Jets at CMS Fedor Ratnikov, University of Maryland MIT, August 1, 2008.

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Presentation transcript:

Jets at CMS Fedor Ratnikov, University of Maryland MIT, August 1, 2008

August 1, 2008Jet reconstruction at CMS. F.Ratnikov2 Introduction I am in CMS JetMET POG since 2005 –Since beginning of the CMSSW era Exclusively responsible for design and implementation of jet reconstruction chain, as well as for design and implementation of Jets Energy Corrections machinery Involved into and support most ongoing Jet activities Jet contact for the CMS RECO group

August 1, 2008Jet reconstruction at CMS. F.Ratnikov3 Credits CMS Jet/MET DPG is a big team This presentation includes results obtained by different people –A.Anastassov, A.Bhatti, V.Buege, J.Cammin, F.Chlebana, R.Harris, S.Essen, O.Kodolova, K.Kousouris, A.Nikitenko, A.Oehler, D. del Re, G.Salam, M.Zielinski

August 1, 2008Jet reconstruction at CMS. F.Ratnikov4 Outline Why jets are tricky Jet reconstruction algorithms –General requirements –Algorithms used at CMS –Performance Jet flavors: CaloJets GenJets, PFJets Jet reconstruction software design Resolution, efficiency Jet Energy Corrections –Generic design –Supported corrections Summary

August 1, 2008Jet reconstruction at CMS. F.Ratnikov5 Basic Reconstructed Physics Objects p p partons particles tracker calorimeter HCAL ECAL muon detector     e,e, e,e, e q,g  0, ,  *,  … ±,,,e,±,,,e, 

August 1, 2008Jet reconstruction at CMS. F.Ratnikov6 Requirements to Jet Algorithms Jet 1Jet 2 Collinear Safety Jet is lost  Infrared Safety Jets are merged  Procedure must be stable with respect to reasonable variations of the energy pattern

August 1, 2008Jet reconstruction at CMS. F.Ratnikov7 Jet Algorithms Iterative Cone –Seeded –Single pass - fast –IR 2 unsafe, collinear unsafe CDF Midpoint Cone –Seeded –With split/merge passes –IR 3 unsafe, collinear unsafe

August 1, 2008Jet reconstruction at CMS. F.Ratnikov8 Jet Algorithms (cont) k T –Seedless –N 3  N·ln(N) - fast –IR, collinear safe Seedless Infrared Safe Cone (SISCone) –Seedless –N 4  N 2 ·ln(N) - Reasonably fast –IR, collinear safe CMS routinely uses –IC R=0.5 –SISC R=0.5, R=0.7 –k T D=0.4, D=0.6

August 1, 2008Jet reconstruction at CMS. F.Ratnikov9 Midpoint Cone vs SIS Cone CMS switched to using SISCone instead of Midpoint Cone recently

August 1, 2008Jet reconstruction at CMS. F.Ratnikov10 Comparing Jet Properties IC 0.5 KT 0.4 SISC 0.5 Jet reconstruction efficiency Jet energy resolution

August 1, 2008Jet reconstruction at CMS. F.Ratnikov11 Algorithms Speed SIS Cone R=0.5 Midpoint Cone R=0.5 Iterative Cone R=0.5 K T D=0.4 # of inputs CPU time (ms)

August 1, 2008Jet reconstruction at CMS. F.Ratnikov12 CaloJets Baseline for Jet reconstruction at CMS Input is CaloTower –Mostly follow HCAL granularity –Contains few HCAL cells and many (25 in the barrel) ECAL cells Ecal Hcal Tower Calo Tower Hcal Center CaloJets include information about electromagnetic fraction, energies deposited in different subdetectors etc. Produce CaloJets for every approved algorithm –Part of “RECO” sequence People are free to run own jet algorithm on CaloTowers –Necessary information is available in all standard datasets

August 1, 2008Jet reconstruction at CMS. F.Ratnikov13 GenJets Clustering energies of MC level particles Include “invisible” particles? –Muons –Neutrinos –SUSY, if any Current approach –Include all “invisible” except ones from prompt decays of gauge bosons Produce GenJets for every approved algorithm –Part of “post SIM” sequence People are free to make own selection of MC particles and run jet algorithm on them –Necessary information is available in all standard datasets

August 1, 2008Jet reconstruction at CMS. F.Ratnikov14 PFJets +  +0 0+  +0 0 PFCandidate combines information from various detectors to make the best combined estimation of particle properties PFJet is made from PFCandidates and contains information about contributions of every particle class: –Electromagnetic/hadronic –Charged/neutral

August 1, 2008Jet reconstruction at CMS. F.Ratnikov15 Jet Reconstruction at CMS Factorize algorithms and jet flavors –Algorithms treat inputs as set of 4-momenta –Flavor specific pre/postprocessing are shared by all algorithms inputs Generic Candidates (Lorentz Vectors) Jet reconstruction Algorithm protojet flavor specific Jets event flavor specific algorithm specific

