P. Loch U of Arizona June 23, 2009 P. Loch U of Arizona June 23, 2009 Introduction To Jet & Missing...

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U of ArizonaU of Arizona

June 23, 2009June 23, 2009

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June 23, 2009June 23, 2009

Introduction ToIntroduction ToJet & Missing Transverse Energy Jet & Missing Transverse Energy

Reconstruction in ATLASReconstruction in ATLAS

Introduction ToIntroduction ToJet & Missing Transverse Energy Jet & Missing Transverse Energy

Reconstruction in ATLASReconstruction in ATLAS

Peter LochPeter Loch

University of ArizonaUniversity of Arizona

Tucson, ArizonaTucson, Arizona

USAUSA

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June 23, 2009June 23, 20092222 PreliminariesPreliminariesPreliminariesPreliminaries ScopeScope

Introduction focuses on explanation of algorithms and methodsIntroduction focuses on explanation of algorithms and methods Including some pointers to underlying principles, motivations, and Including some pointers to underlying principles, motivations, and

expectationsexpectations Support discussion sessions by presenting common issues only onceSupport discussion sessions by presenting common issues only once

Plots shown can be obsoletePlots shown can be obsolete Plots are used to deliver impressions only – no or few hard facts!Plots are used to deliver impressions only – no or few hard facts! Latest performance evaluation and comparisons will be discussed in Latest performance evaluation and comparisons will be discussed in

depth in the course of the next few daysdepth in the course of the next few days AudienceAudience

Clearly introductory character aims at prospective new Clearly introductory character aims at prospective new contributors contributors Lecture style but please – ask questions!Lecture style but please – ask questions!

Hopefully useful even for people already working on the topicsHopefully useful even for people already working on the topics If you are bored – you know where the beach is…If you are bored – you know where the beach is… … … but then don’t waste time addressing basic issues during the but then don’t waste time addressing basic issues during the

discussions!discussions! Historical contextHistorical context

Follow-up of presentations given at Milan & TucsonFollow-up of presentations given at Milan & Tucson Updates and extended missing Et partUpdates and extended missing Et part

Thanks to Michel Lefebvre and Peter Krieger for their help with Thanks to Michel Lefebvre and Peter Krieger for their help with the first two presentations!the first two presentations!

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June 23, 2009June 23, 20093333 RoadmapRoadmapRoadmapRoadmap Hadronic shower model simulation in Geant4Hadronic shower model simulation in Geant4

John ApostolakisJohn Apostolakis

Energy reconstruction in the ATLAS Energy reconstruction in the ATLAS calorimeterscalorimeters Manuella VincterManuella Vincter

Jets & missing transverse energy Jets & missing transverse energy reconstruction and calibrationreconstruction and calibration This talkThis talk

Introduction to modern jet algorithmsIntroduction to modern jet algorithms Paolo FrancavillaPaolo Francavilla

Summary of the recent ATLAS jet algorithm Summary of the recent ATLAS jet algorithm studiesstudies Sebastian EckweilerSebastian Eckweiler

Jet software from a user’s point of view Jet software from a user’s point of view experienceexperience Kerstin PerezKerstin Perez

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June 23, 2009June 23, 20094444 Overview (1)Overview (1)Overview (1)Overview (1) Part I: Introduction to jets at LHCPart I: Introduction to jets at LHC

Physics with jets at LHCPhysics with jets at LHC Some examples for final states involving jetsSome examples for final states involving jets

Physics collision environmentPhysics collision environment E.g., pile-upE.g., pile-up

Jet algorithms – rules and guidelinesJet algorithms – rules and guidelines Physics requirements to meaningful jetsPhysics requirements to meaningful jets Experimental requirements and limitationsExperimental requirements and limitations

Part II: Detector jet reconstruction and calibrationPart II: Detector jet reconstruction and calibration Calorimeter signal reconstruction for hadrons Calorimeter signal reconstruction for hadrons

Signals from hadronic showersSignals from hadronic showers Calorimeter towers & clustersCalorimeter towers & clusters Hadronic calorimeter energy scaleHadronic calorimeter energy scale

Jet reconstruction and calibrationJet reconstruction and calibration Task overviewTask overview Calorimeter input signalsCalorimeter input signals Cell weightingCell weighting

Jet energy scale corrections & characteristicsJet energy scale corrections & characteristics Experimental data and simulationsExperimental data and simulations Track jetsTrack jets

Software aspects of jet reconstruction and calibrationSoftware aspects of jet reconstruction and calibration

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June 23, 2009June 23, 20095555 Overview (2)Overview (2)Overview (2)Overview (2)

Part III: Missing EPart III: Missing Ett Reconstruction Reconstruction Contributions to missing EtContributions to missing Et Software aspectsSoftware aspects

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Physics with Jets at LHC Physics with Jets at LHC Physics with Jets at LHC Physics with Jets at LHC

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June 23, 2009June 23, 20097777 Where Do Jets Come From At LHC?Where Do Jets Come From At LHC?Where Do Jets Come From At LHC?Where 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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t bW jjj

t bW l jj

t bW jjj

t bW l jj


top mass reconstruction


LHCLHC




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LHCLHC




t bW jjj

t bW l jj

t bW jjj

t bW l jj


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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

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June 23, 2009June 23, 200911111111 LHC Environment: Underlying EventLHC Environment: Underlying EventLHC Environment: Underlying EventLHC Environment: Underlying Event

Collisions of other Collisions of other partons in the protons partons in the protons generating the signal generating the signal interactioninteraction Unavoidable in hadron Unavoidable in hadron

collisionscollisions No real first principle No real first principle

calculationscalculations Low pT (non-pertubative) Low pT (non-pertubative)

QCDQCD Some correlation with hard Some correlation with hard

scatteringscattering Typically tuned from data in Typically tuned from data in

physics generatorsphysics generators Carefully measured at Carefully measured at

TevatronTevatron Phase space factor applied Phase space factor applied

to LHC tune in absence of to LHC tune in absence of datadata

One of the first things to be One of the first things to be measured at LHCmeasured at LHC

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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




QCDQCD Some correlation with hard Some correlation with hard

scatteringscattering Typically tuned from data in Typically tuned from data in

physics generatorsphysics generators Carefully measured at Carefully measured at

TevatronTevatron Phase space factor applied Phase space factor applied



Look 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

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QCDQCD Activity shows some Activity shows some

correlation with hard correlation with hard scattering (radiation?)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 Phase space factor applied



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)

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June 23, 2009June 23, 200914141414 LHC Environment: Pile-UpLHC Environment: Pile-UpLHC Environment: Pile-UpLHC Environment: Pile-Up

Multiple interactions Multiple interactions between partons in other between partons in other protons in the same protons in the same bunch crossingbunch crossing Consequence of high rate Consequence of high rate

(luminosity) and high (luminosity) and high proton-proton total cross-proton-proton total cross-section (~75 mb)section (~75 mb)

Statistically independent Statistically independent of hard scatteringof hard scattering But similar models used for But similar models used for

soft physicssoft physics Signal history in Signal history in

calorimeter increases calorimeter increases noisenoise Signal 10-20 times slower Signal 10-20 times slower

than bunch crossing rate than bunch crossing rate (25 ns)(25 ns)

Noise has coherent Noise has coherent charactercharacter Cell signals linked through Cell signals linked through

past shower developmentspast shower developments

Et ~ 58 GeV

Et ~ 81 GeV

without pile-up

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Et ~ 58 GeV

Et ~ 81 GeV

with design luminosity pile-up

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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

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June 23, 2009June 23, 200917171717 Why Is That Important?Why Is That Important?Why Is That Important?Why 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

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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June 23, 2009June 23, 200918181818

Jet Algorithms – Rules & GuidelinesJet Algorithms – Rules & GuidelinesJet Algorithms – Rules & GuidelinesJet Algorithms – Rules & Guidelines

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June 23, 2009June 23, 200919191919 Jetology 101Jetology 101Jetology 101Jetology 101

What are jets for experimentalists?What are jets for experimentalists? A bunch of particles generated by hadronization of a common A bunch of particles generated by hadronization of a common

sourcesource Quark, gluon fragmenationQuark, gluon fragmenation

As a consequence, the particles in this bunch have correlated As a consequence, the particles in this bunch have correlated kinematic propertieskinematic properties Reflecting the source by sum rules/conservationsReflecting the source by sum rules/conservations

The The interactinginteracting particles in this bunch generated an particles in this bunch generated an observable signal in a detectorobservable signal in a detector Protons, neutrons, pions, photons, electrons, muons, other Protons, neutrons, pions, photons, electrons, muons, other

particles with laboratory lifetimes >~10ps, and the corresponding particles with laboratory lifetimes >~10ps, and the corresponding anti-particlesanti-particles

The The non-interactingnon-interacting particles do not generate a directly particles do not generate a directly observable signalobservable signal Neutrinos, mostlyNeutrinos, mostly

What is jet reconstruction, then?What is jet reconstruction, then? Model: attempt to collect the final state particles described Model: attempt to collect the final state particles described

above into objects (jets) representing the original parton above into objects (jets) representing the original parton kinematickinematic Re-establishing the correlationsRe-establishing the correlations

Experiment: attempt to collect the detector signals from these Experiment: attempt to collect the detector signals from these particles to measure their original kinematicsparticles to measure their original kinematics Usually not the parton!Usually not the parton!

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June 23, 2009June 23, 200920202020

Jet finding algorithm and its Jet finding algorithm and its configurationconfiguration Seeded or seedless cone and its Seeded or seedless cone and its

parameters parameters Cone size, seed thresholdCone size, seed threshold Recombination algorithmRecombination algorithm

Recursive recombination algorithmsRecursive recombination algorithms Distance parameterDistance parameter Recombination algorithmRecombination algorithm

Signal or constituent definitionSignal or constituent definition Calorimeter towers or clustersCalorimeter towers or clusters Reconstructed tracksReconstructed tracks Generated particlesGenerated particles Generated partonsGenerated partons

Useful concept to talk to other Useful concept to talk to other experiments and theoristsexperiments and theorists Also see Les Houches 2007Also see Les Houches 2007 arXiv:0803.0678v1 [hep-ph]arXiv:0803.0678v1 [hep-ph]

,

,

,

1

1

jetT T i

jet T i ijetT

jet T i ijetT

E E

EE

EE

,

,

,

1

1

jetT T i

jet T i ijetT

jet T i ijetT

E E

EE

EE

, ,jet jet i iE p E p , ,jet jet i iE p E p

“Snowmass”

4-momentum

Jet DefinitionJet DefinitionJet DefinitionJet Definition

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June 23, 2009June 23, 200921212121

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)

Infrared safetyInfrared safety Additional soft particles should Additional soft particles should

not affect jet reconstructionnot affect jet reconstruction

Collinear safetyCollinear safety Split energies (one instead of Split energies (one instead of

two particles) should not change two particles) should not change the jet the jet




two particles) should not change two particles) should not change the jet the jet

Theoretical RequirementsTheoretical RequirementsTheoretical RequirementsTheoretical Requirementsals

o s

ee P

. Fr

anca

vill

a’s

talk

!

