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1 physics reaction of interest (parton level) lost soft tracks due to magnetic field added tracks from in-time (same trigger) pile-up event added tracks from underlying event jet reconstruction algorithm efficiency detector response characteristics (e/h ≠ 1) electronic noise dead material losses (front, cracks, transitions…) pile-up noise from (off-time) bunch crossings detector signal inefficiencies (dead channels, HV…) longitudinal energy leakage calo signal definition (clustering, noise suppression,…) jet reconstruction algorithm efficiency Approach to jet reconstruction needs to emphasize factorization of calibrations and corrections contributing to the jet energy scale! Ingredients to jet reconstruction in calorimeters
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2 Jet calibration strategies JES HES-1 Local, correct effect/effect, relies only on MC, check with pions in TB Needed for refined studies Compute MC weights that minimize Ereco- Etrue Can be used at the start Calo domain Jet domain Physics domain Used in ATHENA HES-2
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3 Method based on longitudinal energy deposit 1. Sampling Calibration (Frank Merritt, Jimmy Proudfoot, AG; Chicago) - Weights calorimeter layers (w i ) = f(Jet energy, eta) - 8 or less parameters per fit depending on eta and energy. Methods based on energy density – Uses detailed cell information → more parameters in the fit 1. H1-Style (Frank Paige, BNL) – two steps procedure - Cell weights (w i ) = f(Cell energy density) - Apply extra correction factor function of Ejet and eta to improve linearity and uniformity. 2. Pisa Calibration (Chiara Roda, Iacopo Vivarelli, Andrea Dotti, Pisa) - Cell weights (w i ) = f(Cell energy density, Jet energy) - Similar idea as above, use extra info of jet energy. 3. Psuedo H1 (Sanjay Padhi, Wisconsin) - Similar as H1-style. Not yet ready to provide jet energy scale. Use g/Z+jet or di-jets to determine H1 weights and not MC … Jet calibration: HES
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4 On average 25% of jet energy is EM Response of the Calorimeter to a jet will depend on the spectrum of its particle constituents. Particle constituents of a jet
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5 Response in Eta Response in Energy Sources of non-linearity and energy fluctuations jet fragmentation e/h cracks/gaps/dead material B field effects clustering effects electronic noise underlying event/pile up On average about 2/3 of jet energy is in EM calorimeter Calorimeter response to jet
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6 EM If not a MIP, a deposits most of its energy in the EM calorimeter. Need to multiply by the overall jet energy scale f( ,EM+cryo+Had) to 100 GeV Endcap: E(EM+Had) = rec. E. Is it by chance for 100 GeV pion ? energy deposit in calorimeters(1) Ex: charged pions (#7406 with 11.0.41) E=100 GeV, <2.5: Rec. E (GeV) E / Rec. E *”Had” calibrated a la H1 **E(EM)<5 GeV Note: Hadronic shower lateral size:15 to 20 cm E (GeV) EM Had* Rec. =96.5 GeV with jet cal ! cryo α√E S3 + E S1 E(EM+cryo+Had) =91.2 GeV No MIPs** EM Had* cryo all E/100 GeV Rec. “bump” due to MIPs**. Wide because of hadronic fluctuations Had EM No MIPs** No consistant with Etmiss
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7 MIPs vs reflects the EM thickness variation: from 1.2 ( =0) to 2 ( =1.4), 1.4-1.6 (EMEC) energy deposit in calorimeters(2) Ex: charged pions (#7406 with 11.0.41) E=100 GeV, <2.5: MIPs** in EM(%) Rec. **E(EM)<5 GeV
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8 Jet energy deposit in calorimeters Main difference between jet and charged pions: no MIPs and 1/3 of 0 in the jet. Therefore, hadronic calorimeters are reduced to tail catchers (very important one !). Ratio HAD/EM is lower than for single pion in the barrel Rec. E (GeV) E / Rec. E E (GeV) Rec. Ex: tt Wb Wb jjb jjb (#5204 with 11.0.41) p T >30 GeV, | |<2.5 EM* Had* cryo* *Variables etEM, etHad, energyInCryostat in ParticleJet EM* Had* cryo* all E(EM+cryo+Had) =130 GeV In the endcap, higher energetic jets explains the reduction of EM component
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