Jets and Hadrons Calibration Strategy in ATLAS Ir e ne Vichou University of Athens

Jets and Hadrons Calibration Jets and Hadrons Calibration Strategy in ATLAS Strategy in ATLAS

Irene Vichou Irene Vichou University of AthensUniversity of Athens

IntroductionIntroductionCalibration Strategy (from testbeam to LHC data)Calibration Strategy (from testbeam to LHC data)Jet and hadron reconstruction Jet and hadron reconstruction In situ methodsIn situ methods

Z+jets and W jj samples

ConclusionsConclusions

July 2002 Ringberg Calibration Workshop - Irene Vichou 2

ConsiderationsConsiderations

The goal is to:The goal is to: reconstruct hadronic

entities on the calorimeter but also muons to assist the Spectrometer and transfer the calibration csts be able to reproduce as

precisely as possible their 4-momenta

This implies:This implies: pass the knowledge of

calorimeter response from the tests of modules

to the assembled detector to physics events

Physics casesPhysics cases mass reconstruction # jets and total E in SUSY

searches jet veto down to 15 GeV QCD studies (… unexpected)

RequirementsRequirements Knowledge of E scale for

jets should be ~1%


...Considerations...Considerations

Physics systematicsPhysics systematics fragmentation ISR FSR underlying and MinBias

Detector SystematicsDetector Systematics response different to charged and

neutral hadrons non linearities B-field dead material longitudinal shower leakage lateral shower size granularity electronics noise


Layout of ATLAS calorimetersLayout of ATLAS calorimeters

Calorimeters in ATLAS cover up to ||=5.

The electromagnetic calorimeter is a liquid argon accordion.

The hadronic calorimeter is an iron-scintillator device in the central region and Lar in the endcap and forward region

The EC cryostat houses EM, HAD and FCAL.


EM calorimeter segmentationEM calorimeter segmentation

•3 longitudinal samplings3 longitudinal samplings•very fine strips in 1st very fine strips in 1st •thick middle samplingthick middle sampling•good for good for //separationseparation

presampler in front forpresampler in front forenergy recoveryenergy recovery


Calibration StrategyCalibration Strategy

Before LHC….Before LHC…. Calibration with single particles at testbeamCalibration with single particles at testbeam transfer of calibration constants to all modules transfer of calibration constants to all modules

so that all calorimeters are set at the EM scaleso that all calorimeters are set at the EM scale

LHC start !LHC start ! intercalibration with single particles at LHCintercalibration with single particles at LHC in situ samplesin situ samples

W jet jet Z(photon)+jet balance

for E regions not reached before? MC...for E regions not reached before? MC...


TileCal calibration with CsTileCal calibration with Cs

AIMAIM: : Equalize cell responses and Equalize cell responses and balance optical non-uniformities.balance optical non-uniformities.

All individual optical components All individual optical components are “seen” in a shadowgram.are “seen” in a shadowgram.

The precision in the cell The precision in the cell response isresponse is 0.2% !!! 0.2% !!!

There is a good correlationThere is a good correlationwith muons ~ 3%with muons ~ 3%


Calibration in test beam Calibration in test beam

eeee

TileCal moduleTileCal modulee/e/ response = f(e/h, response = f(e/h,00 fraction) fraction) e/h (TileCal) = 1.3 ± 0.01e/h (TileCal) = 1.3 ± 0.01check resolution check resolution

Muon response (90Muon response (90oo) is due to ionisation) is due to ionisation•1 in 8 modules will see particles1 in 8 modules will see particles•muon signals correlate with Cs, muon signals correlate with Cs, so...so...Cs constants will be used to transfer theCs constants will be used to transfer theresponses to particles responses to particles


Tuning the Monte-CarloTuning the Monte-Carlo

Combined Test of EM and HAD calorimeters in beams Combined Test of EM and HAD calorimeters in beams (only once for final ATLAS modules!)(only once for final ATLAS modules!)

