Jet Reconstruction in ATLAS Peter Loch University of Arizona Tucson, Arizona, USA Peter Loch...

Jet Reconstruction in Jet Reconstruction in ATLASATLAS

Jet Reconstruction in Jet Reconstruction in ATLASATLASPeter LochPeter Loch

University of ArizonaUniversity of Arizona

Tucson, Arizona, USATucson, Arizona, USA

Peter LochPeter Loch

University of ArizonaUniversity of Arizona

Tucson, Arizona, USATucson, Arizona, USA

e-mail: loch-at-physics.arizona.edue-mail: loch-at-physics.arizona.edu

mailto:[email protected]?subject=Ecole%20de%20Gif%202007%20question

SeminarSeminar

October 31, 2007October 31, 2007

RALRAL


University of University of ArizonaArizona

OutlineOutlineOutlineOutline

Jets at LHCJets at LHCBrief overview on sources for jets and jet features at LHCBrief overview on sources for jets and jet features at LHC

Physics environment: Underlying Event and Pile-upPhysics environment: Underlying Event and Pile-up

Jet reconstruction in ATLASJet reconstruction in ATLASJet findersJet finders

Tower and cluster jetsTower and cluster jets

Jet calibration strategiesJet calibration strategies

In-situ calibrationIn-situ calibration

More from jets at LHCMore from jets at LHCJet reconstruction performanceJet reconstruction performance

Mass reconstruction and jet substructure analysisMass reconstruction and jet substructure analysis

Jet shapesJet shapes

Summary & OutlookSummary & Outlook

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Jets at LHCJets at LHCJets at LHCJets at LHCNew kinematic regime for jet New kinematic regime for jet physicsphysics

Jets can be much harderJets can be much harderJets get more narrow in general Jets get more narrow in general (kinematic effect ~(kinematic effect ~ααss))Higher energies to be contained Higher energies to be contained in calorimetersin calorimeters

Jet reconstruction Jet reconstruction challengingchallenging

Physics requirements typically Physics requirements typically 1% jet energy scale uncertainty1% jet energy scale uncertainty

top mass measurement in ttbar top mass measurement in ttbar LHC is a top factory!

hadronic final states in at the end hadronic final states in at the end of long decay chains in SUSYof long decay chains in SUSY

Quality takes timeQuality takes timePrevious experiments needed up Previous experiments needed up to 10 years of data taking to go to 10 years of data taking to go from ~4% down to ~1%from ~4% down to ~1%Can often not be achieved for all Can often not be achieved for all kinds of jets and in all physics kinds of jets and in all physics environmentsenvironments

W. Stirling, LHCC Workshop “Theory of LHC Processes” (1998)*annotation from J. Huston, Talk @ ATLAS Standard Model WG Meeting (Feb. 2004)

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Jets from QCD Jets from QCD ProcessesProcesses

Jets from QCD Jets from QCD ProcessesProcesses

Jets at low pT most likely Jets at low pT most likely produced by gluon fusionproduced by gluon fusion

Large phase space for radiationLarge phase space for radiationExpectation are multi-jet final states Expectation are multi-jet final states even for 2even for 2→→2 processes2 processes

More likely quark jets at higher More likely quark jets at higher pTpT

Less radiation (Sudakov Less radiation (Sudakov suppression)suppression)Less jets in eventsLess jets in eventsNarrower jets (again)Narrower jets (again)

Large kinematic rangeLarge kinematic rangepT range 10-5000 GeV/cpT range 10-5000 GeV/cDi-jet mass reach several TeV/cDi-jet mass reach several TeV/c22

Multitude of jet flavoursMultitude of jet flavoursExpect corresponding variety of jet Expect corresponding variety of jet shapes with possibly specific shapes with possibly specific calibrations!calibrations!

s = 1.8TeV

s =14 TeV

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Physics Environments @ Physics Environments @ LHCLHCPhysics Environments @ Physics Environments @ LHCLHC

Underlying eventUnderlying eventRefers to multiple interactions Refers to multiple interactions between the two colliding between the two colliding protonsprotonsTypically correlated with hard Typically correlated with hard scatterscatter

Increased activity Increased activity compared to Tevatroncompared to Tevatron

more phase spacemore phase space

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)

Num

ber

char

ged

trac

ks in

tra

nsve

rse

regi

on

A.Moraes, HERA-LHC Workshop,DESY, March 2007

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

Δφ

“toward”|Δφ|<60°

“away”|Δφ|>120°

“transverse”60°<|Δφ|<120°

“transverse”60°<|Δφ|<120°

leading jet

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

independent of independent of luminosity luminosity →→

present at day 1 at present at day 1 at LHC!LHC!

