup activity

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13P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009Why Is That Important?

Jet calibration requirements very stringentJet calibration requirements very stringent Systematic jet energy scale Systematic jet energy scale uncertainties to be extremely uncertainties to be extremely well controlledwell controlled

Top mass reconstructionTop mass reconstruction Relative jet energy resolution Relative jet energy resolution requirement requirement

Inclusive jet cross-sectionInclusive jet cross-section Di-quark mass spectra cut-off in SUSYDi-quark mass spectra cut-off in SUSY

Event topology plays a role at 1% level of Event topology plays a role at 1% level of precisionprecision Extra particle production due to event color flowExtra particle production due to event color flow

Color singlet (e.g., Color singlet (e.g., WW) vs color octet (e.g., gluon/quark) jet ) vs color octet (e.g., gluon/quark) jet sourcesource

Small and large angle gluon radiationSmall and large angle gluon radiation Quark/gluon jet differencesQuark/gluon jet differences

Control of underlying event and pile-up contributionsControl of underlying event and pile-up contributions

1 GeV 1%jetT

T jet

Em

m E

1 GeV 1%jetT

T jet

Em

m E

50%3% 3

(GeV)

100%5% 3

(GeV)

E

E

E

50%3% 3

(GeV)

100%5% 3

(GeV)

E

E

E

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14P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

2. Hadronic Signals in ATLAS2. Hadronic Signals in ATLAS

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15P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

Total weight : 7000 t

Overall length: 46 m

Overall diameter: 23 m

Magnetic field: 2T solenoid

+ toroid

The ATLAS Detector

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16P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

EM Endcap EMEC

EM Barrel EMB

Hadronic Endcap

ForwardTile Barrel

Tile Extended Barrel

The ATLAS Calorimeters

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17P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009ATLAS Calorimeter Summary

Non-compensating calorimetersNon-compensating calorimeters Electrons generate larger signal than pions depositing the same Electrons generate larger signal than pions depositing the same

energyenergy Typically Typically e/e/ππ ≈ ≈ 1.31.3

High particle stoppingHigh particle stoppingpower over wholepower over wholedetector acceptance detector acceptance ||ηη|<4.9|<4.9 ~26-35 X~26-35 X00 electromagnetic electromagnetic

calorimetrycalorimetry ~ 10 ~ 10 λλ total for hadrons total for hadrons

Hermetic coverageHermetic coverage No significant cracks in No significant cracks in

azimuthazimuth Non-pointing transition between barrel, endcap and forwardNon-pointing transition between barrel, endcap and forward

Small performance penalty for hadrons/jetsSmall performance penalty for hadrons/jets High granularityHigh granularity

6 (barrel)-7 (end-caps) longitudinal samplings6 (barrel)-7 (end-caps) longitudinal samplings ~200,000 independently read-out cells in total~200,000 independently read-out cells in total Pre-samplers in front of barrel and end-capPre-samplers in front of barrel and end-cap

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18P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

Signal history in Signal history in calorimeter increases calorimeter increases noisenoise Signal collection in ATLAS Signal collection in ATLAS

10-20 times slower than 10-20 times slower than bunch crossing rate (25 ns)bunch crossing rate (25 ns) Signal history effectively Signal history effectively

adds to noiseadds to noise Baseline suppressed by fast Baseline suppressed by fast

signal shapingsignal shaping Bi-polar shape with net 0 Bi-polar shape with net 0

integralintegral Noise has coherent Noise has coherent

charactercharacter Cell signals linked through Cell signals linked through

past shower developmentspast shower developments

Pile-Up in ATLAS (1)

Prog.Part.Nucl.Phys.60:484-551,2008

Et ~ 58 GeV

Et ~ 81 GeV

without pile-up

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19P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

Et ~ 58 GeV

Et ~ 81 GeV

with design luminosity pile-up



reading out (digitize) reading out (digitize) 5 samples sufficient!5 samples sufficient!

~450 ns @ 2mm LAr, 1 kV/mm

Cell signal shape in Cell signal shape in

ATLAS LAr Calorimeter ATLAS LAr Calorimeter

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20P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

34 2 110 cm sL 34 2 110 cm sL

8 GeV

0.4R

0.7R

18 GeV

0.1 0.1 R

( ) (GeV)TRMS p



Online digital filteringOnline digital filtering Explicit knowledge of Explicit knowledge of

physics pulse shape allows physics pulse shape allows precise reconstruction of precise reconstruction of amplitudeamplitude Needs linear filter Needs linear filter

coefficients and auto-coefficients and auto-correlation matrixcorrelation matrix

Suppresses noise wrt single Suppresses noise wrt single readingreading 1/√2 for 5 samples 1/√2 for 5 samples

First data issuesFirst data issues Pulse-shape and filtering Pulse-shape and filtering

works best at high works best at high ionization ratesionization rates Most complete area Most complete area

cancellation cancellation Initial bunch crossing Initial bunch crossing

50/75/450 ns introduce 50/75/450 ns introduce baselinebaseline Magnitudes depend on Magnitudes depend on

actual bunch spacingactual bunch spacing Increased noise also Increased noise also

possible for some possible for some configurationsconfigurations

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21P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009Basic Signal Scales in ATLAS

Cell signalsCell signals Raw data for physics from online system is amplitude, Raw data for physics from online system is amplitude,

time, filter quality, gain selectiontime, filter quality, gain selection Special readout configurations providing 5…32 samples Special readout configurations providing 5…32 samples

possible possible Cell signals are energy, time, quality, and gainCell signals are energy, time, quality, and gain

Energy scale is “electromagnetic” – determined by electron Energy scale is “electromagnetic” – determined by electron testbeams and simulationstestbeams and simulations

All electronic corrections are appliedAll electronic corrections are applied Signal efficiency corrections are applied Signal efficiency corrections are applied

Reduced signals due to HV problems etc.