E ResolutionE Resolution

60% sampling term, 1.8% cst term60% sampling term, 1.8% cst term2 GeV noise term2 GeV noise term

LinearityLinearity e/e/ ratio ratio 1.35 to 1.371.35 to 1.37

• able to have a suitable hadronic shower Monte-Carloable to have a suitable hadronic shower Monte-Carlo• useful to establish energy reconstruction methodsuseful to establish energy reconstruction methods


Tuning the MC (G4)Tuning the MC (G4)

Pion Test beam resultsPion Test beam resultsvs vs

G4 for hadronic showers G4 for hadronic showers for Lar HECfor Lar HEC


E/p for isolated hadronsE/p for isolated hadrons

and and kk’s from ’s from W(Z) + jets W(Z) + jets ( (++--) + jets) + jets, with , with h h at LHC at LHC

Backgrounds:Backgrounds:• QCD jetsQCD jets• multi-particle multi-particle decaysdecays under control with under control with cuts on Ncuts on Ntracktrackand isolationand isolation

Triggerable (Triggerable ( and E and ETTmissmiss))

p(tracker) = E(calorimeter)p(tracker) = E(calorimeter)

E/p bias:E/p bias:0.3% from QCD0.3% from QCD3.5% total, mainly from 3.5% total, mainly from decaysdecays containing containing

Need to reject the Need to reject the bcg bcg by aby a factor of 5 factor of 5


E/p for isolated hadronsE/p for isolated hadrons

Make use of the fine EM caloMake use of the fine EM calogranularity of the 1st sapling.granularity of the 1st sapling.

A rejection of 11 is achieved A rejection of 11 is achieved at at =0.3=0.3

The residual bias in E/p dueThe residual bias in E/p dueto the to the bcg is bcg is 0.4%0.4%

Nr of Nr of -strips-strips

E(em1)/E(em)E(em1)/E(em)


sample #events

SIGNAL 530 x103

QCD bcg 30 x103

bcg 20 x103

E/p for hadronsE/p for hadrons Statistics for 10 fbStatistics for 10 fb-1-1

Global E/p bias is Global E/p bias is 0.6 %0.6 % (OK if < 1%) (OK if < 1%) The E reaches The E reaches

120 GeV in TileCal (barrel + extended) 240 GeV in the Endcap Lar

It is a good intercalibration methodIt is a good intercalibration method Gives absolute scale for hadronsGives absolute scale for hadrons Direct comparison with beam tests for h’s/mip in EM Direct comparison with beam tests for h’s/mip in EM


… … before using the in situ… before using the in situ… (in these studies)(in these studies)

fixed-cone algorithmfixed-cone algorithm

•““Benchmark” Benchmark” E= E= 11xxEE11++22xxEE22++33xxEE33++44xxEE44

•““a la H1” a la H1” E=EE=E11++22((2,j2,j))xx2,j 2,j + + 33((3,j3,j))xx3,j 3,j ++ 44xxEE44

where where 1…41…4 are PS,EM,HAD,cryostat correction terms are PS,EM,HAD,cryostat correction terms andand j j’s refer to cells ’s refer to cells and and EE4 4

`̀ss are function parametrisations wrt to parton energyare function parametrisations wrt to parton energy

Preserves linearity (calo effects) and resolution Preserves linearity (calo effects) and resolution

Jet Energy ReconstructionJet Energy Reconstruction

Cones Cones RR=0.4 and 0.7=0.4 and 0.7Seed 2 GeV,Ecell>2Seed 2 GeV,Ecell>2 noise noiseEtower Etower (0.1x0.1)(0.1x0.1) > 0.2 GeV > 0.2 GeV

Jet ?Jet ?

Jet E ?Jet E ?