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June 23, 2009June 23, 200922222222 Theoretical RequirementsTheoretical RequirementsTheoretical RequirementsTheoretical Requirements

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)




two particles) should not change two particles) should not change the jetthe jet




two particles) should not change two particles) should not change the jetthe jet

als

o s

ee P

. Fr

anca

vill

a’s

talk

!

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June 23, 2009June 23, 200923232323

Detector technology independenceDetector technology independence Jet efficiency should not depend on detector technologyJet efficiency should not depend on detector technology

Final jet calibration and corrections ideally unfolds all detector effectsFinal jet calibration and corrections ideally unfolds all detector effects

Minimal contribution from spatial and energy resolution to Minimal contribution from spatial and energy resolution to reconstructed jet kinematicsreconstructed jet kinematics Unavoidable intrinsic detector limitations set limitsUnavoidable intrinsic detector limitations set limits

Stability within environmentStability within environment (Electronic) detector noise should not affect jet reconstruction within reasonable (Electronic) detector noise should not affect jet reconstruction within reasonable

limits limits Energy resolution limitationEnergy resolution limitation Avoid energy scale shift due to noiseAvoid energy scale shift due to noise

Stability with changing (instantaneous) luminosityStability with changing (instantaneous) luminosity Control of underlying event and pile-up signal contributionControl of underlying event and pile-up signal contribution

““Easy” to calibrateEasy” to calibrate Small algorithm bias for jet signalSmall algorithm bias for jet signal

High reconstruction efficiencyHigh reconstruction efficiency Identify all physically interesting jets from energetic partons in perturbative QCDIdentify all physically interesting jets from energetic partons in perturbative QCD Jet reconstruction in resonance decaysJet reconstruction in resonance decays

High efficiency to separate close-by jets from same particle decayHigh efficiency to separate close-by jets from same particle decay Least sensitivity to boost of particleLeast sensitivity to boost of particle

Efficient use of computing resourcesEfficient use of computing resources Balance physics requirements with available computingBalance physics requirements with available computing

Fully specified algorithms onlyFully specified algorithms only Absolutely need to compare to theory at particle and parton levelAbsolutely need to compare to theory at particle and parton level Pre-clustering strategy, energy/direction definitions, recombination rules, splitting Pre-clustering strategy, energy/direction definitions, recombination rules, splitting

and merging strategy if applicableand merging strategy if applicable

Experimental RequirementsExperimental RequirementsExperimental RequirementsExperimental Requirements

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June 23, 2009June 23, 200924242424 Jet Algorithm ImplementationsJet Algorithm ImplementationsJet Algorithm ImplementationsJet Algorithm Implementations

See Paolo Francavilla’s talk for details!!See Paolo Francavilla’s talk for details!! Focus on physically meaningful jet findersFocus on physically meaningful jet finders

Implementations follow at least theoretical requirementsImplementations follow at least theoretical requirements

ATLAS now focuses on AntiKt for performance ATLAS now focuses on AntiKt for performance evaluationsevaluations Regularly shaped jetsRegularly shaped jets

Analytical access to area and overlaps (next slide)Analytical access to area and overlaps (next slide)

Good performance for narrow AntiKt jets (R = 0.4)Good performance for narrow AntiKt jets (R = 0.4) As you will see at this workshopAs you will see at this workshop Small nominal and actual area reduces effect of pile-up and Small nominal and actual area reduces effect of pile-up and

underlying eventunderlying event Higher signal stability expected!Higher signal stability expected!

Not ideal for more evolved jet analysisNot ideal for more evolved jet analysis E.g., substructure analysis in high pT jets from boosted heavy E.g., substructure analysis in high pT jets from boosted heavy

particle decays requires kTparticle decays requires kT

als

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June 23, 2009June 23, 200925252525 Jet ShapesJet ShapesJet ShapesJet Shapes

(from G. Salam’s talk at the ATLAS Hadronic Calibration Workshop Tucson 2008)

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June 23, 2009June 23, 200926262626

Calorimeter Signal Calorimeter Signal Reconstruction for HadronsReconstruction for Hadrons

Calorimeter Signal Calorimeter Signal Reconstruction for HadronsReconstruction for Hadrons

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June 23, 2009June 23, 200927272727 Signals from Hadronic ShowersSignals from Hadronic ShowersSignals from Hadronic ShowersSignals from Hadronic Showers

More complex than EM showersMore complex than EM showers Visible EM O(50%)Visible EM O(50%)

ee, , , , oo Visible non-EM O(25%)Visible non-EM O(25%)

Ionization of Ionization of , , pp, ,

Invisible O(25%)Invisible O(25%) Nuclear break-upNuclear break-up Nuclear excitationNuclear excitation

Escaped O(2%)Escaped O(2%) Neutrinos produced in showerNeutrinos produced in shower

Only part of the visible energy is Only part of the visible energy is sampled into the signalsampled into the signal Electromagnetic energy scale Electromagnetic energy scale

calibration does not recover losscalibration does not recover loss Need additional corrections to Need additional corrections to

measure hadron energymeasure hadron energy Cell signal hard to calibrate without Cell signal hard to calibrate without

contextcontext Cell signal from electron or hadron?Cell signal from electron or hadron? Need context to apply correct Need context to apply correct

calibration! calibration!

EM shower

RD3 note 41, 28 Jan 1993

Grupen, Particle Detectors

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June 23, 2009June 23, 200928282828 Shower Characteristics Side-by-SideShower Characteristics Side-by-SideShower Characteristics Side-by-SideShower Characteristics Side-by-Side

ElectromagneticElectromagnetic CompactCompact

Growths in depth ~log(E)Growths in depth ~log(E)

Longitudinal extension scale is Longitudinal extension scale is radiation length radiation length XX00

Distance in matter in which Distance in matter in which ~50% of electron energy is ~50% of electron energy is radiated offradiated off

Photons Photons 9/7 X9/7 X00

Strong correlation between Strong correlation between

lateral and longitudinal shower lateral and longitudinal shower developmentdevelopment

Small intrinsic shower-to-Small intrinsic shower-to-shower fluctuationsshower fluctuations Very regular developmentVery regular development

Can be simulated with high Can be simulated with high precisionprecision 1% or better, depending on 1% or better, depending on

featuresfeatures

HadronicHadronic Scattered, significantly biggerScattered, significantly bigger

Growths in depth ~log(E)Growths in depth ~log(E)

Longitudinal extension scale is Longitudinal extension scale is interaction length interaction length λλ Average distance between two Average distance between two

inelastic interactions in matterinelastic interactions in matter Varies significantly for pions, Varies significantly for pions,

protons, neutronsprotons, neutrons

Weak correlation between Weak correlation between longitudinal and lateral shower longitudinal and lateral shower developmentdevelopment

Large intrinsic shower-to-Large intrinsic shower-to-shower fluctuationsshower fluctuations Very irregular developmentVery irregular development

Can be simulated with Can be simulated with reasonable precisionreasonable precision ~2-5% depending on feature~2-5% depending on feature

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June 23, 2009June 23, 200929292929 Features of Hadronic SignalsFeatures of Hadronic SignalsFeatures of Hadronic SignalsFeatures of Hadronic Signals

Each signal component fraction depends on energyEach signal component fraction depends on energy Visible non-EM fraction Visible non-EM fraction decreases with decreases with EE

Hadronic signals more Hadronic signals more ““electromagnetic” at high energyelectromagnetic” at high energy Measured by Measured by the electron/pion the electron/pion ratio measured at the same ratio measured at the same deposited energydeposited energy

Hadron response not linear with Hadron response not linear with E E in ATLAS, in ATLAS, e/he/h > 1 for each sub-detector > 1 for each sub-detector

““e” is the intrinsic response to visible EMe” is the intrinsic response to visible EM ““h” is the intrinsic response to visible non-EMh” is the intrinsic response to visible non-EM invisible energy is the main source of e/h > 1 invisible energy is the main source of e/h > 1

Large fluctuations of each component fractionLarge fluctuations of each component fraction Non-compensation amplifies fluctuationsNon-compensation amplifies fluctuations

Hadronic calibration attempts to…Hadronic calibration attempts to… … … provide some degree of software compensationprovide some degree of software compensation … … account for the invisible and escaped energyaccount for the invisible and escaped energy

1

0

0

1

1 1

0.80 0.85

1 GeV2.6 GeV

me

h e E E

m

Ep

T.A. Gabriel, D.E. Groom, Nucl. Instr. Meth. A338 (1994) 336

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June 23, 2009June 23, 200930303030 Calorimeter CellsCalorimeter CellsCalorimeter CellsCalorimeter Cells

Smallest signal collection volumeSmallest signal collection volume Defines resolution of spatial structuresDefines resolution of spatial structures

Finest granularity depends on direction and sampling layerFinest granularity depends on direction and sampling layer Each is read out independentlyEach is read out independently

Can generate more than one signal (e.g., TileCell features two Can generate more than one signal (e.g., TileCell features two readouts)readouts)

Individual cell signalsIndividual cell signals Sensitive to noiseSensitive to noise

Fluctuations in electronics gain and shapingFluctuations in electronics gain and shaping Time jittersTime jitters Physics sources like multiple proton interaction history in pile-upPhysics sources like multiple proton interaction history in pile-up