Towers and clustersTowers and clusters Individual cell signals hard to useIndividual cell signals hard to use

Can be <0 due to noiseCan be <0 due to noise Hard to determine source of signal without Hard to determine source of signal without

context/neighbourhoodcontext/neighbourhood e/h > 1 required specific corrections for hadronic signals

Need to collect cell signals into larger objectsNeed to collect cell signals into larger objects Towers and clustersTowers and clusters

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22P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

Impose a regular grid view on Impose a regular grid view on eventevent ΔΔ××ΔφΔφ = 0.1×0.1 = 0.1×0.1 grid grid Motivated by particle Et flow in Motivated by particle Et flow in

hadron-hadronhadron-hadron collisionscollisions Well suited for trigger purposesWell suited for trigger purposes

Collect cells into tower gridCollect cells into tower grid Cells EM scale signals are summed Cells EM scale signals are summed

with geometrical weightswith geometrical weights Depend on cell area containment Depend on cell area containment

ratio ratio Weight = 1 for projective cells of Weight = 1 for projective cells of

equal or smaller than tower sizeequal or smaller than tower size Summing can be selectiveSumming can be selective

See jet input signal discussionSee jet input signal discussion Towers have massless four-Towers have massless four-

momentum representationmomentum representation Fixed direction given by geometrical Fixed direction given by geometrical

grid centergrid center

wcell

1.0

1.0

0.25 0.25

0.25 0.25

η

φ

projective cellsprojective cellsnon-projectivenon-projective

cellscells

0,

0

1 if

1 if

cell

cell cellA A

cellcell

cell

E w E

Aw

A

0,0

1 if

1 if

cell

cell cellA A

cellcell

cell

E w E

Aw

A

2 2 2

, , , , , x y z

x y z

E E p p p p

p p p p

2 2 2

, , , , , x y z

x y z

E E p p p p

p p p p

ATLAS Calorimeter Towers

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23P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

Signal extraction tool Signal extraction tool Attempt reconstruction of Attempt reconstruction of individual particle showersindividual particle showers

Reconstruct 3-dim clusters of Reconstruct 3-dim clusters of cells with correlated signals cells with correlated signals

Use shape of these clusters to Use shape of these clusters to locally calibrate themlocally calibrate them

Explore differences between Explore differences between electromagnetic and hadronic electromagnetic and hadronic shower development and select shower development and select best suited calibrationbest suited calibration

Supress noise with least bias on physics signalsSupress noise with least bias on physics signals Often less than 50% of all cells in an event with “real” signalOften less than 50% of all cells in an event with “real” signal

Some implications of jet environmentSome implications of jet environment Shower overlap cannot always be resolvedShower overlap cannot always be resolved

Clusters represent merged particle showers in dense jetsClusters represent merged particle showers in dense jets Clusters have varying sizes Clusters have varying sizes

No simple jet area as in case of towersNo simple jet area as in case of towers Clusters are mass-less 4-vectors (as towers)Clusters are mass-less 4-vectors (as towers)

No “artificial” mass contribution due to showeringNo “artificial” mass contribution due to showering Issues with IR safety at very small scale insignificantIssues with IR safety at very small scale insignificant

Pile-Up environment triggers split as well as mergePile-Up environment triggers split as well as merge Note that calorimeters themselves are not completely IR safeNote that calorimeters themselves are not completely IR safe

ATLAS Topological Cell Clusters (1)

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24P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

Cluster seedingCluster seeding Cluster seed is cell with significant signal above a primary thresholdCluster seed is cell with significant signal above a primary threshold

Cluster growth: direct neighboursCluster growth: direct neighbours Neighbouring cells (in 3-d) with cell signal significance above some basic Neighbouring cells (in 3-d) with cell signal significance above some basic

threshold are collectedthreshold are collected Cluster growth: control of expansionCluster growth: control of expansion

Collect neighbours of neighbours for cells above secondary signal Collect neighbours of neighbours for cells above secondary signal significance threshold significance threshold Secondary threshold lower than primary (seed) threshold Secondary threshold lower than primary (seed) threshold

Cluster splittingCluster splitting Analyze clusters for local signal maxima and split if more than one foundAnalyze clusters for local signal maxima and split if more than one found

Signal hill & valley analysis in 3-dSignal hill & valley analysis in 3-d Final “energy blob” can contain low signal cells Final “energy blob” can contain low signal cells

Cells survive due to significant neighbouring signalCells survive due to significant neighbouring signal Cells inside blob can have negative signalsCells inside blob can have negative signals

ATLAS also studies “TopoTowers”ATLAS also studies “TopoTowers” Use topological clustering as noise suppression tool onlyUse topological clustering as noise suppression tool only Distribute only energy of clustered cells onto tower gridDistribute only energy of clustered cells onto tower grid Motivated by DZero approachMotivated by DZero approach


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25P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

cluste

r candidate #1

cluste

r candidate #2

#3?