E Eem had3 1


Jet Energy ReconstructionJet Energy Reconstruction

Sampling(% GeV1/2)

Constant()

Barrel 52.3 1.1 1.7 0.1

Endcap 64.2 2.4 3.6 0.2

Jet Energy Resolution termsJet Energy Resolution terms

And dependece on pseudorapidityAnd dependece on pseudorapidity

50%50% 3%3%

R=0.7R=0.7

samplingsampling constantconstant


Taus calibrationTaus calibration

Will be covered in Ambreesh’s talk as it is part of testWill be covered in Ambreesh’s talk as it is part of testcarried out in the new ATHENA frameworkcarried out in the new ATHENA framework


Extrapolation to high EExtrapolation to high E

And after calibrating…..And after calibrating…..What if wrong extrapolation to energies not reached What if wrong extrapolation to energies not reached before?before?

Example: Use of a Monte-Carlo not reproducing well the e/hExample: Use of a Monte-Carlo not reproducing well the e/h

norm at 100 GeVnorm at 100 GeV

norm at 500 GeVnorm at 500 GeV


In situ samplesIn situ samples

NeedNeed: Absolute for verification: Absolute for verificationWishWish: Statistics should be adequate above bcg: Statistics should be adequate above bcg Trigger available Trigger available Wide Energy coverage Wide Energy coverage

ChoicesChoices: Mass reconstruction of the W: Mass reconstruction of the W• only light q jetsonly light q jets• limited E and limited E and reachreach

Balance of pBalance of pTT between Z and leading jet between Z and leading jet • wider E andwider E andreachreach• b-jet contentb-jet content• good to transfer calibration across calorimeters?good to transfer calibration across calorimeters?


In situ samples In situ samples

Simulated using PYTHIA/JETSETSimulated using PYTHIA/JETSET

Fast simulationFast simulation• smearing with calorimeter resolutionsmearing with calorimeter resolution• jet finding from deposited energy in towersjet finding from deposited energy in towers

Full simulationFull simulation

• using GEANT 3.21using GEANT 3.21• G-Calor calorimeter response modelG-Calor calorimeter response model• addition of pile-up events and electronics noiseaddition of pile-up events and electronics noise• digital filtering for cell energy reconstruction digital filtering for cell energy reconstruction

In the following studies In the following studies

• Fixed cone algorithm used for jet reconstructionFixed cone algorithm used for jet reconstruction• Benchmark/Sampling method for jet E calculationBenchmark/Sampling method for jet E calculation and also weighting method for the Z+jetsand also weighting method for the Z+jets


In situ W In situ W jj jj

W’s are abundant through the tt events sampleW’s are abundant through the tt events sampleAt low L 1500 lAt low L 1500 lvvjjbb final states/day !jjbb final states/day !

The jj final states of the W decay should satisfy:The jj final states of the W decay should satisfy:

•Events easily triggered from isolated lepton and 2 b-jets.Events easily triggered from isolated lepton and 2 b-jets.•No physics bcg’s.No physics bcg’s.•Combinatorial bcg under the W peak ~ 30%.Combinatorial bcg under the W peak ~ 30%.

ppTTpartonparton/p/pTT

jetjet

~50 GeV out of cone losses

>200 GeV jet overlap pbms (add cut of R>0.8)

M E E Mjj j j j j W 2 11 2 1 2( cos )

Characteristics:Characteristics:


In situ W In situ W jj jj

After calibrating (full sim):

>70 GeV 1% is achievable

~50 GeV 3% looks fair

Further studies showed:Further studies showed:overestimation of corrected jet energy towards the high end of overestimation of corrected jet energy towards the high end of E-spectrum was due to underestimation of the angle.E-spectrum was due to underestimation of the angle.

Problem solved by taking into account E,Problem solved by taking into account E,and and in the minimisation in the minimisationprocedure and correct energies and angles.procedure and correct energies and angles.

