Jet Reconstruction in Athena Atlas Calorimeter Energy Calibration Workshop Ringberg Castle 23/07/02 Ambreesh Gupta, University of Chicago Outline : Introduction Athena : The Atlas Software Framework Jet Reconstruction Tau Reconstruction Energy Flow Summary

People Involved Martine, Monika, Peter, Ed, Srini, Tom, Hong, Jim, Jon, Frank, Frank… The group of people involved in jet reconstruction in the atlas software framework - People interested can join the JetRec bi-weekly telephone meeting at 5 pm CERN time on Wednesdays.

pp q q Initial Parton in Hard Scattering Reconstructed Jet in Calorimeter ISR/FSR Fragmentation Underlying Event e/  Dead material Magnetic field Electronic Noise Pile Up Event Properties Detector Effects LHC Design  s = 14 TeV L = cm -2 sec -1 Collision Every 25ns 23 Interaction/Collision The challenge is to identify reconstructed jet with the initial parton : Nontrivial

Goal of Hadron Calorimetry:. Resolution 50%/  E  3%.. Jet Scale 1%.

The Steps of Jet Measurement Jet Measurement can be broadly divided in three steps Jet Reconstruction Energy Calibration Flavor Identification Energy deposit in the calorimeter is clustered by Jet reconstruction algorithms, e.g Cone and Kt. Energy of a Jet is calibrated for non-compensation, dead material, magnetic field, etc. b-tag,  -tag, etc.

Athena : The Atlas Software Framework Transient Event Data Store Transient Detector and Calibration Data Store Algorithm A Algorithm B Algorithm C Framework Philosophy: Data Classes are Stable, Algorithms Change. User Can Plug in New Algorithms. Framework Provides Services: Execute, Monitor and Output From Algorithms.

Jet Reconstruction Package CalCell CaloCluster Tracks CaloTower Many Kind of Input Data MC Truth Many Kind of Algorithms Cone Kt Cluster ….. ProtoJet Energy Flow Abstract The Inputs For Algs ProtoJet Class:. Can be created for different sub system.. Homogenous.

Jet Reconstruction Package Cone Kt Cluster ….. Jet Jet Reconstruction Algorithms Jet Class:. Jets are composed of ProtoJet. Provide Mechanism to deal with Overlapped Jets.. Provide mechanism to deal with Recombination Schemes. Energy Correction Algorithms Sampling Based Correction H1 Style Correction Jet Working with data abstractions is great but the information lost is required by correction Algorithms…..

Navigating Composite Objects Problem Statement : Given a Jet made of ProtoJet – How do I know what kind of CaloCell (LAr,Tile,etc.) are they made of ? Jet PJet Tower Cell JetToken PJetToken TowerToken CellToken Record structural pattern in Tokens. Access them through special processor classes.

Available Tools and Packages There are many ‘Packages’ that help in Jet Reconstruction. The three listed below are the typical names associated with, jet, tau and energy flow reconstruction -. JetRec. tauRec. eflowRec

JetRec

Jet Algorithms Jet algorithms are employed to map final states, both in QCD pert. theory and in the data, onto jets. The motivating idea is that these jets are surrogates for the underlying energetic parton. Cone jetK T jet Clustering - hadrons, Calorimeter Cells,Towers etc., for nearness… Nearness in angle => Cone Algorithm. Nearness in relative transverse momentum => Kt algorithm. Historically hadron collider use cone algorithms : easier calibration Recombination Scheme - The momentum addition rule of particles in a jet.

Cone Algorithm Cluster particles within a radius R =  2  2. Cone iterated until a stable Et weighted cone is achieved. Possible to produce overlapped cones – Needs a Split-Merge step. Various version of cone algorithm dealing with issues of speed and theoretical uncertainty. Implementation of a seedless cone and split-merge algorithm in JetRec. Configurable through jobOption file. Chrono services provided by Athena time profile algorithms. Average reconstruction time for 1 GeV jet ~ 0.7 sec. 1/  E GeV -2  /E

Kt Algorithm Cluster “particles” in order of increasing relative transverse momentum. Requires a method to terminate clustering. The algorithm is O(n 3 ) => Pre-Cluster particles. No overlapping Jets. Theoretically well behaved by design. Implementation of one Pre-Cluster and kT algorithm in JetRec. Reco time for 1000 GeV jet. Apply an Et cut of 100 MeV => 200 input ProtoJet. Average time ~1 sec.. Not Et cut => 800 input ProtoJet. Average time ~ 1 min. 1/  E GeV -2  /E