Hard to calibrate for hadronsHard to calibrate for hadrons No measure to determine if electromagnetic or hadronic in cell signal No measure to determine if electromagnetic or hadronic in cell signal

alone, i.e. no handle to estimate e/halone, i.e. no handle to estimate e/h Need signal neighbourhood to calibrateNeed signal neighbourhood to calibrate

Basic energy scaleBasic energy scale Use electron calibration to establish basic energy scale for cell signalsUse electron calibration to establish basic energy scale for cell signals

Cell geometryCell geometry Quasi-projective by pointing to the nominal collision vertex in Quasi-projective by pointing to the nominal collision vertex in

central and endcap ATLAS calorimeterscentral and endcap ATLAS calorimeters Lateral sizes scale with pseudo-rapidity and azimuthal angular Lateral sizes scale with pseudo-rapidity and azimuthal angular

openingopening Non-projective in ATLAS Forward CalorimeterNon-projective in ATLAS Forward Calorimeter

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June 23, 2009June 23, 200931313131 Calorimeter TowersCalorimeter TowersCalorimeter TowersCalorimeter Towers

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

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June 23, 2009June 23, 200932323232 Topological Cell Clusters (1)Topological Cell Clusters (1)Topological Cell Clusters (1)Topological Cell Clusters (1)

Motivation Motivation 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

Attempt to suppress noise with Attempt to suppress noise with least bias on physics signalsleast bias on physics signals Often less than 50% of all cells Often less than 50% of all cells

in an event with “real” signalin an event with “real” signal

Uses cell signal significance Uses cell signal significance (signal over noise)(signal over noise) ElectronicElectronic Electronic + pile-up (quadratic Electronic + pile-up (quadratic

sum)sum)

Electronic Noise in Calorimeter Cells S. M

enke, AT

LAS

Physics W

orkshop 07/2005

Pile-up Noise in Calorimeter Cells S. M

enke, AT

LAS

Physics W

orkshop 07/2005

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TopoCluster algorithm TopoCluster algorithm implementation implementation Seeding (S)Seeding (S)

Cells with signal significance Cells with signal significance above primary seed thresholdabove primary seed threshold

Collecting (P)Collecting (P) Directly neighboring cells with Directly neighboring cells with

signals above basic threshold, signals above basic threshold, directly neighboring seed cells directly neighboring seed cells in 3-dimin 3-dim

Growth control (N)Growth control (N) Collect neighbors of neighbors Collect neighbors of neighbors

if those have signals above if those have signals above secondary seed significance secondary seed significance

Initial Cluster is done when no Initial Cluster is done when no more such cellsmore such cells

SplittingSplitting Find local signal maxima in Find local signal maxima in

cluster with cluster with E > E > 500 MeV500 MeV Split cluster between those Split cluster between those

Fine tuningFine tuning SeedingSeeding

Seeds can be restricted to Seeds can be restricted to certain calorimeter regionscertain calorimeter regions

SplittingSplitting Splitting is guided by EM Splitting is guided by EM

calorimeter in big clusterscalorimeter in big clusters Cells at split boundary are Cells at split boundary are

shared between clustersshared between clusters Signal weight is function of Signal weight is function of

cluster energiescluster energies

Default “4/2/0” Default “4/2/0” configuration for hadronic configuration for hadronic final statefinal state Primary seed significance Primary seed significance

S = 4S = 4

Secondary seed significance Secondary seed significance N = 2N = 2

Basic significance threshold Basic significance threshold P = 0, all cells neighboring a P = 0, all cells neighboring a

seed survive noise seed survive noise suppression!suppression!

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June 23, 2009June 23, 2009

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June 23, 2009June 23, 2009

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cluste

r candidate #1

cluste

r candidate #2

#3?

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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200936363636 4/2/0 TopoClusters4/2/0 TopoClusters4/2/0 TopoClusters4/2/0 TopoClusters

P

N

S

20 GeV pions

Resolution of Sum Eclus

P N

S

180 GeV pions

Resolution of Sum Eclus

S

N

P

Mean of Sum Eclus

Speckmayer, Carli

4,2,0 performs in 4,2,0 performs in the best waythe best way beam test pions beam test pions = =

0.450.45

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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200937373737 Local Hadronic Calibration (LC)Local Hadronic Calibration (LC)Local Hadronic Calibration (LC)Local Hadronic Calibration (LC)

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 (see later) But not the jet energy (see later)

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June 23, 2009June 23, 200938383838 LC Sequence LC Sequence LC Sequence LC 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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June 23, 2009June 23, 200939393939 Cluster ClassificationCluster ClassificationCluster ClassificationCluster Classification

Phase-space pion counting methodPhase-space pion counting method Classify clusters using the correlation ofClassify clusters using the correlation of

Shower shape variables in single Shower shape variables in single ±± MC events MC events = cluster barycenter depth in calo = energy weighted average cell density

Electromagnetic fraction estimator in bin of shower Electromagnetic fraction estimator in bin of shower shape variables:shape variables:

ImplementationImplementation keep keep FF in bins of in bins of , , EE, , , , of clusters for a given cluster of clusters for a given cluster

If E < 0, then classify as unknown Lookup F from the observables ||, E, , Cluster is EM if F > 50%, hadronic otherwise

0

0 2F

0

0 2F

, , , producing a cluster in a given

total

N X EX

N X

, , , producing a cluster in a given

total

N X EX

N X

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June 23, 2009June 23, 200940404040 Cluster Classification EfficiencyCluster Classification EfficiencyCluster Classification EfficiencyCluster Classification Efficiency

watc

h f

or

update

s in

LC

sess

ion!

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June 23, 2009June 23, 200941414141 LC Hadronic CalibrationLC Hadronic CalibrationLC Hadronic CalibrationLC Hadronic Calibration

hadronic weight

Cell signal Cell signal weightingweighting

Based on H1 conceptBased on H1 concept High cell signal High cell signal density – electromag-density – electromagnetic depositnetic deposit Low cell signal Low cell signal density – hadronic density – hadronic depositdeposit

Weights calculated from Geant4 charged pion simulationsWeights calculated from Geant4 charged pion simulations Large phase space covered in ATLAS geometryLarge phase space covered in ATLAS geometry Calibration hits provide local deposited energy referenceCalibration hits provide local deposited energy reference

Weights parameterized as function of cluster propertiesWeights parameterized as function of cluster properties Averaged in bins of cluster energy and cell signal densityAveraged in bins of cluster energy and cell signal density Weights stored in tables per sampling and directionWeights stored in tables per sampling and direction

2.0 < |2.0 < || < 2.2, HEC layer 1| < 2.2, HEC layer 1

watc

h f

or

update

s in

LC

sess

ion!

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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200942424242

Weights are extracted from simulationsWeights are extracted from simulations Signals and deposited energies from single charged pion MCSignals and deposited energies from single charged pion MC

Weights are calculated as function of cluster & cell variablesWeights are calculated as function of cluster & cell variables Signal environment used as additional indicator of hadronic characterSignal environment used as additional indicator of hadronic character

iv nvisis nonEmcell

E escmcel

nonEmcell

apedc ll lell ceE EEEw E

Escaped energy (no signal contribution)

Invisible energy (no signal contribution)

Ionization energy (charged hadron & muon signal contribution)

Electromagnetic energy (electron,positron,photon signal contribution)

Purely hadronic shower branch

Electromagnetic shower branch

, , ,...visnonEmem Emcell cell active

c A E E t

Reconstructed em scale signal

LC Cell Signal WeightingLC Cell Signal WeightingLC Cell Signal WeightingLC Cell Signal Weighting

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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200943434343 LC Dead Material CorrectionsLC Dead Material CorrectionsLC Dead Material CorrectionsLC Dead Material Corrections

Dead materialDead material Energy losses not directly Energy losses not directly

measurablemeasurable Signal distribution in vicinity can helpSignal distribution in vicinity can help

Introduces need for signal Introduces need for signal corrections up to O(10%)corrections up to O(10%) Exclusive use of signal featuresExclusive use of signal features Corrections depend on Corrections depend on

electromagnetic or hadronic energy electromagnetic or hadronic energy depositdeposit

Major contributionsMajor contributions Upstream materialsUpstream materials Material between LArG and Tile Material between LArG and Tile

(central)(central) CracksCracks

dominant sources for signal lossesdominant sources for signal losses ||ηη|≈1.4-1.5|≈1.4-1.5 ||ηη|≈3.2|≈3.2

Clearly affects detection efficiency Clearly affects detection efficiency for particles and jetsfor particles and jets Already in trigger!Already in trigger! Hard to recover jet reconstruction Hard to recover jet reconstruction

inefficiencies inefficiencies Generate fake missing Et Generate fake missing Et

contributioncontribution Topology dependence of missing Et Topology dependence of missing Et

reconstruction qualityreconstruction quality

Rel

ativ

e en

ergy

loss

in d

ead

mat

eria

lR

elat

ive

ener

gy lo

ss in

dea

d m

ater

ial

G. Posp

elo

v’s

contr

ibuti

on t

o t

his

work

shop

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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200944444444 Out-of-cluster CorrectionsOut-of-cluster CorrectionsOut-of-cluster CorrectionsOut-of-cluster Corrections

Compensate loss of true Compensate loss of true signalsignal Limited efficiency of noise Limited efficiency of noise

suppression schemesuppression scheme Discard cells with small true Discard cells with small true

energy not close to a energy not close to a primary or secondary seedprimary or secondary seed

Accidental acceptance of a Accidental acceptance of a pure noise cellpure noise cell

Can be significant for Can be significant for isolated pionsisolated pions 10% at low energy10% at low energy

Correction derived from Correction derived from single pionssingle pions Compensates the isolated Compensates the isolated

particle lossparticle loss But in jets neighboring But in jets neighboring

clusters can pick up lost clusters can pick up lost energyenergy

Use isolation moment to Use isolation moment to measure effective “free measure effective “free surface” of each clustersurface” of each cluster Scale single pion correction Scale single pion correction

with this moment (0…1)with this moment (0…1)

single pions

QCD jets

watc

h f

or

update

s in

LC

sess

ion!

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June 23, 2009June 23, 200945454545

Attempt to calibrate hadronic calorimeter signals in Attempt to calibrate hadronic calorimeter signals in smallest possible signal contextsmallest possible signal context Topological clustering implements noise suppression with least Topological clustering implements noise suppression with least

bias signal feature extractionbias signal feature extraction Residual concerns about infrared safety!Residual concerns about infrared safety!