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26P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009ATLAS Local Hadronic Calibration

Local hadronic energy scale restoration depends on Local hadronic energy scale restoration depends on origin of calorimeter signalorigin of calorimeter signal Attempt to classify energy deposit as electromagnetic or hadronic Attempt to classify energy deposit as electromagnetic or hadronic

from the cluster signal and shapefrom the cluster signal and shape Allows to apply specific corrections and calibrationsAllows to apply specific corrections and calibrations

Local calibration approachLocal calibration approach Use topological cell clusters as signal base for a hadronic energy Use topological cell clusters as signal base for a hadronic energy

scalescale Recall cell signals need context for hadronic calibrationRecall cell signals need context for hadronic calibration

Basic concept is to reconstruct the locally deposited energy from Basic concept is to reconstruct the locally deposited energy from the cluster signal firstthe cluster signal first This is not the particle energyThis is not the particle energy

Additional corrections for energy losses with some correlation to Additional corrections for energy losses with some correlation to the cluster signals and shapes extend the local scopethe cluster signals and shapes extend the local scope True signal loss due to the noise suppression in the cluster algorithm True signal loss due to the noise suppression in the cluster algorithm

(still local)(still local) Dead material losses in front of, or between sensitive calorimeter Dead material losses in front of, or between sensitive calorimeter

volumes (larger scope than local deposit)volumes (larger scope than local deposit) After all corrections, the reconstructed energy is on After all corrections, the reconstructed energy is on

average the isolated particle energyaverage the isolated particle energy E.g., in a testbeamE.g., in a testbeam

But not the jet energy – missing curling tracks, dead material losses But not the jet energy – missing curling tracks, dead material losses without correlated cluster signal,… without correlated cluster signal,…

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Aug. 27, 2009Aug. 27, 2009ATLAS Local Scale Sequence

Electronic and readout effects Electronic and readout effects unfolded (nA->GeV calibration)unfolded (nA->GeV calibration)

3-d topological cell clustering 3-d topological cell clustering includes noise suppression and includes noise suppression and establishes basic calorimeter establishes basic calorimeter signal for further processingsignal for further processing

Cluster shape analysis provides Cluster shape analysis provides appropriate classification for appropriate classification for calibration and correctionscalibration and corrections

Cluster character depending Cluster character depending calibration (cell signal weighting for calibration (cell signal weighting for HAD, to be developed for EM?)HAD, to be developed for EM?)

Apply dead material corrections Apply dead material corrections specific for hadronic and specific for hadronic and electromagnetic clusters, resp.electromagnetic clusters, resp.

Apply specific out-of-cluster Apply specific out-of-cluster corrections for hadronic and corrections for hadronic and electromagnetic clusters, resp.electromagnetic clusters, resp.

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Aug. 27, 2009Aug. 27, 2009

3. Jet Input Objects 3. Jet Input Objects

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29P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009Jet Input Objects (1)

Calorimeter signal basedCalorimeter signal based Basic 0.1 x 0.1 calorimeter towersBasic 0.1 x 0.1 calorimeter towers

All cells (~190,000) projected into towersAll cells (~190,000) projected into towers Electromagnetic energy scale signalElectromagnetic energy scale signal No noise suppression but noise cancellation attemptNo noise suppression but noise cancellation attempt

Topological 0.1 x 0.1 calorimeter towersTopological 0.1 x 0.1 calorimeter towers Cells from topological clusters onlyCells from topological clusters only Electromagnetic energy scale signalElectromagnetic energy scale signal Noise suppression like for topological clustersNoise suppression like for topological clusters

Topological calorimeter cell clustersTopological calorimeter cell clusters Electromagnetic and local hadronic scale signalsElectromagnetic and local hadronic scale signals Noise suppressedNoise suppressed

From tracking detectorsFrom tracking detectors Reconstructed tracksReconstructed tracks

Charged particles onlyCharged particles only

From simulationFrom simulation Stable and interacting particles from generators reaching sensitive Stable and interacting particles from generators reaching sensitive

detectorsdetectors

Lab lifetime > 10 psLab lifetime > 10 ps Excludes neutrinos and muons from hard interactionExcludes neutrinos and muons from hard interaction

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Aug. 27, 2009Aug. 27, 2009Jet Input Objects (2)

from K. Perez, Columbia U.

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Aug. 27, 2009Aug. 27, 2009Jets in the ATLAS Calorimeters

S.D. Ellis, J. Huston, K. Hatakeyama, P. Loch, M. Toennesmann, Prog.Part.Nucl.Phys.60:484-551,2008

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Aug. 27, 2009Aug. 27, 2009

Sequential processSequential process Input signal selectionInput signal selection

Get the best signals out of your detector on a given signal scaleGet the best signals out of your detector on a given signal scale Preparation for jet findingPreparation for jet finding

Suppression/cancellation of “unphysical” signal objects with E<0 (due Suppression/cancellation of “unphysical” signal objects with E<0 (due to noise)to noise)

Possibly event ambiguity resolution (remove reconstructed electrons, Possibly event ambiguity resolution (remove reconstructed electrons, photons, taus,… from detector signal)photons, taus,… from detector signal)

Not done in ATLAS before jet reconstruction! Pre-clustering to speed up reconstruction (not needed anymore)Pre-clustering to speed up reconstruction (not needed anymore)

Jet findingJet finding Apply your jet finder of choiceApply your jet finder of choice

All implementations from FastJet and SISCone available Default is AntiKt4 with R = 0.4Default is AntiKt4 with R = 0.4

Reference is legacy ATLAS seeded fixed cone Narrow jets least affected by pile-up

Jet calibrationJet calibration Depending on detector input signal definition, jet finder choices, Depending on detector input signal definition, jet finder choices,

references…references… Default calibration uses cell weightsDefault calibration uses cell weights