August 1, 2008Jet reconstruction at CMS. F.Ratnikov16 HI Specifics HI events are huge on particle level Not a big deal for CaloJets –Not more than ~5K fired CaloTowers anyway Big deal for GenJets –One event - 35K particles –SISCone killer (remember: N 2 LnN algorithm) 40 min of CPU time 30 Gbytes of memory In most cases just crashes the reconstruction job –k T survives: takes ~20 sec of CPU time

August 1, 2008Jet reconstruction at CMS. F.Ratnikov17 Event By Event Pileup Subtraction FASTJET approach –Applicable to IR safe algorithms only, any jet flavor –Calculate jet area by ghost method Put extra very small ghost energies into nodes of  -  grid –Assume pileup jet area proportional to p T –Use low p T jets to derive PU energy density –Estimate high p T jets PU contribution using PU energy density and jet area CMS approach –Applicable to any algorithm, CaloJets only –Run regular jet reconstruction –Get average energy in CaloTowers outside reconstructed jets in every  ring –Subtract that energy from CaloTowers contributing to the jet –Re-calculate jet parameters using corrected energies of contributing towers

August 1, 2008Jet reconstruction at CMS. F.Ratnikov18

August 1, 2008Jet reconstruction at CMS. F.Ratnikov19 JetArea/PU Subtraction Costs

August 1, 2008Jet reconstruction at CMS. F.Ratnikov20 Jet Energy Scale Jet corrections –Generic: applied to all jets –Optional: fine tuning for specific jet types/hypothesis Factorized (chained) corrections approach Different jet correctors are services in CMSSW –Chained corrector is a service on top of individual correctors Use cases: –Producers to apply corrections to all jets, produce new jet correction –Use correction services directly from analysis modules –Use simple corrections (not including extra event information) from FWLite/ROOT scripts

August 1, 2008Jet reconstruction at CMS. F.Ratnikov21 L1: Offset/Zero Suppression Offset in Jet Area In Calorimeter Pile-up Noise

August 1, 2008Jet reconstruction at CMS. F.Ratnikov22 L2: Relative to Barrel ( , p T ) No assumptions about  symmetry

August 1, 2008Jet reconstruction at CMS. F.Ratnikov23 Measuring Relative Scale: Dijet Balance Utilize p T conservation for dijet events Use dedicated calibration triggers to collect dijet events Before Corrections After Corrections

August 1, 2008Jet reconstruction at CMS. F.Ratnikov24 L3: Absolute Scale (p T )

August 1, 2008Jet reconstruction at CMS. F.Ratnikov25 Measuring Absolute Scale:  /Z Balance Utilize p T conservation for  -jet and Z(  )-jet events Rescale back from parton level to particle level using MC Precision  -jet balance for 1 fb -1 Statistics for 1 fb -1

August 1, 2008Jet reconstruction at CMS. F.Ratnikov26 L4: Electromagnetic Fraction Corrects uncompensated Calorimeter response  P T vs. EMF in P T Bins  P T vs. EMF in  Bins

August 1, 2008Jet reconstruction at CMS. F.Ratnikov27 L5: Flavor Corrections Scales jet energy to particle level –Needs jet flavor hypothesis a priori

August 1, 2008Jet reconstruction at CMS. F.Ratnikov28 Track Corrections 1.Reconstruct calorimeter jet 2.Subtract expected response of “in-calo-cone” tracks from calo jet E T and add track momentum jet E T and add track momentum 3.Add momentum of “out-calo-cone” tracks tracks

August 1, 2008Jet reconstruction at CMS. F.Ratnikov29 Conclusions Jet reconstruction in CMS is mature –Infrastructure is stable for years –Bells and twisters still being added, further polishing Infinite process anyway –Algorithms to be used in CMS analysis are established At least for the beginning of data taking –Still flexible enough to accommodate special desires for special analysis Jet calibrations are ready for data taking –MC based corrections for the very beginning of data taking –Calibration data samples and procedures to extract corrections from data (10pb -1, 100pb -1 scenarios)

BACK UP SLIDES

August 1, 2008Jet reconstruction at CMS. F.Ratnikov31 CMS Detector

August 1, 2008Jet reconstruction at CMS. F.Ratnikov32 Jet Energy Clusterization We are mostly interested to reconstruct parton level objects parameters basing on visible measurables –Direct measurements for muons –Corrections for bremsstrahlung / conversion for electrons and photons –Multiple steps conversions for quarks/gluons: original partons  hadronization into long living particles  showering in EM and HAD calorimeters  measured energies –Original parton is seen as energy cluster in the calorimeter (and tracker), a.k.a. Jet –Algorithms for energy clusters search a.k.a. Jet Reconstruction

August 1, 2008Jet reconstruction at CMS. F.Ratnikov33 FastJet Package Stand alone C++ package supported by G.Salam&Co Contains –Fast implementation of k T algorithms family –SISCone –Ancient: MidPoint, JetClu, etc. –Newer: anti-kt Provide bridges –Between different experiments –Between experiments and theory CMS uses FastJet for k T, SISCone

August 1, 2008Jet reconstruction at CMS. F.Ratnikov34 Jet Area May be well defined for IR safe algorithms only