No bias towards a certain physics analysisNo bias towards a certain physics analysis Calibration driven by calorimeter signal features without further Calibration driven by calorimeter signal features without further

assumption assumption Good common signal base for all hadronic final state objectsGood common signal base for all hadronic final state objects

Jets, missing Et, tausJets, missing Et, taus

Factorization of cluster calibrationFactorization of cluster calibration Cluster classification largely avoids application of hadronic Cluster classification largely avoids application of hadronic

calibration to electromagnetic signal objectscalibration to electromagnetic signal objects Low energy regime challengingLow energy regime challenging

Signal weights for hadronic calibration are functions of cluster Signal weights for hadronic calibration are functions of cluster and cell parameters and variablesand cell parameters and variables Cluster energy and directionCluster energy and direction Cell signal density and location (sampling layer)Cell signal density and location (sampling layer)

Dead material and out of cluster corrections are independently Dead material and out of cluster corrections are independently applicableapplicable

Summary LC FeaturesSummary LC FeaturesSummary LC FeaturesSummary LC Features

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June 23, 2009June 23, 200946464646

Jet Reconstruction & CalibrationJet Reconstruction & CalibrationJet Reconstruction & CalibrationJet Reconstruction & Calibration

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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200947474747 Jet Reconstruction Task OverviewJet Reconstruction Task OverviewJet Reconstruction Task OverviewJet Reconstruction Task Overview

Experiment (“Nature”)

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June 23, 2009June 23, 2009

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Particles

2 2( , )pdf Q x

UEMB

MB MB

Multiple InteractionsMultiple Interactions

Stable Particles

Decays

Jet Finding

Particle Jets

Particle Jets

GeneratedParticles

GeneratedParticles

Modeling Particle JetsModeling Particle Jets

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Modeling Calorimeter JetsModeling Calorimeter Jets

Stable Particles

Raw Calorimeter Signals

Detector Simulation

Reconstructed Calorimeter Signals

Signal Reconstruction

Jet Finding

Reconstructed Jets

Reconstructed JetsIdentified

ParticlesIdentified Particles


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Measuring Calorimeter JetsMeasuring Calorimeter Jets

Reconstructed Jets

Reconstructed Jets

Observable Particles

Raw Calorimeter Signals

Measurement

Reconstructed Calorimeter Signals

Signal Reconstruction

Jet Finding

Identified ParticlesIdentified Particles


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Jet Reconstruction ChallengesJet Reconstruction Challenges

physics reaction of interest (interaction or parton level)physics reaction of interest (interaction or parton level)

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

jet reconstruction algorithm efficiency

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

jet reconstruction algorithm efficiency

longitudinal energy leakagedetector signal inefficiencies (dead channels, HV…)

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

calo signal definition (clustering, noise suppression…)dead material losses (front, cracks, transitions…)

detector response characteristics (e/h ≠ 1)jet reconstruction algorithm efficiency

lost soft tracks due to magnetic field

longitudinal energy leakagedetector signal inefficiencies (dead channels, HV…)

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

calo signal definition (clustering, noise suppression…)dead material losses (front, cracks, transitions…)

detector response characteristics (e/h ≠ 1)jet reconstruction algorithm efficiency

lost soft tracks due to magnetic field


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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200952525252

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

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

Pre-clustering to speed up reconstruction (not needed as much Pre-clustering to speed up reconstruction (not needed as much anymore)anymore)

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

Jet calibrationJet calibration Depending on detector, jet finder choices, references…Depending on detector, jet finder choices, references…

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

significancesignificance

ObjectiveObjective Reconstruct particle level featuresReconstruct particle level features

Test models and extract physicsTest models and extract physics

““How-to” Of Jet ReconstructionHow-to” Of Jet Reconstruction““How-to” Of Jet ReconstructionHow-to” Of Jet Reconstruction

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June 23, 2009June 23, 200953535353 Input Signals (1) Input Signals (1) Input Signals (1) Input Signals (1)

Topological cell clusters (“TopoClusters”)Topological cell clusters (“TopoClusters”) Remove all negative energy clustersRemove all negative energy clusters

Noise suppressed at cluster level, no cancellation strategy Noise suppressed at cluster level, no cancellation strategy neededneeded

Negative clusters have no or insignificant physics signalNegative clusters have no or insignificant physics signal

Clusters provide flexible signalClusters provide flexible signal Three signal states availableThree signal states available

“UNCALIBRATED” – electromagnetic energy scale, cluster energy is cell energy sum including possible topological weights from cluster splitting

“CALIBRATED” – fully calibrated (LC) cluster, cluster energy is sum of weighted cell energies where weights represent the full correction in LC projected back to cell level

“ALTCALIBRATED” – cluster kinematics calculated from cell weights from the jet calibration (see later)

Subject positive energy clusters to jet findingSubject positive energy clusters to jet finding Choice of signal state of cluster Choice of signal state of cluster

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June 23, 2009June 23, 200954545454 Input Signals (2)Input Signals (2)Input Signals (2)Input Signals (2)

Unbiased towers (“CaloTowers”)Unbiased towers (“CaloTowers”) Electromagnetic energy scale signal onlyElectromagnetic energy scale signal only

No hadronic tower calibration scheme availableNo hadronic tower calibration scheme available

All cells includedAll cells included Can have net negative energy at fixed directionCan have net negative energy at fixed direction No noise suppressionNo noise suppression

Apply tower noise cancellationApply tower noise cancellation Sum towers signals in vicinity of negative tower until energy Sum towers signals in vicinity of negative tower until energy

sum > 0 sum > 0 Discard negative signal tower if re-summation does not Discard negative signal tower if re-summation does not

generate a positive signal (vicinity exhausted)generate a positive signal (vicinity exhausted) Note that in this re-summation the original towers are Note that in this re-summation the original towers are

preservedpreserved

Subject all original and merged towers to jet findingSubject all original and merged towers to jet finding Note that the resulting jets will have the original towers as Note that the resulting jets will have the original towers as

constituents, not the merged ones!constituents, not the merged ones!

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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200955555555 Input Signals (3)Input Signals (3)Input Signals (3)Input Signals (3)

Noise suppressed towers (“TopoTowers”)Noise suppressed towers (“TopoTowers”) Electromagnetic energy scale signal onlyElectromagnetic energy scale signal only

Could be extended in the future to LC and cell weighting Could be extended in the future to LC and cell weighting signals!signals!

Only cells surviving noise suppression are used in the Only cells surviving noise suppression are used in the towerstowers TopoClusters are used as noise suppression toolTopoClusters are used as noise suppression tool Additional cell filters possibleAdditional cell filters possible

Remove all negative energy TopoTowersRemove all negative energy TopoTowers Same argument as for TopoClusters – noise suppression Same argument as for TopoClusters – noise suppression

already applied, no cancellation neededalready applied, no cancellation needed

Subject positive energy TopoTowers to jet findingSubject positive energy TopoTowers to jet finding Jet constituents are these towersJet constituents are these towers

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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200956565656 Electromagnetic Energy Scale InputElectromagnetic Energy Scale InputElectromagnetic Energy Scale InputElectromagnetic Energy Scale Input

Tower jetsTower jets Jets are found using electromagnetic energy scale signals from Jets are found using electromagnetic energy scale signals from

towerstowers Only option – and done like this in most other experimentsOnly option – and done like this in most other experiments May be problem for recursive recombination jet finders as tower May be problem for recursive recombination jet finders as tower

signals may be wrong by several 10% relative to each othersignals may be wrong by several 10% relative to each other

Jets are calibrated after formationJets are calibrated after formation Apply a jet context calibration using cells (cell weighting) and/or Apply a jet context calibration using cells (cell weighting) and/or

sampling energies (sampling weights)sampling energies (sampling weights) Dead material and magnetic field effects intrinsically corrected by Dead material and magnetic field effects intrinsically corrected by

calibration functionscalibration functions

Cluster jetsCluster jets Jets can be found using electromagnetic energy scale signalsJets can be found using electromagnetic energy scale signals

One option with the same potential precision problem as for towersOne option with the same potential precision problem as for towers

Jets are calibrated after formationJets are calibrated after formation Same as for towers as weights do not show significant dependence on Same as for towers as weights do not show significant dependence on

calorimeter signal definitioncalorimeter signal definition

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June 23, 2009June 23, 200957575757 Local Hadronic Scale InputLocal Hadronic Scale InputLocal Hadronic Scale InputLocal Hadronic Scale Input

Clusters onlyClusters only Jets are found in a signal space with e/h compensated and Jets are found in a signal space with e/h compensated and

some other signal efficiencies already correctedsome other signal efficiencies already corrected Intuitively better for recursive recombination algorithms (kT – Intuitively better for recursive recombination algorithms (kT –

flavors)flavors)

Jet needs final set of correctionsJet needs final set of corrections Local hadronic scale does not have a jet contextLocal hadronic scale does not have a jet context Dead material energy losses not correlated with cluster Dead material energy losses not correlated with cluster

signalssignals Magnetic field bends charged particles with pT < 400-500 Magnetic field bends charged particles with pT < 400-500

MeV away from the calorimeterMeV away from the calorimeter

Cluster jet composition depends on input Cluster jet composition depends on input scalescale Jets found with electromagnetic signals cannot be Jets found with electromagnetic signals cannot be

expected to be the same as the ones found with locally expected to be the same as the ones found with locally calibrated signalscalibrated signals At least not with all aspects, especially composition detailsAt least not with all aspects, especially composition details Main features may be similar Main features may be similar

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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200958585858 Calibration FlowCalibration FlowCalibration FlowCalibration 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!