Jet selectionJet selection Apply cuts on kinematics etc. to select jets of interest or significanceApply cuts on kinematics etc. to select jets of interest or significance

ObjectiveObjective Reconstruct particle level featuresReconstruct particle level features

Test models and extract physicsTest models and extract physics

ATLAS Jet Reconstruction

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Aug. 27, 2009Aug. 27, 2009Monte Carlo Jet Calibration

Typical Monte Carlo based normalizationTypical Monte Carlo based normalization Match particle level jets with detector jets in simple topologies Match particle level jets with detector jets in simple topologies

(fully simulated QCD di-jets)(fully simulated QCD di-jets) Use same specific jet definition for bothUse same specific jet definition for both Match defined by maximum angular distanceMatch defined by maximum angular distance

Can include isolation requirements

Determine calibration function parameters using truth particle jet Determine calibration function parameters using truth particle jet energy constraintenergy constraint Fit calibration parameters such that relative energy resolution is bestFit calibration parameters such that relative energy resolution is best

Include whole phase space into fit (flat in energy)

Correct residual non-linearities by jet energy scale correction Correct residual non-linearities by jet energy scale correction functionfunction Numerical inversion technique applied hereNumerical inversion technique applied here

Magnitudes of calibrations and corrections depend on Magnitudes of calibrations and corrections depend on signal choicessignal choices Electromagnetic energy scale signals require large corrections Electromagnetic energy scale signals require large corrections

while particle level or local hadronic signal have much less while particle level or local hadronic signal have much less correctionscorrections Effect on systematic errorsEffect on systematic errors

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34P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009ATLAS Jet Cell Weights

Cell signal weightingCell signal weighting Statistically determined cell signal Statistically determined cell signal weights try to compensate for weights try to compensate for e/h>1 in jet contexte/h>1 in jet context

Motivated by H1 cell weightingMotivated by H1 cell weighting High cell signal density indicatesHigh cell signal density indicates on average electromagnetic on average electromagnetic signal originsignal origin

Ideally weight = 1

Low cell signal indicates hadronic depositLow cell signal indicates hadronic deposit Weight > 1

Cell weights are determined as function of cell signal density and Cell weights are determined as function of cell signal density and locationlocation Use truth jet matching in fully simulated QCD di-jet events Use truth jet matching in fully simulated QCD di-jet events Crack regions not included in fitCrack regions not included in fit

Residual jet energy scale corrections – see next slidesResidual jet energy scale corrections – see next slides

2

2

1

( , )cells

rec true

jets trueN

rec i i i i i ii

E E

E

E w E V X E

2

2

1

( , )cells

rec true

jets trueN

rec i i i i i ii

E E

E

E w E V X E

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35P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009Cell Weight Calibration For Jets

Cell signal weighting Cell signal weighting functions do not restore functions do not restore jet energy scale for all jet energy scale for all jetsjets Crack regions not included Crack regions not included

in fitsin fits Only on jet context used for Only on jet context used for

fitting weightsfitting weights Cone jets with R=0.7Cone jets with R=0.7

Only one calorimeter signal Only one calorimeter signal definition used for weight definition used for weight fitsfits CaloTowers CaloTowers

Additional response Additional response corrections applied to corrections applied to restore linearityrestore linearity Non-optimal resolution for Non-optimal resolution for

other than reference jet other than reference jet samples can be expectedsamples can be expected

Changing physics Changing physics environment not environment not explicitly corrected explicitly corrected Absolute precision limitationAbsolute precision limitation

, 3 , 0

, , ,

( , ) , , ,

, , ,

calo calo calo calox y z

cell cell cell cellcell cell x y z

cells

calo caloDM t EMB t Tile

calo calo calo calo calo calo calo caloT x T y T z

E p p p

w X E p p p

E E

p p p p p p p p

, 3 , 0

, , ,

( , ) , , ,

, , ,

calo calo calo calox y z

cell cell cell cellcell cell x y z

cells

calo caloDM t EMB t Tile

calo calo calo calo calo calo calo caloT x T y T z

E p p p

w X E p p p

E E

p p p p p p p p

Jets

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36P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009ATLAS Cell Weight Calibration For Jets


in fitsin fits Only on jet context used for Only on jet context used for

fitting weightsfitting weights Cone jets with R=0.7Cone jets with R=0.7





, , ,

( , ) , , ,

final final final finalx y z

calo calo calo calo calo caloT x y z

E p p p

f p E p p p

, , ,

( , ) , , ,

final final final finalx y z

calo calo calo calo calo caloT x y z

E p p p

f p E p p p

Jets

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37P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009ATLAS Cell Weight Calibration For Jets


in fitsin fits Only one jet context used Only one jet context used

for fitting weightsfor fitting weights Cone jets with R=0.7Cone jets with R=0.7





Response for jets in ttbar(same jet finder as used fordetermination of calibrationfunctions with QCD events)

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38P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009Final Jet Energy Scale Calibration

Jet energy scale (JES) for first dataJet energy scale (JES) for first data Fully Monte Carlo based calibrations hard to validate quickly Fully Monte Carlo based calibrations hard to validate quickly

with initial datawith initial data Too many things have to be right, including underlying event Too many things have to be right, including underlying event

tunes, pile-up activity, etc.tunes, pile-up activity, etc. Mostly a generator issue in the beginningMostly a generator issue in the beginning

Need flat response and decent energy resolution for jets as Need flat response and decent energy resolution for jets as soon as possiblesoon as possible Data driven scenario a la DZero implementedData driven scenario a la DZero implemented