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Pile-upPile-upPile-upPile-upLarge pp total cross-section Large pp total cross-section (~75mb)(~75mb)

~23 “minimum bias” (soft to medium ~23 “minimum bias” (soft to medium hard) collisions between protons in the hard) collisions between protons in the same bunch in addition to triggered same bunch in addition to triggered hard scatterhard scatter

@ 10@ 103434 cm cm-2-2 s s-1-1 Poisson distributedPoisson distributed

Similar dynamics as UESimilar dynamics as UEStatistically independent Statistically independent

No correlation to hard scatter!No correlation to hard scatter!Generate lots of additional particles in Generate lots of additional particles in addition to the underlying eventaddition to the underlying event

~370 particles/unit rapidity per bunch ~370 particles/unit rapidity per bunch crossing (3700 within ATLAS)crossing (3700 within ATLAS)~1,800 charged tracks in ATLAS/bunch ~1,800 charged tracks in ATLAS/bunch crossingcrossing

High crossing rate at LHC (40 High crossing rate at LHC (40 MHz)MHz)

Calorimeter signals typically to slowCalorimeter signals typically to slowShort signal shaping, bi-polar shaping Short signal shaping, bi-polar shaping function (ATLAS)function (ATLAS)

Long signal history (~500-600 ns) Long signal history (~500-600 ns) generates “out-of-time” pile-upgenerates “out-of-time” pile-up

Canceling area Canceling area → → integrated effect 0integrated effect 0Careful, only true in limit of continuous Careful, only true in limit of continuous collisionscollisions

Can be treated as noise in calorimeterCan be treated as noise in calorimeterAsymmetric!Asymmetric!

Et ~ 58 GeV

Et ~ 81 GeV

no pile-up added

LHC design luminosity pile-up added

P. S

avard et al., AT

LAS

-CA

L-NO

084/1996

R = 0.7

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Experimenter’s View on JetsExperimenter’s View on JetsExperimenter’s View on JetsExperimenter’s View on Jets

physics reaction of interest (interaction or parton level)

lost soft tracks due to magnetic field

added tracks from underlying event

jet reconstruction algorithm efficiency

detector response characteristics (e/h ≠ 1)

electronic noise

dead material losses (front, cracks, transitions…)

pile-up noise from (off- and in-time) bunch crossings

detector signal inefficiencies (dead channels, HV…)

longitudinal energy leakage

calo signal definition (clustering, noise suppression ,…)

jet reconstruction algorithm efficiency

added tracks from in-time (same trigger) pile-up event

We like to factorize the calibration and corrections dealing with We like to factorize the calibration and corrections dealing with these effects as much as possible!these effects as much as possible!

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Theoretical Requirements for Jet Theoretical Requirements for Jet FindersFinders

Theoretical Requirements for Jet Theoretical Requirements for Jet FindersFinders

Infrared safetyInfrared safetyAbsence of additional Absence of additional radiation splits jetsradiation splits jets

Presence of radiation Presence of radiation merges jetsmerges jets

Collinear safetyCollinear safetySplit seedsSplit seeds

infrared sensitivity(soft gluon radiation merges jets)

collinear sensitivity (2)(signal split into two towers below threshold)

collinear sensitivity (1)(sensitive to Et ordering of seeds)

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Experimental Requirements for Jet Experimental Requirements for Jet FindersFinders

Experimental Requirements for Jet Experimental Requirements for Jet FindersFinders

Detector technology independenceDetector technology independenceMinimal contributions to spatial and energy resolutionMinimal contributions to spatial and energy resolutionInsignificant effects of detector environmentInsignificant effects of detector environment

NoiseNoiseDead materialDead materialCracks Cracks

Easy to calibrateEasy to calibrateWell…Well…

Environment independenceEnvironment independenceStability with changing luminosityStability with changing luminosityIdentify all physically interesting jets from energetic partons in Identify all physically interesting jets from energetic partons in pertubative QCD (pQCD)pertubative QCD (pQCD)High reconstruction efficiencyHigh reconstruction efficiency

ImplementationImplementationFully specifiedFully specified

All selections and other configurations knownAll selections and other configurations knownEfficient use of computing sourcesEfficient use of computing sources

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Popular Jet Algorithms in ATLASPopular Jet Algorithms in ATLASPopular Jet Algorithms in ATLASPopular Jet Algorithms in ATLASSeeded coneSeeded cone

Place cone with radius R Place cone with radius R around seedaround seed

pT > 1 GeVpT > 1 GeV

Collect all particles in coneCollect all particles in cone

Re-calculate energy and Re-calculate energy and direction of conedirection of cone

4-momentum recombination4-momentum recombination

Find more particle in new Find more particle in new conecone

Stop until no more particles to Stop until no more particles to be foundbe found

Stable solutionStable solution

Particles can be shared Particles can be shared between jets between jets

Is not infrared safeIs not infrared safeNeeds split & merge (50% Needs split & merge (50% threshold)threshold)

May miss signficant energyMay miss signficant energyDark jetsDark jets

Recursive recombination (kT)Recursive recombination (kT)Calculate for all particles Calculate for all particles ii and and pairs pairs ij ij ::

Combine any two pairs to jet if:Combine any two pairs to jet if:

Else remove Else remove ii from list from listIs a jetIs a jet

Calculate new combinationsCalculate new combinationsStop when all particles declared Stop when all particles declared jetsjets

Each particle is part of one jet Each particle is part of one jet only (exclusive assignment)only (exclusive assignment)