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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200959595959

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 JetsCaloTower JetsCaloTower JetsCaloTower Jets

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June 23, 2009June 23, 200960606060

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 JetsTopoCluster JetsTopoCluster JetsTopoCluster Jets

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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200961616161

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 JetsTopoTower JetsTopoTower JetsTopoTower Jets

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June 23, 2009June 23, 200962626262 Signal Choice Affects Jet ShapeSignal Choice Affects Jet ShapeSignal Choice Affects Jet ShapeSignal Choice Affects Jet Shape

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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200963636363

Can we get the hadronic shower branch signals up to a Can we get the hadronic shower branch signals up to a signal corresponding to the electromagnetic signal?signal corresponding to the electromagnetic signal? Reduce fluctuationsReduce fluctuations Direct proportionality of energy and signalDirect proportionality of energy and signal

One approach: cell signal weighting in highly granular One approach: cell signal weighting in highly granular calorimetercalorimeter Small signal densities in a calorimeter cell indicate hadronic Small signal densities in a calorimeter cell indicate hadronic

deposit and should receive an additional correction (weight) deposit and should receive an additional correction (weight) Pioneered by CDHS (1977) and developed by H1 (1992)Pioneered by CDHS (1977) and developed by H1 (1992)

High signal densities indicate electromagnetic signals and don’t High signal densities indicate electromagnetic signals and don’t need additional correctionsneed additional corrections Dense, compact showers from electrons/photonsDense, compact showers from electrons/photons

But how can we determine these weights?But how can we determine these weights? It’s mostly a matter of context: are we trying to determine them It’s mostly a matter of context: are we trying to determine them

for single particles (clusters) or jetsfor single particles (clusters) or jets ATLAS works with both approachesATLAS works with both approaches

Jets from both tower signals use jet context cell weightsJets from both tower signals use jet context cell weights Jets from topological clusters can use jet context cell weights as well Jets from topological clusters can use jet context cell weights as well

as cell weights determined in the cluster context in local hadronic as cell weights determined in the cluster context in local hadronic calibration (see earlier)calibration (see earlier)

Dealing With Non-CompensationDealing With Non-CompensationDealing With Non-CompensationDealing With Non-Compensation

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June 23, 2009June 23, 200964646464 Jet Calibration With Cell WeightsJet Calibration With Cell WeightsJet Calibration With Cell WeightsJet Calibration With Cell Weights

Weights are determined by resolution minimization fits Weights are determined by resolution minimization fits with calorimeter jets in “good” detector regionswith calorimeter jets in “good” detector regions Use full simulations of QCD di-jets to fit Use full simulations of QCD di-jets to fit w(…)w(…) such that such that

Truth reference typically matching simulated particle Truth reference typically matching simulated particle jetjet Experimental constraints possible, e.g. using photon-jet balanceExperimental constraints possible, e.g. using photon-jet balance

Weight determination includes primary electromagnetic Weight determination includes primary electromagnetic component of jetcomponent of jet Dense cell signals have weights ~1Dense cell signals have weights ~1

Weights compensate all signal inefficiencies, not only Weights compensate all signal inefficiencies, not only e/he/h Dead material corrections, leakage, possible low level of Dead material corrections, leakage, possible low level of

factorization!factorization!

3 0( , )jet jetcalo cell cell cells DM EMB Tile true

cells

E w X E E E E

3 0( , )jet jetcalo cell cell cells DM EMB Tile true

cells

E w X E E E E

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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200965656565 Cell Weight Calibration For JetsCell Weight Calibration For JetsCell Weight Calibration For JetsCell 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

P. LochP. Loch


June 23, 2009June 23, 2009

P. LochP. Loch




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

P. LochP. Loch


June 23, 2009June 23, 2009

P. LochP. Loch




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)

Snapshot!

P. LochP. Loch


June 23, 2009June 23, 2009

P. LochP. Loch


June 23, 2009June 23, 200968686868 Local Hadronic Calibration (LC)Local Hadronic Calibration (LC)Local Hadronic Calibration (LC)Local Hadronic Calibration (LC)

Calibrating calorimeter signals firstCalibrating calorimeter signals first No jet contextNo jet context But need other context for cell signal weighting But need other context for cell signal weighting

normalization normalization →→ topological cell cluster topological cell cluster Energy blobs follow shower shape somewhatEnergy blobs follow shower shape somewhat

Cluster based hadronic calibrationCluster based hadronic calibration Advantages to jet context: can use cluster shape to Advantages to jet context: can use cluster shape to

parameterize cell weightsparameterize cell weights Measure compactness of signal cluster by clusterMeasure compactness of signal cluster by cluster Shape and size variables are easily reconstructed for each Shape and size variables are easily reconstructed for each

clustercluster

Allows factorizationAllows factorization Deal with e/h at detector level (not jet level)Deal with e/h at detector level (not jet level) Correct for local dead material at cluster level alreadyCorrect for local dead material at cluster level already

Requires cluster signal to have some correlation with lossRequires cluster signal to have some correlation with loss

P. LochP. Loch


June 23, 2009June 23, 2009

P. LochP. Loch


June 23, 2009June 23, 200969696969 LC Features In JetsLC Features In JetsLC Features In JetsLC Features In Jets

Not a jet calibration Not a jet calibration per seper se Energy lost in particles Energy lost in particles

leaving no or weak signal leaving no or weak signal trace in calorimeter not trace in calorimeter not recoverable at cluster recoverable at cluster levellevel Magnetic fieldMagnetic field Dead materialDead material

Need jet level Need jet level corrections on top of corrections on top of this scalethis scale Transition hadronic to jet Transition hadronic to jet

energy scale can depend energy scale can depend on jet featureson jet features

P. LochP. Loch


June 23, 2009June 23, 2009

P. LochP. Loch


June 23, 2009June 23, 200970707070 LC Features In JetsLC Features In JetsLC Features In JetsLC Features In Jets

Not a jet calibration Not a jet calibration per seper se Energy lost in particles Energy lost in particles

leaving no or weak signal leaving no or weak signal trace in calorimeter not trace in calorimeter not recoverable at cluster recoverable at cluster levellevel Magnetic fieldMagnetic field Dead materialDead material

Need jet level Need jet level corrections on top of corrections on top of this scalethis scale Transition hadronic to jet Transition hadronic to jet

energy scale can depend energy scale can depend on jet features on jet features

Jet level correction for jets from locally calibrated clusters can recover jet energy

Example: correction based on jet width measurew

atc

h f

or

update

s in

jet

energ

y s

cale

sess

ion!

P. LochP. Loch


June 23, 2009June 23, 2009

P. LochP. Loch


June 23, 2009June 23, 200971717171

Jet Energy Scale CorrectionsJet Energy Scale CorrectionsJet Energy Scale CorrectionsJet Energy Scale Corrections

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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200972727272 Final Jet Energy Scale CalibrationFinal Jet Energy Scale CalibrationFinal Jet Energy Scale CalibrationFinal 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 implemented Data driven scenario a la DZero implemented Major topic of this workshop – only overview here!Major topic of this workshop – only overview here!

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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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200973737373 JES Correction Model For First DataJES Correction Model For First DataJES Correction Model For First DataJES Correction Model For First Data

optional

data driven

MC

Note that sequence Note that sequence is essential, but not is essential, but not a settled subjecta settled subject Expect discussions at Expect discussions at

this workshopthis workshop

watc

h f

or

update

s in

LC

sess

ion!

P. LochP. Loch


June 23, 2009June 23, 2009

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June 23, 2009June 23, 200974747474 Data Driven JES Corrections (1)Data Driven JES Corrections (1)Data Driven JES Corrections (1)Data Driven JES Corrections (1)

PileUp subtraction (see D. Miller’s contribution to this PileUp subtraction (see D. Miller’s contribution to this meeting!)meeting!) Goal:Goal:

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

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

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 for a given instantaneous Uses expectations from the average Et flow for a given instantaneous

luminosityluminosity Instantaneous luminosity is measured by the # vertices in the eventInstantaneous luminosity is measured by the # vertices in the event Requires measure of jet size (AntiKt advantage)Requires measure of jet size (AntiKt 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

D. M

iller’

s co

ntr

ibuti

on t

o JES s

ess

ion

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June 23, 2009June 23, 2009

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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

severa

l co

ntr

ibuti

ons

to JES s

ess

ion

P. LochP. Loch


June 23, 2009June 23, 2009

P. 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

severa

l co

ntr

ibuti

ons

to JES s

ess

ion

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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200977777777 Numerical InversionNumerical InversionNumerical InversionNumerical Inversion

( )trueR E

( )recR E

( )true trueR E E

trueE

Transfer of response function from dependence on true variable to dependence on measured variable

( )rec true truex E R E E ( )rec true truex E R E E

( ) ( ( ) )rec true truey R E R R E E ( ) ( ( ) )rec true truey R E R R E E

P. LochP. Loch


June 23, 2009June 23, 2009

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June 23, 2009June 23, 200978787878 Jets Not From Hard ScatterJets Not From Hard ScatterJets Not From Hard ScatterJets Not From Hard Scatter

Dangerous background for W+n jets cross-sections etc.Dangerous background for W+n jets cross-sections etc. Lowest pT jet of final state can be faked or misinterpreted as Lowest pT jet of final state can be faked or misinterpreted as

coming from underlying event or multiple interactionscoming from underlying event or multiple interactions Underlying event: multi-parton interactions Underlying event: multi-parton interactions Multiple proton interactions: pile-upMultiple proton interactions: pile-up

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 interactionsJet-by-jet handle for multiple interactions Classic indicator for multiple interactions is number of Classic indicator for multiple interactions is number of

reconstructed vertices in eventreconstructed 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 can in principle If we can attach vertices to reconstructed jets, we can in principle identify jets not from hard scatteringidentify jets not from hard scattering Limited to pseudorapidities within 2.5!Limited to pseudorapidities within 2.5!