Additional jet by jet correctionsAdditional jet by jet corrections Interesting ideas to use all observable signal features for Interesting ideas to use all observable signal features for

jets to calibratejets to calibrate Geometrical momentsGeometrical moments Energy sharing in calorimetersEnergy sharing in calorimeters

Concerns about stability and MC dependence to be Concerns about stability and MC dependence to be understoodunderstood Can consider e.g. truncated moments using only prominent Can consider e.g. truncated moments using only prominent

constituents for stable signalconstituents for stable signal

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39P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009ATLAS JES Correction Model for First Data

optional

data driven

MC

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Aug. 27, 2009Aug. 27, 2009

4. Jet Reconstruction Performance4. Jet Reconstruction Performance

Jets

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41P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009Jet Performance Evaluations (1)

Jet performance evaluationJet performance evaluation Proof of success for each methodProof of success for each method

Closure tests applied to calibration data sourceClosure tests applied to calibration data source

Strong indications that one jet reconstruction approach is Strong indications that one jet reconstruction approach is not sufficientnot sufficient Evaluation needs to be extended to different final statesEvaluation needs to be extended to different final states Systematic errors and corrections for alternative jet finders Systematic errors and corrections for alternative jet finders

and configurations need to be evaluatedand configurations need to be evaluated

G. Salam, talk at ATLAS Hadronic Calibration Workshop, Tucson, Arizona, USA, March 2009

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42P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009Jet Performance Evaluations (2)

Jet signal linearity and resolutionJet signal linearity and resolution Closure tests for calibration determinationClosure tests for calibration determination

Ultimate precision and resolution for given method applied to Ultimate precision and resolution for given method applied to calibration samplecalibration sample

Response comparisons for different signal definitionsResponse comparisons for different signal definitions Need to reduce exploration phase spaceNeed to reduce exploration phase space Real data needed for final decisionReal data needed for final decision

E.g. towers vs clusters, calibration scheme

Jet Energy Scale (JES) stabilityJet Energy Scale (JES) stability Typically better than 2% with respect to signal linearity in Typically better than 2% with respect to signal linearity in

closure testsclosure tests Calibration approaches are stableCalibration approaches are stable

Signal uniformity within the same average deviationsSignal uniformity within the same average deviations Resolution goal is achievable with studied calibration Resolution goal is achievable with studied calibration

approachesapproaches See next slideSee next slide

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Aug. 27, 2009Aug. 27, 2009Jet Energy Resolution

98

63

26 98

63

26

1123728 299

111

41

1123728 299

111

41

(GeV) for 88 1

(GeV) for 1020 1

0

2

7 GeV

26 GeVt

t j t

jet

e

p E

p E

Very preliminary!Very preliminary!

Older evaluation!Older evaluation!

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44P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009Data Driven Evaluation

Photon+jet(s)Photon+jet(s) Well measured electromagnetic Well measured electromagnetic

system balances jet responsesystem balances jet response Central value theoretical Central value theoretical

uncertainty ~2% limits precisionuncertainty ~2% limits precision Due to photon isolation

requirements

But very good final state for But very good final state for evaluating calibrationsevaluating calibrations

Can test different correction levels Can test different correction levels in factorized calibrationsin factorized calibrations E.g., local hadronic calibration in E.g., local hadronic calibration in

ATLASATLAS

Limited pT reach for 1-2% Limited pT reach for 1-2% precisionprecision 25->300 GeV within 100 pb25->300 GeV within 100 pb-1-1

Z+jet(s)Z+jet(s) Similar idea, but less initial Similar idea, but less initial

statisticsstatistics Smaller reach but less backgroundSmaller reach but less background

Jets

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45P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009Data Driven Evaluation

Photon+jet(s)Photon+jet(s) Well measured electromagnetic Well measured electromagnetic

system balances jet responsesystem balances jet response Central value theoretical Central value theoretical

uncertainty ~2% limits precisionuncertainty ~2% limits precision Due to photon isolation

requirements

But very good final state for But very good final state for evaluating calibrationsevaluating calibrations

Can test different correction levels Can test different correction levels in factorized calibrationsin factorized calibrations E.g., local hadronic calibration in E.g., local hadronic calibration in

ATLASATLAS

Limited pT reach for 1-2% Limited pT reach for 1-2% precisionprecision 25->300 GeV within 100 pb-125->300 GeV within 100 pb-1

Z+jet(s)Z+jet(s) Similar idea, but less initial Similar idea, but less initial

statisticsstatistics Smaller reach but less backgroundSmaller reach but less background

Jets

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Aug. 27, 2009Aug. 27, 2009W Mass Spectroscopy

In-situ calibration In-situ calibration validation handlevalidation handle Precise reference in ttbar Precise reference in ttbar

eventsevents Hadronically decaying W-Hadronically decaying W-

bosonsbosons

Jet calibrations should Jet calibrations should reproduce W-massreproduce W-mass Note color singlet sourceNote color singlet source No color connection to rest of No color connection to rest of

collision – different underlying collision – different underlying event as QCDevent as QCD

Also only light quark jet Also only light quark jet referencereference

Expected to be sensitive to jet Expected to be sensitive to jet algorithmsalgorithms Narrow jets perform better – Narrow jets perform better –

as expectedas expected

raw signal

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47P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009Jets Not From Hard Scatter

Dangerous background for W+n jets cross-Dangerous background for W+n jets cross-sections etc.sections etc.