Infrared safeInfrared safe

22 2, , 2

2 22 2, , 2

2

min( , )

min( , )

ijij t i t j

ij ijt i t j

i i

Rd p p

D

yp p

D

d p

ij id d

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Jet Finders in ATLASJet Finders in ATLASJet Finders in ATLASJet Finders in ATLASAlternative applications:Alternative applications:

CDF mid-point, Cambridge/Aachen CDF mid-point, Cambridge/Aachen recursive recombination (0recursive recombination (0thth order kT), order kT), “optimal jet finder” (event shape fit)“optimal jet finder” (event shape fit)More options: move to More options: move to FastJetFastJet libraries libraries

CMS, theoryCMS, theory

No universal configuration or jet No universal configuration or jet finderfinder

Narrow jets Narrow jets W->jj in ttbar, some SUSYW->jj in ttbar, some SUSY

Wider jetsWider jetsInclusive jet cross-section, QCD Inclusive jet cross-section, QCD

N.G

od

bh

an

e, Je

tRec

Jun

e 2

00

6

AlgorithmAlgorithm RRconecone DD ClientsClients

Seeded ConeSeeded ConeEtSeed = 1 GeV, fEtSeed = 1 GeV, fS/MS/M = 0.5 = 0.5

0.40.4 W mass W mass spectroscopyspectroscopy, top , top physics, physics, SUSYSUSY

Kt (FastKt)Kt (FastKt) 0.40.4

Seeded ConeSeeded ConeEtSeed = 1 GeV, fEtSeed = 1 GeV, fS/MS/M = 0.5 = 0.5

0.70.7 QCD, jet QCD, jet cross-cross-sectionssectionsKt (FastKt)Kt (FastKt) 0.60.6 P.-A. Delsart, June 2006

mW

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The ATLAS DetectorThe ATLAS DetectorThe ATLAS DetectorThe ATLAS Detector

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ATLAS CalorimetersATLAS CalorimetersATLAS CalorimetersATLAS Calorimeters

Tile CalorimetersTile Calorimeters

Electromagnetic Liquid Argon

Calorimeters

Electromagnetic Liquid Argon

Calorimeters

Hadronic Liquid Argon EndCap CalorimetersHadronic Liquid Argon EndCap Calorimeters

Forward Liquid Argon Calorimeters

Forward Liquid Argon Calorimeters

Electromagnetic Calorimeters: Liquid Argon/Pb accordion structure; highly granular readout (~170,000 channels); 0.0025 ≤ Δη ≤ 0.05, 0.025 ≤ Δφ ≤ 0.1; 2-3 longitudinal samplings; ~24-26 X0 deep covers |η|<3.2, presampler up to |η|<1.8;

Central Hadronic Calorimeters Scintillator/Fe in tiled readout; Δη x Δφ = 0.1 x 0.1 3 longitudinal samplings, covers |η|<1.7;

EndCap Hadronic Calorimeters Liquid Argon/Cu parallel plate absorber structure; Δη x Δφ = 0.1 x 0.1 (1.5<|η|<2.5), Δη x Δφ = 0.2 x 0.2 (2.5<|η|<3.2); 4 samplings;

Forward Calorimeters Liquid Argon/Cu or W absorbers with tubular electrodes in non-projective geometry; Δη x Δφ ≈ 0.2 x 0.2 (3.2<|η|<4.9) 3 samplings;

η=1.475

η=1.8

η=3.2

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ATLAS Calorimeter DetailsATLAS Calorimeter DetailsATLAS Calorimeter DetailsATLAS Calorimeter Details

FCal1

FCal2

FCal3

Cryostat walls(warm/cold)

to interactionvertex

p from LHC

Hadronic EndCap

(2 wheels)

ElectromagneticEndCap

Cu Shielding

Electromagnetic Barrel Module

total ~200,000 channels, with hadronic coverage ~10 absorption lengths in full acceptance (|η|<5) and a typical level of non-compensation e/h≈1.3-1.6;

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Calorimeter Signals: Calorimeter Signals: TowersTowersCalorimeter Signals: Calorimeter Signals: TowersTowers

Imposes regular grid view Imposes regular grid view on eventon event

ΔηΔη××ΔφΔφ = 0.1×0.1 = 0.1×0.1

Motivated by event EMotivated by event ETT flow flowNatural for trigger!Natural for trigger!

Calorimeter cell signals Calorimeter cell signals are summed up in tower are summed up in tower binsbins

No cell selection, all cells are No cell selection, all cells are includedincluded

Indiscriminatory signal sum Indiscriminatory signal sum includes cells without any includes cells without any true signal at alltrue signal at all

Sum typically includes Sum typically includes geometrical weightgeometrical weight

Towers have fixed Towers have fixed directiondirection

Massless four-momentum Massless four-momentum representationrepresentation

2

2cell

cell

cell cell

cellcell

E w E

Aw

2

2cell

cell

cell cell

cellcell

E w E

Aw

wcell

1.0

1.0

0.25 0.25

0.25 0.25

η

φ

wcell

1.0

1.0

0.25 0.25

0.25 0.25

η

φ

, , , , ,T x y zE E p p p p

projective cellsprojective cellsnon-projectivenon-projective

cellscells

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Calorimeter Signals: Calorimeter Signals:

Topological ClustersTopological Clusters

Calorimeter Signals: Calorimeter Signals:

Topological ClustersTopological ClustersAttempt to reconstruct particle Attempt to reconstruct particle showersshowers

Establish local signal correlations Establish local signal correlations in (neighbouring) cellsin (neighbouring) cells““energy blob” in 3-denergy blob” in 3-d

Growing volume algorithm Growing volume algorithm using seeds and signal using seeds and signal thresholdsthresholds

Primary seeds start clusterPrimary seeds start clusterSecondary seeds among Secondary seeds among neighbours control growthneighbours control growthBasic cell selection threshold Basic cell selection threshold suppresses noisesuppresses noiseAll thresholds use signal-over-noise All thresholds use signal-over-noise rather than signalrather than signal

Signal significance is above a Signal significance is above a constant (but complex) thresholdconstant (but complex) thresholdNote: smallest reliably measurable Note: smallest reliably measurable energy is changing with noise!energy is changing with noise!Avoids regional energy thresholds Avoids regional energy thresholds (lots of tuning)(lots of tuning)Uses experimentally accessible Uses experimentally accessible informationinformationGets the best out of the Gets the best out of the calorimeter! calorimeter!

Pile-up Noise in Calorimeter Cells S. M

enke, AT

LAS

Physics W

orkshop 07/2005

34 2 110 cm sL

Electronic Noise in Calorimeter Cells S. Menke, A

TLA

S P

hysics Workshop 07/2005

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Principle of Topological ClusteringPrinciple of Topological ClusteringPrinciple of Topological ClusteringPrinciple of Topological Clustering

η

φ

η

φ 1 1

111

1

1 1 1 1

1

1

1111

1

1

1

1 1 1

1

1

1

1

11111

1

1

1

11

1

1

2 2

22

2

2 2 2

2

2

2

2

2

2

2

2

2

2

2

2

2 2

2

3 3

333

3

3 3 3

3

3

3 3 3

4

4

4 4

4414

14

14

14 4

552

5 54

1 54

52

52

51

51

51

4cellnoisecell

E

2cellnoisecell

E

0cellnoisecell

E

Primary seeds

Secondary seeds

Basic threshold

Cluster splitting introduces geometrical weights!Cluster splitting introduces geometrical weights!

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Calorimeter Signals: It’s All In The Calorimeter Signals: It’s All In The Pictures…Pictures…

Calorimeter Signals: It’s All In The Calorimeter Signals: It’s All In The Pictures…Pictures…

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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)

Tower Jets in ATLASTower Jets in ATLASTower Jets in ATLASTower Jets in ATLASSum up electromagnetic scale calorimeter cell Sum up electromagnetic scale calorimeter cell signals into towerssignals into towers

Fixed grid of Fixed grid of ΔΔηη x x ΔΔφφ = 0.1 x 0.1 = 0.1 x 0.1Non-discriminatory, no cell suppressionNon-discriminatory, no cell suppressionWorks well with pointing readout geometriesWorks well with pointing readout geometries

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

Tower noise suppressionTower noise suppressionSome towers have net negative signalsSome towers have net negative signalsApply “nearest neighbour tower recombination”Apply “nearest neighbour tower recombination”

Combine negative signal tower(s) with nearby positive signal Combine negative signal tower(s) with nearby positive signal towers until sum of signals > 0towers until sum of signals > 0 Remove towers with no nearby neighboursRemove towers with no nearby neighbours

Towers are “massless” pseudo-particlesTowers are “massless” pseudo-particlesFind jetsFind jets

Note: towers have signal on electromagnetic energy scaleNote: towers have signal on electromagnetic energy scaleCalibrate jetsCalibrate jets

Retrieve calorimeter cell signals in jetRetrieve calorimeter cell signals in jetApply signal weighting functions to these signalsApply signal weighting functions to these signalsRecalculate 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

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Determination of Tower Jet Determination of Tower Jet CalibrationCalibration

Determination of Tower Jet Determination of Tower Jet CalibrationCalibration

Sample of fully simulated QCD di-jet events from hard Sample of fully simulated QCD di-jet events from hard scatter pT>17 GeV/c to kinematic limitscatter pT>17 GeV/c to kinematic limit

Electronic noise included in simulationElectronic noise included in simulation

Match reconstructed calorimeter jet with close-by particle Match reconstructed calorimeter jet with close-by particle jetjet

Both jets reconstructed with seeded cone R=0.7Both jets reconstructed with seeded cone R=0.7pTpTseedseed>1 GeV/c>1 GeV/cOverlap threshold 50%Overlap threshold 50%

Match exclusive: only accepted if only one jet close byMatch exclusive: only accepted if only one jet close byCalorimeter jets are based on tower signals in a grid of Calorimeter jets are based on tower signals in a grid of ΔΔηηxxΔΔηη = = 0.1x0.10.1x0.1

Access cell signals in jetAccess cell signals in jetH1 motivated cell signal weighting strategyH1 motivated cell signal weighting strategyDetermine cell signal weights in resolution optimization fit using truth Determine cell signal weights in resolution optimization fit using truth particle jet energy as normalizationparticle jet energy as normalization