Energy Correction Algorithms Various method of energy correction used by Atlas in studies – Parametric minimization, in-situ, e/h. Setup of example algorithm to do energy correction - weights taken from earlier studies (Lefevre & Santoni, Martine) - iterative procedure to approximate the true energy for parameters - use Navigation packages. The correction improves both linearity and resolution, but not in exact match with earlier studies. New studies with H1 style calibration … see later  /E 1/  E GeV -2

tauRec

Tau Reconstruction Identify Cluster Associate Tracks to Cluster Calibrate Cluster Tau ID cuts A Sliding Window algorithm with window 0.5x0.5 Three highest p T tracks with p T > 2 GeV And within  R < 0.4 1) H1 style calibration 2) Hadronic calibration Variables to distinguish hadronic tau decays from QCD jets. 20 fold reduction in bkg. with 50% acceptance for SUSY signal. Tau’s have unique importance in SUSY searches. Reconstruction Steps :

Hadronic Calibration (Used in Physics TDR) Weights derived from single pion Corrects the overall energy scale but does not give optimal resolution.

H1 Type Calibration Makes use of the fact that hadronic showers are more localized than EM showers. Derive weights in bins of Et for each layer - EM3, Tile and HEC No weights for EM1, EM2. Minimize function : With constraint : Samples of single pion with p T = 10, 20, 40, 80, 160 GeV were used.

Calibrated E T /P T (  ) vs  H1 weights) Pion resolution with H1 weights much better than fixed weights.  /E = 38.56%/  E  3.56% Applying the H1 weights to the reconstructed tau events gave significant improvement in both the average response and the resolution.

Extending H1 style Tau Calibration to Jets. Jet35 sample was chosen for this study. 35 GeV dijet sample with :. pT ( hard.scat. ) > 35 GeV.. Electron rich trigger. To compare to MC, same jet reconstruction algorithm applied to ProtoJets generated from Truth in ATLFAST. Calibration weights re-derived for this sample. Since sample is dominated by low Et jets, f(E T ) chosen to be – f(E T ) = E T 2

Comparing Et/Et,MC kt Jet : Mean close to 1. Increases with Jet Et cut. Resolution curves show tails in gaussian fit. Fits fairly well with double gaussian. cone Jet : Mean close to 1. Similar to above, increases with jet Et cut. Tails, substantially reduced compared to above.

E T /E T (MC) after calibration ( kT jet )

Fitted H1 weights for Jets BinW(EM2)W(EM3)W(Tile)W(HEC) 0= = Cryo term = 0.471*  (E EM3 * E Tile ) Gap weight = E T Bins = 1/32, 1/16, 1/8, … 16 GeV

Investigating the Tails Possible effect of miss measurement of jet energy due to magnetic field studied by taking in to account of tracks that sweep in(out) of the jet. Cleaner Jet sample ( without electron rich trigger ) for several E T bins being requested for further studies on the tails. No noticeable change.

eflowRec

Energy Flow Concept Introduced first by LEP experiments led to significant improvement in jet energy resolution. The idea is simple but challenge to realize – requires building the particle ID associated with the track. This starts running in to difficulties in high track multiplicity environment and coarse calorimeter granularity. Basic Idea : The well measured particle momentum substitutes random fluctuation of energy in the calorimeter => better resolution.

Energy Flow Package ECALHCAL neutral charged eflowRec is a first attempt to combine calorimeter, tracking and PID information to improve energy resolution for jet and E T Miss Tracks and cluster matched in  and  ( neutral particle ) and using helix parameter of tracks ( charged particles ) to form topologically connected eflow objects. Subtract expected energy deposit in EM and Had cluster. Loop over the remaining EM clusters and subtract expected energy in HCAL clusters Loop over tracks Estimated based on the particle ID hypothesis. Algorithm flow :

Plans : eflowRec Combined muon algorithm as input. Brem recovery and conversion finding. PID internal to eflowRec. 3D cluster reconstruction. Limitation at present due the availability of full PID packages. Various choices to be made: Need MC studies to constraint. scalar sum pT missing pT x-comp. missing pT y-comp. of missing pT

Summary The jet reconstruction setup in Athena is fairly mature. The important things that should be on the priority are – documentation and a setup to test and validate released code in a simple way. New studies in calibration studies driving the software setup to produce the right tools. Progress in tau reconstruction and H1 style calibration. First implementations of an Energy Flow package available in Athena. Please send comment/suggestions to the jets-combined mailing list or join the bi-weekly phone meetings for further details.