Lowest pT jet of final state can be faked or Lowest pT jet of final state can be faked or misinterpreted as coming from underlying event misinterpreted as coming from underlying event or multiple interactionsor multiple interactions

Extra jets from UE are hard to handleExtra jets from UE are hard to handle No real experimental indication of jet sourceNo real experimental indication of jet source

Some correlation with hard scattering?Some correlation with hard scattering? Jet area?Jet area? No separate vertexNo separate vertex

Jet-by-jet handle for multiple proton Jet-by-jet handle for multiple proton interactionsinteractions

Classic indicator for multiple interactions is Classic indicator for multiple interactions is number of reconstructed vertices in eventnumber of reconstructed vertices in event

Tevatron with RMS(z_vertex) ~ 30 cmTevatron with RMS(z_vertex) ~ 30 cm LHC RMS(z_vertex) ~ 8 cmLHC RMS(z_vertex) ~ 8 cm

If we can attach vertices to reconstructed jets, we If we can attach vertices to reconstructed jets, we can in principle identify jets not from hard can in principle identify jets not from hard scatteringscattering

Limited to pseudorapidities within 2.5!Limited to pseudorapidities within 2.5!

Track jetsTrack jets Find jets in recon-Find jets in reconstructed tracksstructed tracks

~60% of jet pT, ~60% of jet pT, with RMS ~0.3 – with RMS ~0.3 – not a good not a good kinematic estimatorkinematic estimator

Dedicated algorithmDedicated algorithm Cluster track jets in Cluster track jets in pseudo-rapidity, azimuth, pseudo-rapidity, azimuth, and delta(Zand delta(ZVertexVertex))

Match track and Match track and calorimeter jetcalorimeter jet

Also helps response!Also helps response!

Jets

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48P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

6. Conclusions & Outlook6. Conclusions & Outlook

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49P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009Conclusions

This was a mere snapshotThis was a mere snapshot Jet reconstruction at ATLAS deserves a bookJet reconstruction at ATLAS deserves a book

Complex environment, complex signals, lots of information Complex environment, complex signals, lots of information content in ATLAS (and CMS) eventscontent in ATLAS (and CMS) events

First data jet reconstruction and calibration First data jet reconstruction and calibration strategy in placestrategy in place Includes simulation and data inputIncludes simulation and data input

Emphasis on “data driven”Emphasis on “data driven” Expect to establish flat jet response for first physics quicklyExpect to establish flat jet response for first physics quickly

Discussion on how to establish initial systematic uncertainties Discussion on how to establish initial systematic uncertainties just startedjust started Some ideas exist but procedures need to be ironed out betterSome ideas exist but procedures need to be ironed out better Still on track for first useful collision dataStill on track for first useful collision data

We are looking beyond obvious jet performance We are looking beyond obvious jet performance variablesvariables Jet shapes are considered for refined JES calibrationJet shapes are considered for refined JES calibration

Jet-by-jet correctionsJet-by-jet corrections Experimental sensitivity to unfold jet substructure exploredExperimental sensitivity to unfold jet substructure explored

Needs more studies with real dataNeeds more studies with real data Discovery tool for boosted heavy particles!Discovery tool for boosted heavy particles!

We are waiting for collision data!We are waiting for collision data!

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Aug. 27, 2009Aug. 27, 2009

Some BackupSome Backup

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Aug. 27, 2009Aug. 27, 2009Electromagnetic Calorimetry

Highly segmented Highly segmented lead/liquid argon accordionlead/liquid argon accordion No azimuthal cracksNo azimuthal cracks 3 depth segments3 depth segments

+ pre-sampler (limited + pre-sampler (limited coverage)coverage)

Strip cells in 1Strip cells in 1stst layer layer Very high granularity in pseudo-Very high granularity in pseudo-

rapidity rapidity

Deep cells in 2Deep cells in 2ndnd layer layer High granularity in both High granularity in both

directionsdirections

Shallow cells in 3Shallow cells in 3rdrd layer layer

0.003 0.1

0.025 0.025

0.05 0.025

Electromagnetic BarrelElectromagnetic BarrelElectromagnetic BarrelElectromagnetic Barrel

Jets

In

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Week o

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52P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

Tile calorimeterTile calorimeter Iron/scintillator tiled readoutIron/scintillator tiled readout 3 depth segments3 depth segments

Quasi-projective readout cellsQuasi-projective readout cells First two layers:First two layers:

Third layerThird layer

Very fast light Very fast light

collectioncollection ~50 ns~50 ns Dual fiber Dual fiber

readout for each readout for each

channelchannel

0.1 0.1 0.1 0.1

0.2 0.1 0.2 0.1

Hadronic Calorimetry

Jets

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FN

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53P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

EndCap Calorimeters

0.025 0.025 2.5, middle layer

0.1 0.1 2.5 3.2

0.025 0.025 2.5, middle layer

0.1 0.1 2.5 3.2

0.1 0.1 2.5

0.2 0.2 2.5 3.2

0.1 0.1 2.5

0.2 0.2 2.5 3.2

Electromagnetic “Spanish Electromagnetic “Spanish Fan” accordionFan” accordion Highly segmented with up to Highly segmented with up to

three longitudinal segmentsthree longitudinal segments

Hadronic liquid Hadronic liquid argon/copper argon/copper calorimetercalorimeter Parallel plate Parallel plate

designdesign Four longitudinal Four longitudinal

segmentssegments Quasi-projective Quasi-projective

cellscells

Jets

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54P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

FCal1FCal1

FCal2FCal2

FCal3FCal3

Forward Calorimeters

Design featuresDesign features Compact absorbersCompact absorbers

Small showersSmall showers Tubular thin gap electrodesTubular thin gap electrodes