Weights are function of cell location and cell signal densityWeights are function of cell location and cell signal densityDense signals – em, less dense signals hadronic

Re-calculate jet four-momentum using cell weightsRe-calculate jet four-momentum using cell weightsJet energy and direction changeJet energy and direction change

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Tower Jet PerformanceTower Jet PerformanceTower Jet PerformanceTower Jet Performance

Signal linearitySignal linearityRelative to matched MC Relative to matched MC truth jet!truth jet!

calibrated

49%σ = 3.4%E E[GeV]

S. Padhi, ATLAS Physics Workshop 07/2005

S. Padhi, ATLAS Physics Workshop 07/2005

Energy resolutionEnergy resolutionRelative to truthRelative to truth

2.35 2.55 10 13 GeV /ty p c

Kristin Lohwasser, September 2007

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Tower Jet Tower Jet UniformityUniformityTower Jet Tower Jet UniformityUniformity

Signal linearity as Signal linearity as function of jet directionfunction of jet direction

Cracks less visible for Cracks less visible for wider jets, as expectedwider jets, as expected

No strong jet energy No strong jet energy dependencedependence

Relative energy Relative energy resolution as function resolution as function of jet directionof jet direction

Cracks deteriorate signalCracks deteriorate signal

Relative effect stronger Relative effect stronger dependend on jet energy, dependend on jet energy, less on jet sizeless on jet size



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Cluster Jets Cluster Jets in ATLASin ATLAS

Cluster Jets Cluster Jets in ATLASin ATLAS

Attempt to factorizeAttempt to factorizeNoise suppressionNoise suppression

Noisy cells are removedNoisy cells are removed

Hadronic calibrationHadronic calibrationSignal weighting in cluster Signal weighting in cluster context, no jet biascontext, no jet bias

Dead material correctionsDead material correctionsLimited to vicinity of clustersLimited to vicinity of clustersCannot correct if no signal at Cannot correct if no signal at all nearbyall nearby

Out-of cluster correctionsOut-of cluster correctionsEfficiency correction for Efficiency correction for clustering algorithmclustering algorithm

Provides calibrated input Provides calibrated input to jet findingto jet finding

Relative mis-calibration Relative mis-calibration O(5%)O(5%)

Instead of O(30%)Instead of O(30%)

Clusters can be interpreted Clusters can be interpreted as massless pseudo-particlesas massless pseudo-particles

ATLAS convention, see later!ATLAS convention, see later!

Topological Clustering(includes noise suppression)

CaloCells(em scale)

CaloClusters(em scale)

Calorimeter Jets(em scale)

CaloClusters(em scale, classified)

Cluster Classification(identify em type clusters)



CaloClusters(locally calibrated had scale)

Hadronic Cluster Calibration(apply cell signal weighting dead material corrections, etc.)

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.)

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Why Cluster Jets At All?Why Cluster Jets At All?Why Cluster Jets At All?Why Cluster Jets At All?Reduce noise Reduce noise contributioncontribution

Fixed cone tower jetFixed cone tower jet

1

24

3

5

6

Fixed cone cluster jetFixed cone cluster jet

Iacopo Vivarelli, September 2006 Iacopo Vivarelli, September 2006

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Determination of cluster Determination of cluster calibrationcalibration

Determination of cluster Determination of cluster calibrationcalibration

ClassificationClassificationUse measurable cluster variables to determine if cluster looks Use measurable cluster variables to determine if cluster looks electromagnetic, hadronic, or noisyelectromagnetic, hadronic, or noisy

Cluster location (“early”) and average cell signal density useful to classify Cluster location (“early”) and average cell signal density useful to classify electromagnetic and hadronic clusterselectromagnetic and hadronic clustersNoisy clusters are typically seeded by negative signalNoisy clusters are typically seeded by negative signal

Often negative total cluster energy

Hadronic weightingHadronic weightingApply only to hadronic clustersApply only to hadronic clusters

Uses cluster direction, cluster energy, cell signal density and cell location Uses cluster direction, cluster energy, cell signal density and cell location (sampling layer) to find cell signal weights (sampling layer) to find cell signal weights

Dead material correctionsDead material correctionsApply to hadronic and electromagnetic clustersApply to hadronic and electromagnetic clusters

Uses DM corrections parametrized as function of cluster shapesUses DM corrections parametrized as function of cluster shapes

Out of cluster correctionsOut of cluster correctionsAccount for lost true signal due to clusteringAccount for lost true signal due to clustering

All corrections are derived from single pions and photonsAll corrections are derived from single pions and photonsDetailed simulations are needed for most of themDetailed simulations are needed for most of themCan all be benchmarked with test beam data! Can all be benchmarked with test beam data! Cannot correct for everything at cluster level Cannot correct for everything at cluster level

No signal, no correction!No signal, no correction!

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Cluster Jet Signal LinearityCluster Jet Signal LinearityCluster Jet Signal LinearityCluster Jet Signal Linearity

Flat response in Et and Flat response in Et and rapidityrapidity

Forward region problems under Forward region problems under studystudy

Missing ~8% jet energy Missing ~8% jet energy ~3% cluster mis-classification~3% cluster mis-classification

Cluster classified as em, but Cluster classified as em, but really is hadronicreally is hadronic

~3% signal efficiency~3% signal efficiencySignal of low energetic particles Signal of low energetic particles below cluster thresholdbelow cluster threshold

~2% electromagnetic calibration~2% electromagnetic calibrationEm clusters need own calibrationEm clusters need own calibration

Basic scale insufficient

Remember: calibration so far Remember: calibration so far comes from single particle!comes from single particle!