Result: Result: E of parton and jet agree within ~ 1% over the range 50-250 GeVE of parton and jet agree within ~ 1% over the range 50-250 GeV


In situ WIn situ Wjet jetjet jet

Statistics: Statistics: 100 K100 K W’s for W’s for 10 fb10 fb-1-1

The W The W jj decay in tt events should provide the jj decay in tt events should provide the wished 1% absolute scale precision from 50 to wished 1% absolute scale precision from 50 to few hundred GeV for few hundred GeV for light quarkslight quarks

Lower end of spectrum:Lower end of spectrum: interplay between FSR and out of cone losses for specific

reconstruction algorithms

Higher endHigher end residual effects due to overlap are significant and special

treatment has to be applied to overcome this without significant loss of statistics (e.g. by asking well-separated jets)


In situ Z+jetIn situ Z+jet

Direct Z production, events with Z+jets where ZDirect Z production, events with Z+jets where Zee or Zee or ZMethod: pMethod: pT T balance between Z (leptonic/precisely measured) andbalance between Z (leptonic/precisely measured) and

highest phighest pTT jet jet

Large cross section, no statistics problemLarge cross section, no statistics problem

… … but balance is not perfectbut balance is not perfect

HP +UE +FSR +ISR0.0260.015

0.0050.002

0.0500.034

0.0970.071

ppTT imbalance wrt to processes imbalance wrt to processes

20<p20<pTT<60 GeV jets<60 GeV jets

60<p60<pTT<120 GeV jets<120 GeV jets

fractional imbalance between Z and jet: fractional imbalance between Z and jet:

FrIp p

pT

Z

T

j

T

Z



ppT T imbalance wrt to selection cutsimbalance wrt to selection cuts1 jet pT>20 GeV <3.2

>3.06 rad >3.06 radLoose jet veto

>3.06 radTight jet veto

0.0970.071

0.0500.042

0.0490.041

0.0440.033

Selections to favour topologies with back-to-back Z and jetSelections to favour topologies with back-to-back Z and jet•azimuthal angle between Z and leading jet > 3.06 radazimuthal angle between Z and leading jet > 3.06 rad•loose jet veto: no other jet ploose jet veto: no other jet pTT>40 GeV and |>40 GeV and ||<3.2 (|<3.2 (possible at high Lpossible at high L))•tight jet veto: no other jet ptight jet veto: no other jet pTT>15 GeV and |>15 GeV and ||<4.9|<4.9

20<p20<pTT<60 GeV<60 GeV60<p60<pTT<120 GeV <120 GeV

Fr IFr I



Impact of cuts assessed also with full simulationImpact of cuts assessed also with full simulation

Example is the jet veto capability with comparison betweenExample is the jet veto capability with comparison betweenfast and full simulationfast and full simulation

Fraction on events with >1 jet is reconstructed wrt to the pFraction on events with >1 jet is reconstructed wrt to the pTT threshold applied threshold applied

Cone Cone R = 0.7R = 0.7

adjustment of padjustment of pTT threshold to take into account threshold to take into account the EM scale calibration in full simthe EM scale calibration in full sim

Good agreement between fast and full sim in jet veto efficiency!Good agreement between fast and full sim in jet veto efficiency!



20-60 GeV 60-120 GeV >120 GeV

Barrel(… 1.7)

340K9K

180K4K

44K1K

End-cap(… 3.2)

190K5K

90K1.5K

16K0.5K

Forward(… 4.9)

30K 10K 1K

Rates after cuts are adequate for statistical sensitivity of 1%Rates after cuts are adequate for statistical sensitivity of 1%for pfor pTT<200 GeV. <200 GeV.

Nr of b-jets assuming 50% tagging efficiency hopefullyNr of b-jets assuming 50% tagging efficiency hopefullysufficient to constrain b-jet scale to % level. sufficient to constrain b-jet scale to % level.

+jet sample offers 30 times more events but more tend to bias+jet sample offers 30 times more events but more tend to biasin selecting back-to-back eventsin selecting back-to-back events

Number of jets after cuts for 10 fbNumber of jets after cuts for 10 fb-1-1 integrated luminosity in integrated luminosity in calorimeter and pcalorimeter and pT T regionsregions

Nr of Nr of b-jetsb-jets90% purity90% purity

NB overall jet sample content:NB overall jet sample content: 28% gluon , 54% light quark, 12% c and 6% b-jets28% gluon , 54% light quark, 12% c and 6% b-jets



Comparison between full and fast simulationComparison between full and fast simulation1 jet pT>20 GeV <3.2