Suppress positive charge build-up Suppress positive charge build-up (Ar+) in high ionization rate (Ar+) in high ionization rate environmentenvironment

Stable calibrationStable calibration Rectangular non-projective readout Rectangular non-projective readout

cellscells

Electromagnetic FCal1Electromagnetic FCal1 Liquid argon/copperLiquid argon/copper

Gap ~260 Gap ~260 μμmm Hadronic FCal2Hadronic FCal2

Liquid argon/tungstenLiquid argon/tungsten Gap ~375 Gap ~375 μμmm

Hadronic FCal3Hadronic FCal3 Liquid argon/tungstenLiquid argon/tungsten

Gap ~500 Gap ~500 μμmm

0.2 0.2 0.2 0.2

Jets

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55P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

Tower Building(Δη×Δφ=0.1×0.1, non-discriminant)

CaloCells(em scale)

CaloTowers(em scale)

Calorimeter Jets(em scale)

Jet Finding(cone R=0.7,0.4; kt)

Jet Based Hadronic Calibration(“H1-style” cell weighting in jets etc.)

Calorimeter Jets(fully calibrated had scale)

Physics Jets(calibrated to particle level)

Jet Energy Scale Corrections(noise, pile-up, algorithm effects, etc.)

Refined Physics Jet(calibrated to interaction level)

In-situ Calibration(underlying event, physics environment, etc.)

ProtoJets(E>0,em scale)

Tower Noise Suppression(cancel E<0 towers by re-summation)

Sum up electromagnetic scale calorimeter cell signals Sum up electromagnetic scale calorimeter cell signals into towersinto towers Fixed grid of Fixed grid of ΔΔηη x x ΔΔφφ = 0.1 x 0.1 = 0.1 x 0.1 Non-discriminatory, no cell suppressionNon-discriminatory, no cell suppression Works well with pointing readout geometriesWorks well with pointing readout geometries

Larger cells split their signal between towers according to the overlap Larger cells split their signal between towers according to the overlap area fractionarea fraction

Tower noise suppressionTower noise suppression Some towers have net negative signalsSome towers have net negative signals Apply “nearest neighbour tower recombination”Apply “nearest neighbour tower recombination”

Combine negative signal tower(s) with nearby positive signal towers Combine negative signal tower(s) with nearby positive signal towers until sum of signals > 0until sum of signals > 0

Remove towers with no nearby neighboursRemove towers with no nearby neighbours

Towers are “massless” pseudo-particlesTowers are “massless” pseudo-particles Find jetsFind jets

Note: towers have signal on electromagnetic energy scaleNote: towers have signal on electromagnetic energy scale Calibrate jetsCalibrate jets

Retrieve calorimeter cell signals in jetRetrieve calorimeter cell signals in jet Apply signal weighting functions to these signalsApply signal weighting functions to these signals Recalculate jet kinematics using these cell signalsRecalculate jet kinematics using these cell signals

Note: there are cells with negative signals!Note: there are cells with negative signals!

Apply final correctionsApply final corrections

CaloTower Jets

Jets

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56P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

Topological Clustering(includes noise suppression)

CaloCells(em scale)


Cluster Classification(identify em type clusters)


Out Of Cluster Corrections(hadronic & electromagnetic)Jet Based Hadronic Calibration

(“H1-style” cell weighting in jets etc.)




In-situ Calibration(underlying event,

physics environment, etc.)

Hadronic Cluster Calibration(apply cell signal weighting)

Dead Material Correction(hadronic & eleectromagentic)

CaloClusters(em scale, classified)

CaloClusters(locally calibrated had scale)

CaloClusters(hadronic scale)

CaloClusters(had scale+DM)

Calorimeter Jets(partly calibrated/corrected)


CaloClusters(em scale)



TopoCluster Jets

Jets

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57P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

Tower Building(Δη×Δφ=0.1×0.1, non-discriminant)

CaloCells(em scale, selected)

CaloTowers(em scale)



Jet Based Hadronic Calibration(“H1-style” cell weighting in jets etc.)





In-situ Calibration(underlying event,

physics environment, etc.)

Topological Clustering(includes noise suppression)

CaloCells(em scale)

CaloClusters(em scale)

Extract Cells In Clusters(excludes noisy cells)

Apply noise Apply noise suppression to tower suppression to tower jetsjets Topological clustering is Topological clustering is

used as a noise used as a noise suppression tool onlysuppression tool only

Similar to DZero Similar to DZero approachapproach

New implementationNew implementation Only in ESD context so Only in ESD context so

farfar Working on schema to Working on schema to

bring these jets into the bring these jets into the AODAOD Including constituentsIncluding constituents

Allows comparisons Allows comparisons for tower and cluster for tower and cluster jets with similar jets with similar noise contributionnoise contribution Should produce rather Should produce rather

similar jets than tower similar jets than tower jets at better jets at better resolutionresolution

Less towers per jetLess towers per jet

TopoTower Jets

CERN-OPEN-2008-020

Jets

In

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58P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009Calibration Flow

Electromagnetic Scale J et

Electromagnetic Scale Cells

Apply WeightsDead Material

Correction

Recombine

Final Energy Scale J et

Apply Final Correction

cells in EMB3/Tile0all cells

Retreive Cells

Local Hadronic Scale J et

Final Energy Scale J et

Apply Final Correction

Lots of work in calorimeter domain!