No jet context whatsoever!No jet context whatsoever!

Studies under way…Studies under way…We are now looking at topology We are now looking at topology based on clusters based on clusters Also started to look at jetsAlso started to look at jets

S.Menke/G. PospelovMarch 2007 T&P

S.Menke/G. PospelovMarch 2007 T&P

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Jet Energy Scale CorrectionsJet Energy Scale CorrectionsJet Energy Scale CorrectionsJet Energy Scale CorrectionsUse of kinematic Use of kinematic constraints in ppconstraints in pp

Photon/Z+jet pT balancePhoton/Z+jet pT balanceCentral value model Central value model dependent!dependent!

TopologyTopologyHard cuts on back-to-back no

problem at LHC!

Kinematic limit ~400 GeV/c Kinematic limit ~400 GeV/c pT(photon) for 1%pT(photon) for 1%

First shot at jet energy scale!First shot at jet energy scale!

W mass W mass Powerful but very special jetsPowerful but very special jets

W color-disconnectedNarrow jets

Di-jet balanceDi-jet balanceExtrapolation tool to high pT Extrapolation tool to high pT

Also detector uniformityAlso detector uniformity

Topology dependenceTopology dependence

Normalization strategyNormalization strategyMatch reconstructed pT Match reconstructed pT balance with particle level balance with particle level balancebalance

Unfold topology dependences Unfold topology dependences

Sigrid Jorgensen, September 2006

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Photon+JetPhoton+JetPhoton+JetPhoton+JetMissing Et Projection Missing Et Projection Fraction (MPF)Fraction (MPF)

Pioneered by DØPioneered by DØ

Low sensitivity to pile-upLow sensitivity to pile-up

No jet context neededNo jet context neededCan use clusters, towers, Can use clusters, towers, even cell signalseven cell signals

calo signals

calot t

tjetcalo

t

p p

pR

p

Dou

g S

chou

ten

, A

TL-

CO

M-P

HYS

-20

07

-05

7,S

ep

tem

ber

20

07

uncalibrated clustersuncalibrated clusters

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Jet Energy Scale From WJet Energy Scale From WJet Energy Scale From WJet Energy Scale From WChallenge: pile-up and W boostChallenge: pile-up and W boost

Pile-up can “improve” jet energy scale! Pile-up can “improve” jet energy scale!

W colour-disconnected from rest of eventW colour-disconnected from rest of eventCannot expect the same particle flow around jetCannot expect the same particle flow around jetNot straight forward to carry over corrections based on W mass to other jets at 1% levelNot straight forward to carry over corrections based on W mass to other jets at 1% level

P. Savard, P. Loch, CALOR97

η(W) ~1.8

34 2 110 cm sL

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Very High pT JetsVery High pT JetsVery High pT JetsVery High pT JetsReconstruction concern: Reconstruction concern: leakageleakage

Find indicators in jet signal Find indicators in jet signal to tag leakageto tag leakage

Late showering in Late showering in calorimetercalorimeter

Use muon spectrometer Use muon spectrometer hits behind jethits behind jet

No energy measurement, No energy measurement, but good tagbut good tag

Studies underway to Studies underway to validate jet energy scale validate jet energy scale at very high pTat very high pT

pT balance in systems with pT balance in systems with very high pT jet balancing very high pT jet balancing several lower energetic jetsseveral lower energetic jets

Frank P

aige, AT

LAS

T&

P W

eek February 2006

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Jet Finder Efficiencies in ATLASJet Finder Efficiencies in ATLASJet Finder Efficiencies in ATLASJet Finder Efficiencies in ATLASEfficiencyEfficiency

Only free parameter: Only free parameter: matching radius matching radius RRmm

No kinematics matching!No kinematics matching!

PurityPurityRelates to Relates to fake ratefake rate

# matches reconstructed and truth jets( )

# truth jets

( )

m

jetsm m

jetstruth

R

N R

N

# matches reconstructed and truth jets( )

# reconstructed jets

( )1 ( )

m

jetsm m

jets fake mreco

R

RN R

N

Jets in VBF!Jets in VBF!

Martin Schmitz, September 2007

Jets in VBF!Jets in VBF!

Martin Schmitz, September 2007

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Pile-Up in Clone Cluster Pile-Up in Clone Cluster JetsJetsPile-Up in Clone Cluster Pile-Up in Clone Cluster JetsJets

Expect cluster to suppress Expect cluster to suppress noisenoise

Works for pile-up as wellWorks for pile-up as wellFlucutations can be suppressed if Flucutations can be suppressed if correct noise RMS used in cluster correct noise RMS used in cluster finderfinder

Cluster noise cuts are symmetric!Cluster noise cuts are symmetric!