P. LochP. Loch


June 23, 2009June 23, 2009

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June 23, 2009June 23, 200979797979

Match tracks in track jet with Match tracks in track jet with calorimeter jetcalorimeter jet Calculate pT fraction coming from each Calculate pT fraction coming from each

vertex for given jetvertex for given jet Jets with little pT from primary vertex are Jets with little pT from primary vertex are

likely from multiple interactions (e.g. pile-up)likely from multiple interactions (e.g. pile-up)

ATLAS MC(preliminary)

ATLAS MC(preliminary)

Application of TrackjetsApplication of TrackjetsApplication of TrackjetsApplication of Trackjets

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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200980808080

Software Aspects for Jet Software Aspects for Jet Reconstruction and CalibrationReconstruction and Calibration

(see Kerstin Perez’ talk)(see Kerstin Perez’ talk)

Software Aspects for Jet Software Aspects for Jet Reconstruction and CalibrationReconstruction and Calibration

(see Kerstin Perez’ talk)(see Kerstin Perez’ talk)

P. LochP. Loch


June 23, 2009June 23, 2009

P. LochP. Loch


June 23, 2009June 23, 200981818181 Jet Reconstruction SoftwareJet Reconstruction SoftwareJet Reconstruction SoftwareJet Reconstruction Software

Algorithm design guidelinesAlgorithm design guidelines Simple algorithm structureSimple algorithm structure

Jet reconstruction is defined by combining tools in the Jet reconstruction is defined by combining tools in the appropriate way appropriate way

Typical sequence: input filter – jet finder – (jet calibrator) – jet Typical sequence: input filter – jet finder – (jet calibrator) – jet output filteroutput filter

All managed by one highly configurable, generic algorithm All managed by one highly configurable, generic algorithm

Universal code for jet finding implementationUniversal code for jet finding implementation Same algorithm and tools for calorimeter, track, “truth Same algorithm and tools for calorimeter, track, “truth

particle” jetsparticle” jets FastJet libraries (Salam et al.) used for actual jet finder FastJet libraries (Salam et al.) used for actual jet finder

implementations (kT, C/A kT, AntiKt, SISCone,…)implementations (kT, C/A kT, AntiKt, SISCone,…) Except ATLAS legacy cone (not IR safe beyond LO)

Specific code for calibration can be plugged inSpecific code for calibration can be plugged in E.g., cell weight calibrator toolE.g., cell weight calibrator tool

P. LochP. Loch


June 23, 2009June 23, 2009

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June 23, 2009June 23, 200982828282 Re-reconstructing JetsRe-reconstructing JetsRe-reconstructing JetsRe-reconstructing Jets

Always possible from ESD with your favorite Always possible from ESD with your favorite jet finderjet finder CaloTowers, TopoTowers, TopoClustersCaloTowers, TopoTowers, TopoClusters

Can apply cell weighting calibrationCan apply cell weighting calibration Can reconstruct LC jetsCan reconstruct LC jets

Possible from AOD with restrictionsPossible from AOD with restrictions Only TopoClusters availableOnly TopoClusters available

Electromagnetic energy scale jetsElectromagnetic energy scale jets LC jetsLC jets New – cell weighted cluster signal can be exploredNew – cell weighted cluster signal can be explored

Detailed documentation on ATLAS TWikiDetailed documentation on ATLAS TWiki Also tutorial on Saturday afternoon!Also tutorial on Saturday afternoon!

see t

uto

rial on S

atu

rday!

P. LochP. Loch


June 23, 2009June 23, 2009

P. LochP. Loch


June 23, 2009June 23, 200983838383

Missing Et (MET) ReconstructionMissing Et (MET) ReconstructionMissing Et (MET) ReconstructionMissing Et (MET) Reconstruction

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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200984848484 Detector Signal MET ContributionsDetector Signal MET ContributionsDetector Signal MET ContributionsDetector Signal MET Contributions

Hard signal in calorimetersHard signal in calorimeters Fully reconstructed & calibrated particles and jetsFully reconstructed & calibrated particles and jets

Not always from hard interaction!Not always from hard interaction!

Hard signal in muon spectrometerHard signal in muon spectrometer Fully reconstructed & calibrated muonsFully reconstructed & calibrated muons

May generate isolated or embedded soft calorimeter signalsMay generate isolated or embedded soft calorimeter signals Care needed to avoid double countingCare needed to avoid double counting

Soft signals in calorimetersSoft signals in calorimeters Signals not used in reconstructed physics objectsSignals not used in reconstructed physics objects

I.e., below reco threshold(s)I.e., below reco threshold(s) Needs to be included in MET to reduce scale biases and improve Needs to be included in MET to reduce scale biases and improve

resolutionresolution Need to avoid double countingNeed to avoid double counting

Common object use strategy in ATLASCommon object use strategy in ATLAS Find smallest available calorimeter signal base for physics objects (cells or Find smallest available calorimeter signal base for physics objects (cells or

cell clusters)cell clusters) Check for exclusive basesCheck for exclusive bases

Same signal can only be used in one physics objectSame signal can only be used in one physics object Veto MET contribution from already used signalsVeto MET contribution from already used signals

Track with selected signal baseTrack with selected signal base Priority of association is defined by reconstruction uncertaintiesPriority of association is defined by reconstruction uncertainties

Electrons (highest quality) Electrons (highest quality) → → photons photons →→ muons* muons* →→ taus taus →→ jets (lowest jets (lowest quality)quality)

P. LochP. Loch


June 23, 2009June 23, 2009

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June 23, 2009June 23, 200985858585 MET Calorimeter IssuesMET Calorimeter IssuesMET Calorimeter IssuesMET Calorimeter Issues

Calorimeter issuesCalorimeter issues About 70-90% of all cells have no About 70-90% of all cells have no true or significant signaltrue or significant signal

Depending on final state, of courseDepending on final state, of course

Applying symmetric or asymmetricApplying symmetric or asymmetric noise cuts to cell signals noise cuts to cell signals

Reduces fluctuations significantlyReduces fluctuations significantly But introduces a bias (shift in But introduces a bias (shift in average missing Et)average missing Et)

Topological clustering applies more reasonable noise cutTopological clustering applies more reasonable noise cut Cells with very small signals can survive based on the signals Cells with very small signals can survive based on the signals

in neighboring cellsin neighboring cells Still small bias possible but close-to-ideal suppression of noiseStill small bias possible but close-to-ideal suppression of noise

K. C

ranmer, in talk by S

. Menke,

AT

LAS

Physics W

orkshop 07/2005

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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200986868686 MET Validation & CalibrationMET Validation & CalibrationMET Validation & CalibrationMET Validation & Calibration

MET is determined by hard signals in eventMET is determined by hard signals in event Reconstructed particles and jets above thresholdReconstructed particles and jets above threshold

All objects on well defined energy scale, e.g. best reconstruction for All objects on well defined energy scale, e.g. best reconstruction for individual object typeindividual object type

Really no freedom to change scales for any of these objectsReally no freedom to change scales for any of these objects Little calibration to be done for METLittle calibration to be done for MET Note that detector inefficiencies are corrected for physics objectsNote that detector inefficiencies are corrected for physics objects

Some freedom for soft MET contribution…Some freedom for soft MET contribution… Signals not used in physics objects often lack corresponding Signals not used in physics objects often lack corresponding

context to constrain calibrationcontext to constrain calibration Low bias LC based on signal shapes inside calorimeters helpsLow bias LC based on signal shapes inside calorimeters helps

Some degree of freedom hereSome degree of freedom here But contribution is small and mostly balanced in Et anywayBut contribution is small and mostly balanced in Et anyway

Source here often UE/pile-up!

……and overall acceptance limitationsand overall acceptance limitations Detector “loses” particles in non-instrumented areas or due to Detector “loses” particles in non-instrumented areas or due to

magnetic field in inner cavitymagnetic field in inner cavity Same remarks as above, very small and likely balanced signalsSame remarks as above, very small and likely balanced signals

Event topology dependent adjustments to MET are imaginable to Event topology dependent adjustments to MET are imaginable to recover these lossesrecover these losses

I prefer “validation” rather than “calibration”I prefer “validation” rather than “calibration” Discrepancies in MET need to be isolated for systematic controlDiscrepancies in MET need to be isolated for systematic control

P. LochP. Loch


June 23, 2009June 23, 2009

P. LochP. Loch


June 23, 2009June 23, 200987878787

MET scale can be checked MET scale can be checked with physicswith physics Look for one hadronic and Look for one hadronic and

one leptonic tau from Z one leptonic tau from Z decaysdecays Can be triggered nicely with Can be triggered nicely with

lepton + MET requirementlepton + MET requirement Use collinear approximation Use collinear approximation

to reconstruct invariant to reconstruct invariant massmass Massless tausMassless taus Neutrinos assumed to be Neutrinos assumed to be

collinear to observable tau collinear to observable tau decay productsdecay products

Check dependence of Check dependence of invariant mass on MET invariant mass on MET scale variationsscale variations Expect correlation!Expect correlation!

1 22( )( )(1 cos )had vm E E E E

1 22( )( )(1 cos )had vm E E E E

Determined from two reconstructed MET components and directions of detectable decay products

Determined from two reconstructed MET components and directions of detectable decay products

CERN-OPEN-2008-020

3

8%

100 pb-1

Z Mass ConstraintZ Mass ConstraintZ Mass ConstraintZ Mass Constraint

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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200988888888

What is that?What is that? MET contribution from response MET contribution from response

variationsvariations Cracks, azimuthal response Cracks, azimuthal response

variations…variations… Never/slowly changingNever/slowly changing Particle dependentParticle dependent

MET contribution from mis-MET contribution from mis-calibrationcalibration E.g., QCD di-jet with one jet E.g., QCD di-jet with one jet

under-calibratedunder-calibrated Relative effect generates MET Relative effect generates MET

pointing to this jetpointing to this jet Dangerous source of METDangerous source of MET

Disturbs many final states in a Disturbs many final states in a different waydifferent way

Can fake new physicsCan fake new physics Suppression strategiesSuppression strategies

Track jetsTrack jets Energy sharing between Energy sharing between

calorimeterscalorimeters Event topology analysisEvent topology analysis

CER

N-O

PEN

-20

08

-02

0

tt

(modeled material asymmetry)

Fake Missing EtFake Missing EtFake Missing EtFake Missing Et

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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200989898989

MET resolution MET resolution measuremeasure

MET resolution in MET resolution in each component as each component as function of scalar Et function of scalar Et sum for various final sum for various final statesstates

Systematically Systematically Evaluated for performance monitoring Evaluated for performance monitoring Careful – scalar Et very sensitive to pile-up, detector Careful – scalar Et very sensitive to pile-up, detector

effects, etc.effects, etc.