Jets

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59P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009Data Driven JES Corrections (1)

PileUp subtractionPileUp subtraction Goal:Goal:

Correct in-time and residual out-of-time Correct in-time and residual out-of-time pile-up contribution to a jet on averagepile-up contribution to a jet on average

Tools:Tools: Zero bias (random) events, minimum bias Zero bias (random) events, minimum bias

eventsevents

Measurement:Measurement: Et density in Et density in ΔΔ××ΔφΔφ bins as function of bins as function of # vertices# vertices TopoCluster feature (size, average TopoCluster feature (size, average energy as function of depth) changesenergy as function of depth) changes as function of # vertices as function of # vertices

Remarks:Remarks: Uses expectations from the average Et flow Uses expectations from the average Et flow

for a given instantaneous luminosityfor a given instantaneous luminosity Instantaneous luminosity is measured by Instantaneous luminosity is measured by

the # vertices in the eventthe # vertices in the event Requires measure of jet size (AntiKt Requires measure of jet size (AntiKt

advantage)advantage)

Concerns:Concerns: Stable and safe determination of averageStable and safe determination of average

UEUE TE UEUE TE

coshUEoffset UE jet jetE A coshUEoffset UE jet jetE A

DD

DD

Determination of the Absolute Jet Energy Scale in the D0 Calorimeters. NIM A424, 352 (1999)

Note that magnitude of correction depends on

calorimeter signal processing!

Note that magnitude of correction depends on

calorimeter signal processing!

Jets

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60P. LochP. Loch



Absolute responseAbsolute response Goal:Goal:

Correct for energy (pT) dependent jet responseCorrect for energy (pT) dependent jet response

Tools: Tools: Direct photons, Z+jet(s),…Direct photons, Z+jet(s),…

Measurement:Measurement: pT balance of well calibrated system (photon, Z) pT balance of well calibrated system (photon, Z) against jet in central regionagainst jet in central region

Remarks:Remarks: Usually uses central reference and central jets (region of flat reponse)Usually uses central reference and central jets (region of flat reponse)

Concerns:Concerns: Limit in precision and estimates for systematics w/o well understood Limit in precision and estimates for systematics w/o well understood

simulations not clearsimulations not clear

t

jett t

pt

p pf

p

t

jett t

pt

p pf

p

Jets

In

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61P. LochP. Loch



Direction response correctionsDirection response corrections Goal:Goal:

Equalize response as function of jet Equalize response as function of jet (pseudo)rapidity(pseudo)rapidity

Tools:Tools: QCD di-jetsQCD di-jets Direct photonsDirect photons

Measurement:Measurement: Di-jet pT balance uses Di-jet pT balance uses reference jet in well calibratedreference jet in well calibrated (central) region to correct (central) region to correct second jet further awaysecond jet further away Measure hadronic response Measure hadronic response variations as function of the jet variations as function of the jet direction with the missing Et direction with the missing Et projection fraction (MPF) method projection fraction (MPF) method

Remarks:Remarks: MPF only needs jet for direction MPF only needs jet for direction

referencereference Bi-sector in di-jet balance explores Bi-sector in di-jet balance explores

different sensitivitiesdifferent sensitivities Concerns:Concerns:

MC quality for systematic uncertaunty MC quality for systematic uncertaunty evaluationevaluation

Very different (jet) energy scales Very different (jet) energy scales between reference and probed jetbetween reference and probed jet

uncalibrated

calo signals

calot t

tjetcalo

t

p p

pR

p

calo signals

calot t

tjetcalo

t

p p

pR

p

Jets

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62P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009Jet Mass Sensitivity

change o

f m

ass

log10(least biased reconstructed mass/GeV)

QCD kT jets, D = 0.6

ATLAS MC(preliminary)

Jets

In

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63P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009

We expected clusters to represent We expected clusters to represent individual particlesindividual particles Cannot be perfect in busy jet Cannot be perfect in busy jet

environment!environment! Shower overlap in finite calorimeter Shower overlap in finite calorimeter

granularitygranularity

Some resolution power, thoughSome resolution power, though Much better than for tower jets!Much better than for tower jets!

~1.6:1 particles:clusters in central ~1.6:1 particles:clusters in central regionregion This is an average estimator subject to This is an average estimator subject to

large fluctuationslarge fluctuations

~1:1 in endcap region~1:1 in endcap region Best match of readout granularity, Best match of readout granularity,

shower size and jet particle energy flowshower size and jet particle energy flow Happy coincidence, not a design feature Happy coincidence, not a design feature

of the ATLAS calorimeter!of the ATLAS calorimeter!

Jet CompositionS.D

. Ellis e

t al., P

rog.P

art.N

ucl.P

hys.6

0:4

84

-55

1,2

00

8

Jets

In

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64P. LochP. Loch


Aug. 27, 2009Aug. 27, 2009Jet Substructure Mass too complex?Mass too complex?

Can be too sensitive to small Can be too sensitive to small signals in jetssignals in jets UE, pile-up, other noiseUE, pile-up, other noise

Use YSplitter to detect Use YSplitter to detect substructuresubstructure Determines scale y for splitting Determines scale y for splitting

a giving jet into 2,3,… subjects, a giving jet into 2,3,… subjects, as determined by yas determined by ycutcut, from, from

More stable as only significant More stable as only significant constituents are used ?constituents are used ?

At least additional information At least additional information to massto mass

Other option:Other option: Look at mass of 2…n hardest Look at mass of 2…n hardest

constituents (Ben Lillie,ANL) constituents (Ben Lillie,ANL)

jetcut Ty y p

Not very sensitive to calorimeter signal details!

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Jets In ATLAS Week of Jets FNAL, Aug. 24-28, 2009 Jets In ATLAS Peter Loch University of Arizona...

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