Some energy offset observedSome energy offset observedPile-up is asymmetricPile-up is asymmetricBaseline larger for correct RMSBaseline larger for correct RMS

Bias toward positive signals by Bias toward positive signals by noise selectionnoise selection

34 2 10.8 10 cm s

34 2 10.8 10 cm s

Et Pile-up in R=0.2 cone

Doug Schouten, ATL-COM-PHYS-2007-057,September 2007

34 2 10.8 10 cm s

Dou

g S

chou

ten

, A

TL-

CO

M-P

HYS

-20

07

-05

7,S

ep

tem

ber

20

07

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Jet MassesJet MassesJet MassesJet MassesGained interest at LHCGained interest at LHC

Heavily boosted top decaysHeavily boosted top decaysAll decay products reconstructed in All decay products reconstructed in one jetone jet

Jet mass one observable indicating Jet mass one observable indicating top decaytop decay

Jet substructure also sensitive to Jet substructure also sensitive to source!source!

Mass measurement challengingMass measurement challengingParticle jet level mass is referenceParticle jet level mass is reference

Simulations only!Simulations only!

Mass of calorimeter jet is affected Mass of calorimeter jet is affected by shower spreadsby shower spreads

Enters: signal definition dependence, Enters: signal definition dependence, cluster shapes, noise,…cluster shapes, noise,…

No significant attempt at Tevatron No significant attempt at Tevatron or elsewhereor elsewhere relative mass difference

cluster jets

cluster jets

cluster jets

tower jets

tower jets

tower jets

0.8y

1.7 2.5y

3.7 4.2y PL

& C

hia

ra P

ale

ari

, Post

er

@ S

LAC

ATLA

S W

ork

shop

, A

ug

ust

20

07

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Mass Reconstruction SensitivitiesMass Reconstruction SensitivitiesMass Reconstruction SensitivitiesMass Reconstruction Sensitivities

Contribution from low energetic particles Contribution from low energetic particles lostlost

Dead material and magnetic fieldDead material and magnetic field

Overall effect depends on signal definitionOverall effect depends on signal definition

How about effect on mass?How about effect on mass?

Exercise: remove particles below pT Exercise: remove particles below pT threshold from jet and re-calculate massthreshold from jet and re-calculate mass

Remember: towers are not calibratedRemember: towers are not calibratedMore severe effect of cut in tower jetsMore severe effect of cut in tower jets

Clusters are calibratedClusters are calibratedMore similar to particle selection in jetsMore similar to particle selection in jets

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Mass Mass SensitivitSensitivity y

Mass Mass SensitivitSensitivity y

change o

f m

ass

log10(least biased reconstructed mass/GeV)

QCD kT jets, D = 0.6

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Jet SubstructureJet SubstructureJet SubstructureJet SubstructureMass 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

J. B

utt

erw

ort

h e

t. a

l,, A

TL-

CO

M-P

HYS

-20

07

-07

7,O

ctob

er

20

07

Not very sensitive to calorimeter signal details!

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Jet Shapes (1)Jet Shapes (1)Jet Shapes (1)Jet Shapes (1)11stst question: any question: any relation between relation between number of particles, number of particles, towers, clusters in towers, clusters in jets?jets?

Most interesting for kTMost interesting for kTD = 0.6 hereD = 0.6 here

Look at matching Look at matching callorimeter/truth jetscallorimeter/truth jetsNote: not the most Note: not the most important variable!important variable!

We already expect We already expect change of “jet picture” change of “jet picture” by detector signal by detector signal definitiondefinitionHints on resolution Hints on resolution power for jet shape power for jet shape variables and mass variables and mass

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Jet Shapes (2)Jet Shapes (2)Jet Shapes (2)Jet Shapes (2)We expected clusters to We expected clusters to represent indivdual particlesrepresent indivdual 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, thoughMuch 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

~1:1 in endcap region~1:1 in endcap regionBest 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 Happy coincidence, not a design feature of the ATLAS calorimeter!feature of the ATLAS calorimeter!

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Jet Shapes (3)Jet Shapes (3)Jet Shapes (3)Jet Shapes (3)

Jet densityJet densityCalculate energy outside Calculate energy outside of cone R = 0.3 as function of cone R = 0.3 as function of pT and directionof pT and direction

Classic Tevatron Classic Tevatron measurementmeasurement

Experimental indication of Experimental indication of transition from (low pT) transition from (low pT) gluon to (high pT) quark gluon to (high pT) quark jets jets

Example: kT jets in Example: kT jets in QCDQCD

D = 0.6D = 0.6

cluster jetstower jetshadron jets

Fract

ion o

f energ

y o

uts

ide c

one a

round jet

axis

(R

cone=

0.3

)

log10(pTjet/GeV)

0.8y

1.7 2.5y

3.7 4.2y

PL &

Ch

iara

Pale

ari, P

oste

r @ S

LAC

ATLA

S W

orksh

op

, Au

gu

st 20

07

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SummarySummarySummarySummaryGeneralGeneral

Everything you have seen here from ATLAS is based on Everything you have seen here from ATLAS is based on simulations and thus very preliminarysimulations and thus very preliminary

Real data can bring us surprises (good and bad)Real data can bring us surprises (good and bad)

Jet signalsJet signalsCluster signal (~200/event) good basis for jet finding in physics Cluster signal (~200/event) good basis for jet finding in physics analysis contextanalysis context

Final jet energy scale corrections depend on analysis choices Final jet energy scale corrections depend on analysis choices for jet finders, -configurations, selected event topologies…for jet finders, -configurations, selected event topologies…

What we can get from jetsWhat we can get from jetsStrong interest to go beyond Tevatron jetsStrong interest to go beyond Tevatron jets

Jet masses and substructure analysis of great interest for Jet masses and substructure analysis of great interest for boosted heavy particle decaysboosted heavy particle decays

Jet shapes can test basic jet formation dynamics ??Jet shapes can test basic jet formation dynamics ??