No direct experimental accessNo direct experimental access Minimum bias with limited reach/precision?Minimum bias with limited reach/precision? Concern is pile-up effect on scalar Et Concern is pile-up effect on scalar Et

CER

N-O

PEN

-20

08

-02

0

50% (GeV)tE

MET Resolution From MCMET Resolution From MCMET Resolution From MCMET Resolution From MC

P. LochP. Loch


June 23, 2009June 23, 2009

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June 23, 2009June 23, 200990909090 MET Scale & ResolutionMET Scale & ResolutionMET Scale & ResolutionMET Scale & Resolution

Experimental accessExperimental access With bi-sector signal With bi-sector signal

projections in Z decaysprojections in Z decays Longitudinal projection Longitudinal projection

sensitive to scalesensitive to scale Calibration of hadronic Calibration of hadronic

recoilrecoil

Perpendicular projection Perpendicular projection sensitive to angular sensitive to angular resolutionresolution

NeutrinoficationNeutrinofication Assumed to be very similar Assumed to be very similar

in Z and Win Z and W One lepton in Z decay can One lepton in Z decay can

be “neutrinofied”be “neutrinofied”

Access to MET resolution Access to MET resolution

hadronic recoil

tE

see E

.Dobso

n’s

contr

ibuti

ons

to M

ET s

ess

ion

P. LochP. Loch


June 23, 2009June 23, 2009

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June 23, 2009June 23, 200991919191

MET scaleMET scale Folds hadronic scale with Folds hadronic scale with

acceptanceacceptance Note: no jets needed!Note: no jets needed!

Experimental tool to validate Experimental tool to validate calibration of “unused” calorimeter calibration of “unused” calorimeter signalsignal Hard objects can be removed from Hard objects can be removed from

recoilrecoil One possible degree of freedom in One possible degree of freedom in

MET “calibration”MET “calibration” Relevance for other final states to Relevance for other final states to

be evaluatedbe evaluated Otherwise purely experimental Otherwise purely experimental

handle!handle!

MET resolutionMET resolution Can be measured along Can be measured along

perpendicular and longitudinal axisperpendicular and longitudinal axis Resolution scale is scalar Et sum Resolution scale is scalar Et sum

of hadronic calorimeter signalof hadronic calorimeter signal Biased by UE and pile-up (MC Biased by UE and pile-up (MC

needed here)needed here) Qualitatively follows calorimeter Qualitatively follows calorimeter

energy resolutionenergy resolution

CER

N-O

PEN

-20

08

-02

0C

ER

N-O

PEN

-20

08

-02

0

MET Scale & ResolutionMET Scale & ResolutionMET Scale & ResolutionMET Scale & Resolution

P. LochP. Loch


June 23, 2009June 23, 2009

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June 23, 2009June 23, 200992929292 Remarks Concerning METRemarks Concerning METRemarks Concerning METRemarks Concerning MET

Missing ET is a complex experimental quantityMissing ET is a complex experimental quantity Sensitive to precision and resolution of hard object reconstructionSensitive to precision and resolution of hard object reconstruction

MET is calibrated by everythingMET is calibrated by everything Easily affected by detector problems and inefficienciesEasily affected by detector problems and inefficiencies

Careful analysis of full event topologyCareful analysis of full event topology Signal shapes in physics and detectorSignal shapes in physics and detector

Known unknown (1): effect of underlying event Known unknown (1): effect of underlying event Some correlation with hard scattering?Some correlation with hard scattering?

Borderline with radiation?Borderline with radiation? Insignificant contribution??Insignificant contribution??

To be confirmed early with di-jetsTo be confirmed early with di-jets Known unknown (2): effect of pile-upKnown unknown (2): effect of pile-up

Level of activity not so clearLevel of activity not so clear Minimum bias first and urgent experimental taskMinimum bias first and urgent experimental task

Expectation is cancellation on average (at least)Expectation is cancellation on average (at least) Detector signal thresholds/acceptance potentially introduce asymmetriesDetector signal thresholds/acceptance potentially introduce asymmetries Need to know the “real” detector Need to know the “real” detector

Considerable contribution to MET fluctuations Considerable contribution to MET fluctuations Severe limitation in sensitivity for discoverySevere limitation in sensitivity for discovery

P. LochP. Loch


June 23, 2009June 23, 2009

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June 23, 2009June 23, 200993939393

MET Reconstruction SoftwareMET Reconstruction SoftwareMET Reconstruction SoftwareMET Reconstruction Software

P. LochP. Loch


June 23, 2009June 23, 2009

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June 23, 2009June 23, 200994949494 RequirementsRequirementsRequirementsRequirements

Support event ambiguity resolution in Support event ambiguity resolution in different signal granularitiesdifferent signal granularities ESD – track cell signal use to veto multiple MET ESD – track cell signal use to veto multiple MET

contributions from same cellcontributions from same cell AOD – track cluster signals for the same reasonAOD – track cluster signals for the same reason Implemented by book-keeping in cell/cluster maps filled by Implemented by book-keeping in cell/cluster maps filled by

MET toolsMET tools

Support re-calculation from ESD or AODSupport re-calculation from ESD or AOD Each MET contribution implemented as tool to adapt to Each MET contribution implemented as tool to adapt to

different data models and signal featuresdifferent data models and signal features METRefEle, METRefGamma, METRefTau, METRefJet, METRefEle, METRefGamma, METRefTau, METRefJet,

METRefMuon, METRefClusterMETRefMuon, METRefCluster

Each tool can work with cells and/or clustersEach tool can work with cells and/or clusters Exploits explicit knowledge of object signal content while Exploits explicit knowledge of object signal content while

using as much common implementation as possibleusing as much common implementation as possible

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June 23, 2009June 23, 2009

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June 23, 2009June 23, 200995959595

General approach of (refined) missing Et General approach of (refined) missing Et calculationcalculation Keep track of “signal use” by each object to avoid double Keep track of “signal use” by each object to avoid double

countingcounting Priority of association defined by client configured algorithm Priority of association defined by client configured algorithm

tool sequencetool sequence MET then calculated from uniquely assigned cells/clustersMET then calculated from uniquely assigned cells/clusters

Contribution can be entered on different energy scales Contribution can be entered on different energy scales including final calibration, local calibration, H1-style cell including final calibration, local calibration, H1-style cell weighting (ESD only) & basic (EM) scaleweighting (ESD only) & basic (EM) scale

AOD challengeAOD challenge No common “smallest” calorimeter signal baseNo common “smallest” calorimeter signal base

Topological cluster for jets, taus, “unused” calorimeter signalTopological cluster for jets, taus, “unused” calorimeter signal Sliding window cluster for electrons/photons (cells in AOD)Sliding window cluster for electrons/photons (cells in AOD) Cell list for isolated muons (in AOD)Cell list for isolated muons (in AOD)

Need a strategy for SW/Topo overlap Need a strategy for SW/Topo overlap Decided to implement 3-d cell/topo cluster and SW Decided to implement 3-d cell/topo cluster and SW

cluster/topo cluster overlap cluster/topo cluster overlap Measure overlap using topo-cluster envelope Measure overlap using topo-cluster envelope

Software IssuesSoftware IssuesSoftware IssuesSoftware Issues

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Event ambiguity resolution Event ambiguity resolution (1) check signal overlap by common calorimeter object use(1) check signal overlap by common calorimeter object use

CaloCells in ESDCaloCells in ESD CaloCluster (topological) in AODCaloCluster (topological) in AOD

(2) apply geometrical distance measures(2) apply geometrical distance measures Cut on (angular) distance between objectsCut on (angular) distance between objects

(3) apply additional similarity of signal measures(3) apply additional similarity of signal measures Cut on similarity of (uncalibrated) signalsCut on similarity of (uncalibrated) signals

Focus here on (1)Focus here on (1) Calorimeter signals in the AODCalorimeter signals in the AOD

Topo-clusters signal of choiceTopo-clusters signal of choice Reconstruct the whole event with low thresholdsReconstruct the whole event with low thresholds Provide shape informationProvide shape information

Used to reconstruct hadronic physics objectsUsed to reconstruct hadronic physics objects Straight forward common object use approachStraight forward common object use approach

New strategy for electrons and muonsNew strategy for electrons and muons Use overlap sliding window/topological cluster (electrons)Use overlap sliding window/topological cluster (electrons) Use overlap between cells and topological cluster (isolated muons) Use overlap between cells and topological cluster (isolated muons)

MET Software ImplementationsMET Software ImplementationsMET Software ImplementationsMET Software Implementations

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June 23, 2009June 23, 200997979797 Cluster Based Signal DecompositionCluster Based Signal DecompositionCluster Based Signal DecompositionCluster Based Signal Decomposition

Find topological clusters used by physics objectsFind topological clusters used by physics objects By object navigationBy object navigation

Jets and taus Jets and taus

More complex for electrons, photons, muonsMore complex for electrons, photons, muons Different cluster algorithm for electrons/photons: fixed size sliding Different cluster algorithm for electrons/photons: fixed size sliding

windowwindow No direct association between muons and (possible) topo clusterNo direct association between muons and (possible) topo cluster

Muon cluster signal may be below threshold Cells are collected around extrapolated track

Cell signals for electrons/photons/muons in AODCell signals for electrons/photons/muons in AOD

Cluster overlap resolution issuesCluster overlap resolution issues Topological clusters represent 3-d energy blobsTopological clusters represent 3-d energy blobs

Motivated by reconstructing one cluster/showerMotivated by reconstructing one cluster/shower Quite efficient even in dense jet environment (~1.6 particles/cluster, Quite efficient even in dense jet environment (~1.6 particles/cluster,

much better for isolated particles)much better for isolated particles)

Simple angular distance based selection may be insufficientSimple angular distance based selection may be insufficient A topo cluster containing signals not generated by the A topo cluster containing signals not generated by the

electron/photon may be “behind” the SW cluster representing this electron/photon may be “behind” the SW cluster representing this particle particle

Better to use other variables/features to measure overlapBetter to use other variables/features to measure overlap

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June 23, 2009June 23, 200998989898

““EM” EM” TopoClusterTopoCluster

Sliding Window Sliding Window ClusterCluster

2 2R

Hadronic Hadronic TopoClusterTopoCluster

Cluster OverlapCluster OverlapCluster OverlapCluster Overlap

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June 23, 2009June 23, 200999999999 Variables For Cluster Overlap ResolutionVariables For Cluster Overlap ResolutionVariables For Cluster Overlap ResolutionVariables For Cluster Overlap Resolution

TopoClusters and Sliding Window clusters TopoClusters and Sliding Window clusters representing the same em shower are differentrepresenting the same em shower are different Different shapesDifferent shapes

TopoCluster size determined by cell signal topologyTopoCluster size determined by cell signal topology SW cluster size fixed by clientSW cluster size fixed by client Both clusters will have different cell content!Both clusters will have different cell content!

