David Berge – CAT Physics Meeting – 9 May Summary Hadronic Calibration Workshop 3 day workshop 14 to 16 March 2008 in Tucson, Arizona Session topics: 1)Monte Carlo / testbeam validation 2)Local hadronic calibration 3)Jet energy scale 4)Missing E T Selected highlights follow

David Berge – CAT Physics Meeting – 9 May Monte Carlo / Testbeam Validation Summary and numbers: –Geant4 plus hadronic interaction model QGSP (“Quark Gluon String Punchthrough”) with Bertini nucleon-nucleon cascade validated and recommended for ATLAS NOTE: Currently available fully simulated samples have QGSP only, without Bertini –Alternative fragmentation (Fritjof) does describe certain aspects of the data well, could be used for studying systematics in case parts of the full simulation samples are available with both QGSP and Fritjof (space is limited)!

David Berge – CAT Physics Meeting – 9 May Monte Carlo / Testbeam Validation Summary and numbers: –Tile numbers: Pion response (1-2%) and resolution (5%) well described Longitudinal/lateral pion shower shapes within 10% Proton longitudinal shower shape problematic: 20-40% too short

David Berge – CAT Physics Meeting – 9 May Monte Carlo / Testbeam Validation Summary and numbers: –Hadronic Endcap (HEC): Response and resolution described by QGSP, but showers too short If Bertini switched on, longitudinal shower development ok Response is ok after Birks law and time convolution –Combined testbeam: Response within 2%, resolution in MC too good

David Berge – CAT Physics Meeting – 9 May Jets Very instructive invited talk: “Theoretical aspects of jet finding” (Gavin Salam)Theoretical aspects of jet finding See also: –hep-ph/ –hep-ph/ –hep-ph/

David Berge – CAT Physics Meeting – 9 May Jets

David Berge – CAT Physics Meeting – 9 May Jets

David Berge – CAT Physics Meeting – 9 May Jets So he claims ATLAS cone is not very meaningful for many processes Not sure what our comment would be

David Berge – CAT Physics Meeting – 9 May Jets

David Berge – CAT Physics Meeting – 9 May Jets Again I’m not really sure how to interpret this I’d expect his definition of “failure rate” differs from what I would call a failure of a jet algorithm

David Berge – CAT Physics Meeting – 9 May Jets Introduced the concept of jet areas as another jet observable Infinitely soft ghost particles are added uniformly to the event, the number of ghosts ending up in a jet measures the area Contamination of hard jets from minimum bias interactions is found to scale with the jet area –Proposes to use the jet area for pile-up subtraction They provide C++ jet-finding library (FastJet), featuring a range of algorithms, including jet area calculationsFastJet –Library linked to ATLAS software in rel 14 for different jet algorithms Jet transverse momentum vs. area, for Pythia LHC dijet event with 22 minimum bias interactions

David Berge – CAT Physics Meeting – 9 May Jets in ATLAS Two variants: 1.Tower jets –Towers are formed based on constituents defined in x space –Noise contributions cancel out, are not suppressed (that is, towers with negative signals are joined with adjacent ones until the signal is positive) 2.Cluster jets –Topological cell clusters are formed based on calorimeter cells with noise cut 4/2/0 (seed/neighbor/perimeter) –Noise is actually suppressed, topo clusters are real energy blobs in 3D –Noise cuts depend on pile-up

David Berge – CAT Physics Meeting – 9 May Jets in ATLAS Main algorithms: 1.Seeded (1 GeV) fixed cone (usually R=0.4 or 0.7), with split-and-merge procedure after all stable cones are found (overlap fraction 50%) 2.Fast kt implementation, usually with distance parameter 0.4 or 0.6 But also configurable: –MidPoint –Optimum jet finder –SISCone in future via FastJet external library

David Berge – CAT Physics Meeting – 9 May Hadronic Calibration in ATLAS 1.Global –Reconstruct hadronic final state objects from towers or clusters at electromagnetic energy scale –Then calibrate jets to particle level in one step, based on (the H1) weights determined from simulations – these weights absorb all detector effects 2.Local –Reconstruct calorimeter clusters and calibrate them to hadronic energy scale, in separate steps for weights and detector corrections –Reconstruct hadronic final state based on the calibrated (!) calorimeter signals

David Berge – CAT Physics Meeting – 9 May Jet Reconstruction Flow

David Berge – CAT Physics Meeting – 9 May Global vs. Local Jet Calibration Kristin Lohwasser

David Berge – CAT Physics Meeting – 9 May Global vs. Local Jet Calibration Kristin Lohwasser

David Berge – CAT Physics Meeting – 9 May Global vs. Local Jet Calibration Global calibration: –Robust for different samples, though difference visible –Restores energy very well –Improved resolution Local calibration: –Can be split and validated in separate steps –Still missing jet corrections on top of calorimeter calibration Kristin Lohwasser

David Berge – CAT Physics Meeting – 9 May Global vs. Local Jet Calibration Local calibration seems to be the preferred choice, despite currently better performance In any case, we need collision data to decide on final recommendation for jet calibration Local calibration outstanding issues –Better treatment of Tile gap cells –Improve out-of-cluster corrections –Improve dead-material corrections –Use jet moments for residual corrections on jet level –Make local calibration pile-up aware

David Berge – CAT Physics Meeting – 9 May Usage of Tracks for Hadronic Reconstruction D.Miller, A.Schwartzman, Su Dong

David Berge – CAT Physics Meeting – 9 May Usage of tracks to select Jets in the Presence of Pile-Up They also plan (ambitiously) to use the JVF for a jet-energy correction to correct for pile-up contributions on a per-jet basis, and to correct missing ET… Jet multiplicity using JVF A flat hard-scatter jet multiplicity distribution is recovered cutting on the JVF Of course crucial for any analysis related to jet multiplicity D.Miller, A.Schwartzman, Su Dong

David Berge – CAT Physics Meeting – 9 May Usage of Tracks to Improve the Jet Energy Resolution Use tracking information to extract information about jet topology, fragmentation, and charged particle distribution Apply track-based energy response corrections Does not require additional jet energy scale corrections, but the track corrections are applied after full energy scale corrections and produce improved jets at the same overall energy scale A.Schwartzman Correlation of jet response with pT(trk)/pT(cal) Also presented track multiplicity, fraction of leading track pT, track maximum opening angle

David Berge – CAT Physics Meeting – 9 May Usage of Tracks to Improve the Jet Energy Resolution Use tracking information to extract information about jet topology, fragmentation, and charged particle distribution Apply track-based energy response corrections Does not require additional jet energy scale corrections, but the track corrections are applied after full energy scale corrections and produce improved jets at the same overall energy scale A.Schwartzman

David Berge – CAT Physics Meeting – 9 May Other interesting topics Missing ET validation from data Results from cosmics (M5/M6) Jet-energy scale validation from data Pile-up, pile-up, pile-up Check the agenda:

David Berge – CAT Physics Meeting – 9 May Backup

David Berge – CAT Physics Meeting – 9 May SISCone Algorithm