New dimension added: jet signal shapes in calorimeters can New dimension added: jet signal shapes in calorimeters can improve calibration jet by jetimprove calibration jet by jet

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OutlookOutlookOutlookOutlookRefined jet calibrationRefined jet calibration

Use calorimeter jet signal shapesUse calorimeter jet signal shapesWe used cluster shapes already, now look at cluster We used cluster shapes already, now look at cluster distribution in jetdistribution in jet

Use inner detector tracksUse inner detector tracksLarge momentum fraction of jet in tracks indicates a very Large momentum fraction of jet in tracks indicates a very hadronic jet, i.e. more correctionshadronic jet, i.e. more corrections

Jet originsJet originsUse inner detector tracks and vertices to separate jets Use inner detector tracks and vertices to separate jets from hard scattering from jets from UE and/or pile-up (A. from hard scattering from jets from UE and/or pile-up (A. Schwartzman)Schwartzman)

All this has not been used much in the past, All this has not been used much in the past, but we have to address a 1% systematic but we have to address a 1% systematic error requirement somehow!error requirement somehow!We are more than ready for data!We are more than ready for data!

Backup SlidesBackup SlidesBackup SlidesBackup Slides

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JES error very quickly JES error very quickly systematically dominatedsystematically dominated

Large statistics in Large statistics in unexplored kinematic range unexplored kinematic range already at low luminosityalready at low luminosity

Calibration channels Calibration channels quickly accessiblequickly accessible

pT balancepT balancePhoton + jet(s) Photon + jet(s) Z+jet(s) laterZ+jet(s) later

Mass spectroscopyMass spectroscopyW->jj in ttbarW->jj in ttbar

I nclusive J et

Production

~101.3×10-6pt > 3 TeV

~10310-4pt > 2 TeV

~1060.1pt > 1 TeV

~109100pt > 200 GeV

~1070.8tt

~1071.5Z → e+e―

~10815W → eν

Evts/year ( =10 fb- 1)

σ (nb)Process

I nclusive J et

Production

~101.3×10-6pt > 3 TeV

~10310-4pt > 2 TeV

~1060.1pt > 1 TeV

~109100pt > 200 GeV

~1070.8tt

~1071.5Z → e+e―

~10815W → eν

Evts/year ( =10 fb- 1)

σ (nb)Process

g

q γ

qg

q γ

q

Dominant direct photon production gives access to gluon structure at high x (~0.0001-0.2) (precision ?)

Jet Energy Scale Jet Energy Scale (JES)(JES)

Jet Energy Scale Jet Energy Scale (JES)(JES)

40 400 GeVTp c 50 200 GeVZ

Tp c

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Measurements with JetsMeasurements with JetsMeasurements with JetsMeasurements with Jets

sensitivity to compositeness scale Λ up to 40 TeV @ 300 fb-1 (all quarks are composites)

CompositenessCompositeness

Deviation from SM

PDFsPDFsdi-jet cross section and properties (Et,η1,η2) constrain parton distribution function

s

( ) 10%s zM

just from cross-section, can be improved by 3/2 jet ratio, but no competition for LEP/HERA!

Strong CouplingStrong Coupling

test of QCD at very small scale ( )s 0.08

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““H1” Style Cell Signal Weighting H1” Style Cell Signal Weighting in ATLASin ATLAS

““H1” Style Cell Signal Weighting H1” Style Cell Signal Weighting in ATLASin ATLAS

Fit constraint:Fit constraint:

Jet four-momentum calculation after fit Jet four-momentum calculation after fit

Final corrections for residual signal non-linearitiesFinal corrections for residual signal non-linearitiesAlgorithm dependenciesAlgorithm dependencies

Available for seeded cone R=0.4, kT D=0.4, D=0.6Available for seeded cone R=0.4, kT D=0.4, D=0.6

Signal dependencies (cluster/tower)Signal dependencies (cluster/tower)

1

, ( , ) , , with cells

Njet jetreco reco i i i i i i

i

E p w X E p E p

2

1 1

( , ) 0jets cells

N Njet

i i i truthj i

w X E Ew

““masslesmassless pseudo-s pseudo-particles”particles”

, ( , )jet jet jeta s t reco truthf p E E

Jet Reconstruction in ATLAS Peter Loch University of Arizona Tucson, Arizona, USA Peter Loch...

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Transcript of Jet Reconstruction in ATLAS Peter Loch University of Arizona Tucson, Arizona, USA Peter Loch...