Different signal fluctuationsDifferent signal fluctuations No noise suppression in SW clustersNo noise suppression in SW clusters

But less direct contributions from small signal “marginal” cells Noise suppression in TopoClustersNoise suppression in TopoClusters

Potentially more small signal cells with relatively large fluctuations

Possible variables to measure overlap (under study)Possible variables to measure overlap (under study) Total raw signalTotal raw signal

Affected by different noise characteristicsAffected by different noise characteristics Relative signal distribution in sampling layersRelative signal distribution in sampling layers

Could be better as some noise is unfolded in the ratiosCould be better as some noise is unfolded in the ratios Geometrical distance (barycenter-to-barycenter in 3-d)Geometrical distance (barycenter-to-barycenter in 3-d)

Not available for SW (could easily be implemented!)Not available for SW (could easily be implemented!) Subject to detector granularity changes (?)Subject to detector granularity changes (?)

Measure common cell contentMeasure common cell content Similar motivation as for ESDSimilar motivation as for ESD Adds several other (more stable) measures to overlap resolution, Adds several other (more stable) measures to overlap resolution,

see next slidessee next slides

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June 23, 2009June 23, 2009100100100100

TopoClusters have 3-d geometryTopoClusters have 3-d geometry Barycenter Barycenter ((x,y,zx,y,z))

In AOD, from In AOD, from ((R,R,ηη,,φφ))

Extension along and perpendicular to Extension along and perpendicular to “direction of flight”“direction of flight” Measured by 2Measured by 2ndnd geometrical moments geometrical moments Vertex assumption (0,0,0) for Vertex assumption (0,0,0) for right nowright now

Principal axis available for large enough clusters

Can calculate envelop around Can calculate envelop around barycenter barycenter Presently ellipsoidalPresently ellipsoidal

Could include apparent “longitudinal asymmetry” of em showers

Use simple model of Use simple model of longitudinal profilelongitudinal profile

x

y

z

c

s

xi

i

ri

Geometrical Features Of ClustersGeometrical Features Of ClustersGeometrical Features Of ClustersGeometrical Features Of Clusters

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June 23, 2009June 23, 2009101101101101

AOD TopoClusters have AOD TopoClusters have no cellsno cells Need to come up with some Need to come up with some

geometrical measuregeometrical measure Use the envelop!Use the envelop!

Can calculate likelihood Can calculate likelihood that cell is within that cell is within envelopenvelop Introduces two parameters Introduces two parameters

with typical values:with typical values:

May need some tuning!May need some tuning! Define cell i is inside topo Define cell i is inside topo

cluster c when…cluster c when… 22

22

ir

c c

i

c c

rp

R Ri c

p

22

22

ir

c c

i

c c

rp

R Ri c

p

x

y

z

c

s

xi

i

ri

3, 3rp p 3, 3rp p

Associating Cells With TopoClustersAssociating Cells With TopoClustersAssociating Cells With TopoClustersAssociating Cells With TopoClusters

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June 23, 2009June 23, 2009102102102102 Cell Content VariablesCell Content VariablesCell Content VariablesCell Content Variables

Shared cells between SW and TopoCluster provide:Shared cells between SW and TopoCluster provide: Fractional number of cells sharedFractional number of cells shared

Can be calculated for both clustersCan be calculated for both clusters Likely more useful for TopoCluster

Energy density measureEnergy density measure Fraction of cluster signal in shared cellsFraction of cluster signal in shared cells

Raw signal reference

Relative profilesRelative profiles Re-summation of raw sampling energies allows to calculate fractions Re-summation of raw sampling energies allows to calculate fractions

by sampling for both types of clustersby sampling for both types of clusters

……

When used with muons:When used with muons: Fraction of cells associated with a muon inside a TopoClusterFraction of cells associated with a muon inside a TopoCluster

Discard TopoCluster signal in MET calculation if muon corrected for Discard TopoCluster signal in MET calculation if muon corrected for calo energy losscalo energy loss

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June 23, 2009June 23, 2009103103103103 MET from Electron/Photon CellsMET from Electron/Photon CellsMET from Electron/Photon CellsMET from Electron/Photon Cells

METRefinedEleTool

egammaContainer

CellProcessor<egamma>Map<Cell>

checkscells

MissingET

(px,py,Et)

cells not yet used

ESD only!ESD only! Cells in electron can contribute on different scales:Cells in electron can contribute on different scales:

electromagnetic scaleelectromagnetic scalerefined scale (out of cluster corrections undone!)refined scale (out of cluster corrections undone!)

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June 23, 2009June 23, 2009104104104104 MET from Electron/Photon CellsMET from Electron/Photon CellsMET from Electron/Photon CellsMET from Electron/Photon Cells

ESD only!ESD only! Cells in electron can contribute Cells in electron can contribute

on different scales:on different scales:electromagnetic scaleelectromagnetic scalerefined scale (out of cluster refined scale (out of cluster corrections undone!)corrections undone!)H1 cell weightsH1 cell weights

METRefinedEleTool

egammaContainer

CellProcessor<egamma>Map<Cell>

checkscells

MissingET

c∙(px,py,Et)

cells not yet used

H1CalibrationTool

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June 23, 2009June 23, 2009105105105105 MET from Electron/PhotonMET from Electron/PhotonMET from Electron/PhotonMET from Electron/Photon

ESD and AODESD and AOD Electron/photon can contribute Electron/photon can contribute

on different scales:on different scales:electromagnetic scaleelectromagnetic scalerefined scale (out of cluster refined scale (out of cluster corrections undone!)corrections undone!)

METRefinedEleTool

ClusterProcessor<egamma>Map<Cluster>

checks overlapping cluster(s)

add egamma if overlap cluster not yet used

ClusterOverlapTool

MissingET

(px,py,Et)

egammaContainer CaloCalTopoCluster

utilizes functions in CaloUtils/CaloClusterOverlapHelpers

(useful also outside of MET calculations)

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June 23, 2009June 23, 2009106106106106 MET from Cells in JetsMET from Cells in JetsMET from Cells in JetsMET from Cells in Jets

ESD only!ESD only! Cells in jets can contribute on different scales:Cells in jets can contribute on different scales:

electromagnetic scale/local hadronic (cluster scales)electromagnetic scale/local hadronic (cluster scales)

refined scale (jet energy scale)refined scale (jet energy scale)

METRefinedJetTool

JetCollection

ClusterProcessor<Jet>Map<Cluster>

checks clusters

MissingET

cells not yet used

CellProcessor<Jet>

Map<Cell>

checks cells (px,py,Et)

Taus and topo-clusters very similar!

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June 23, 2009June 23, 2009107107107107 MET from Cells in JetsMET from Cells in JetsMET from Cells in JetsMET from Cells in Jets

ESD only!ESD only! Cells in jets can contribute on different scales:Cells in jets can contribute on different scales:

electromagnetic scale/local hadronic (cluster scales)electromagnetic scale/local hadronic (cluster scales)refined scale (jet energy scale)refined scale (jet energy scale)H1 cell calibrationH1 cell calibration

METRefinedJetTool

JetCollection


checks clusters

MissingET

cells not yet used

CellProcessor<Jet>

Map<Cell>

checks cells

H1CalibrationTool

c∙(px,py,Et)


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June 23, 2009June 23, 2009108108108108 MET from Clusters in JetsMET from Clusters in JetsMET from Clusters in JetsMET from Clusters in Jets

ESD and AODESD and AOD Clusters in jets can contribute on different scales:Clusters in jets can contribute on different scales:

electromagnetic scale/local hadronic (cluster scales)electromagnetic scale/local hadronic (cluster scales)

refined scale (jet energy scale)refined scale (jet energy scale)

METRefinedJetTool

JetCollection


checks clusters

MissingET

clusters not yet used

(px,py,Et)


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June 23, 2009June 23, 2009109109109109 Other RemarksOther RemarksOther RemarksOther Remarks

MET depends on “nice” behaviour of all other objectsMET depends on “nice” behaviour of all other objects We fixed some things by introducing special treatments, We fixed some things by introducing special treatments,

especially concerning navigationespecially concerning navigation Complication of MET codeComplication of MET code

This costs a lot of time!This costs a lot of time! We should have used Savannah more!!We should have used Savannah more!!

It seems that most objects now behave as expectedIt seems that most objects now behave as expected After tauObject navigation fixAfter tauObject navigation fix Still unclear about isolated muonsStill unclear about isolated muons

Performance checks can now be done with Performance checks can now be done with METPerformance package! METPerformance package! Stable platform for performance evaluationsStable platform for performance evaluations

Need to generalize cell/cluster mapsNeed to generalize cell/cluster maps Contain unambiguous eventContain unambiguous event Useful for MET significance, biasing jet reconstruction etc.Useful for MET significance, biasing jet reconstruction etc.

Can hide clusters already associated with electron from jet findingCan hide clusters already associated with electron from jet finding Need to review code locationNeed to review code location

Some of this should be a RecTool/RecStore rather than MET!Some of this should be a RecTool/RecStore rather than MET!

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June 23, 2009June 23, 2009110110110110

ConclusionConclusionConclusionConclusion

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June 23, 2009June 23, 2009111111111111 ConclusionConclusionConclusionConclusion

Jet/MET effort increased significantly in Jet/MET effort increased significantly in the last few yearsthe last few years Very good!Very good! Jet calibration task forceJet calibration task force MET and data quality task forceMET and data quality task force

Most basic features scenarios laid out Most basic features scenarios laid out for first datafor first data AntiKt R = 0.4 defaultAntiKt R = 0.4 default

Excellent – no more ATLAS cone!Excellent – no more ATLAS cone!

Several calibration scenarios under studySeveral calibration scenarios under study This meeting…This meeting…

Some things need more inputSome things need more input Towards one calibration schemeTowards one calibration scheme

Roadmap for comparisonsRoadmap for comparisons Discussion on SaturdayDiscussion on Saturday

Systematic uncertaintiesSystematic uncertainties How to evaluate with/for initial data?How to evaluate with/for initial data?

MET calculationMET calculation

P. Loch U of Arizona June 23, 2009 P. Loch U of Arizona June 23, 2009 Introduction To Jet & Missing...

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