>3.06 rad >3.06 radLoose jet veto

>3.06 radTight jet veto

0.0530.106

0.0400.091

0.0390.089

0.0330.076

0.0570.089

0.037 0.027 0.0240.050

Fast:Fast:

Full:Full:

all jetsall jetsb-jetsb-jets

Average Fractional ImbalanceAverage Fractional Imbalancein three pin three pT T ranges ranges

ppTT>40 GeV and |>40 GeV and ||<3.2|<3.2



20-60 60-120 >1200.049 0.015 0.004

GeVGeV

Accuracy of the calibration in this sampleAccuracy of the calibration in this sample

Reconstructed jet pReconstructed jet pTT rescaled to balance the Z p rescaled to balance the Z pTT wrt to the original parton pwrt to the original parton pTT

Fractional imbalanceFractional imbalanceof the two pof the two pTT’s’s

Systematics and effect on fractional imbalanceSystematics and effect on fractional imbalance

Uncertainties in modelling ISR:Uncertainties in modelling ISR:1.5 factor in1.5 factor inQCD QCD ±±1.5%(0.3%) at low (high) p1.5%(0.3%) at low (high) pTT

Topology uncertainties on back-to-back:Topology uncertainties on back-to-back: cut tightening by 0.06 rad cut tightening by 0.06 rad -0.7% to -0.1% -0.7% to -0.1%

Cone enlarging to Cone enlarging to R=0.7 R=0.7 0.3% 0.3%


Z+jet sampleZ+jet sample

Reconstructed energy with a weighting methodReconstructed energy with a weighting method

The aThe aii’s are derived using the Z as a reference’s are derived using the Z as a reference

Parametrise the aParametrise the aii’s as functions of E’s as functions of ETTjetjet

E f a ET

rec

i cell jet ( , ) / cosh( )

Non-lineraitiesNon-lineraitieswrt to the partonwrt to the parton


Z+jet resolutionsZ+jet resolutions

bisectorbisector

ppTT jet jet

ppTT Z Z

KKTT

KKTT

Bisector methodBisector method

sensitive to ISR and detector sensitive to ISR and detector resolutionresolutionsensitive to ISRsensitive to ISR

So, resolution due to jet recSo, resolution due to jet rec D 2 2


Z+jet resolutionsZ+jet resolutions

Difference in resolution obtained with the bisector andDifference in resolution obtained with the bisector andthe ‘classic’/true definition.the ‘classic’/true definition.


In situ jet calibrationIn situ jet calibration

The 1% jet calibration uncertainty is difficult but The 1% jet calibration uncertainty is difficult but it seems not impossible with the current studiesit seems not impossible with the current studies

The two types of in situ samples are somewhat The two types of in situ samples are somewhat complementary complementary

W jj will provide very accurately the E-scale at intermediate

energies but systematics rise at the low and high end of spectrum

Z to jet balance can reach higher energies and || (even the forward) systematics are very high at low energies, but above 60 GeV

the 1% requirement seems possible can offer separate calibration of b-jets can transfer calibration across calorimeters can check the linearity of calorimeter (TeV values at the

endcap and forward regions)


Finally...Finally...

Test beam/ single particles and/or electronics Test beam/ single particles and/or electronics calibration to set the cell at the EM scalecalibration to set the cell at the EM scale

transfer to modules not tested where needed

Assign a detector Monte-Carlo that describes Assign a detector Monte-Carlo that describes well the observed with particleswell the observed with particles

remember the high E end..

Work on the machinery for jet/hadrons Work on the machinery for jet/hadrons reconstruction/calibration (even if not final reconstruction/calibration (even if not final choices) and keep flexiblechoices) and keep flexible

no best algorithm or best calibration scheme NOW be ready to try any useful data

In situ calibration cross-check at LHC start (only In situ calibration cross-check at LHC start (only feasibility studies and predictions now)feasibility studies and predictions now)

in situ intercalibration also

Jets and Hadrons Calibration Strategy in ATLAS Ir e ne Vichou University of Athens

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