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Lessons from STAR

This presentation at the EMCal Offline Meeting discusses the lessons learned from the STAR experiment, including jet finders, systematic errors, hadronic and e± corrections, background fluctuations, fake jets, and di-jet analysis.

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Lessons from STAR

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  1. Lessons from STAR Elena Bruna Yale University EMCal Offline Meeting, Frascati May 21st 2009

  2. ALICE vs STAR BEMC: -1<h<1 0<f<2p TPC: -1<h<1 0<f<2p EMCal: -0.7<h<0.7 80<f<190° TPC: -0.9<h<0.9 0<f<2p

  3. Jet Finders in STAR • kT, Anti-kT, SISCone (from FastJet package): • Anti-kT expected to be less sensitive to background effects in heavy ion collisions. • R=0.4, R=0.2 • Jet acceptance |hjet|<1-R • Recombination scheme: E-scheme with massless particles • pT,cut =0 GeV on tracks/towers (pTcut =2 GeV  biased jet sample) • Cuts at particle level: • 0.1< pT(tracks) <20 GeV/c (upper limit to reduce space-charge effects) • E(towers)>150 MeV

  4. Systematic errors / corrections in STAR • Systematic errors: • Hadronic corrections • Double counting of electrons • BEMC calibration • Tracking efficiency, pT resolution • Corrections in spectra and fragmentation functions • Jet pT resolution (detector effect + missing energy) • Fake jets (dominant in Au+Au) • Background fluctuations (dominant in Au+Au)

  5. Hadronic and e± corrections in STAR • At “Reader” level (i.e. before feeding the Jet =Finders) • Hadronic avoid double counting of hadronic energy (pT + hadronic shower) • On the BEMC towers that match TPC tracks • Possible to set the fractional energy to be subtracted: Etower=Etower – fx ptrack (f =100% used) • Electron avoid double counting of e± energy (pT + e.m. shower) • On the BEMC towers that match TPC e± candidates tracks • Keep only track pTor keep only tower E or Etower=Etower – √(pel2+mel2) • e± id: p/E + SMD cluster size + min<dE/dx<max

  6. Event background in Au+Au at STAR r (GeV/area) • Event-by-event basis: • pT (Jet Measured) ~ pT (Jet) + r A ± s √A • r = median pT per unit area • A = jet area • rA  estimated and subtracted (by FastJet) • Background energy in R=0.4 ~ 45 GeV • Substantial region-to-region • background fluctuations • width = s √A(from FastJet) • Comparable in magnitude with • naïve random cones⇒ significantly reduced by applying • a pTcuton tracks and towers AuAu √s=200 GeV STAR Preliminary Multiplicity STAR Preliminary Background fluctuations [Gev] Rc

  7. Fake jets at STAR • Fake jets = background particles clustered as jets • Background model dependent • In inclusive measurements: • Randomize azimuth of each charged track and calorimeter tower • Run jet finder • Remove leading particle from each jet • Re-run jet finder • In di-jet analysis: • “Fake” + Additional Hard Scattering contribution in HI Collisions • Use “jet” spectrum at 90° to correct for “fake” di-jets

  8. Corrections at work • Raw spectrum • Correction for “fake” jets • Unfolding bkg fluctuations (s~6.8 GeV) • Correction for jet pT resolution

  9. Lessons from cross sections and RAA • p+p: jet more collimated with increasing jet pT • Au+Au: suggests strong broadening of the energy profile • R=0.4: significant energy recovered, but visible trend • R=0.2: jet energy not fully recovered in small R

  10. Lessons from di-jets and FF ratio of di-jet spectra AuAu/pp ratio of Fragmentation Functions AuAu/pp • Biased to extreme path length of recoil (High-Tower triggered ev.) • Significant suppression seen • Energy shifts to larger cone radii (>0.4) • Some Jets “absorbed” pt,rec(AuAu)>25 GeV ⇒ < pt,rec(pp)> ~ 25 GeV STAR Preliminary • No significant modification of FF of recoil jets with pTrec>25 GeV • Dominated by non-interacting jets? STAR Preliminary

  11. FastJet analysis in ALICE • Hadronic corrections  done. • From STAR: Flexibility, i.e. different correction schemes to study systematic errors (no, MIP, fractional). Can we do this in ALICE? • e± double counting  foreseen, in progress. Flexibility in PID cuts? • Background: r (magnitude)and s (fluctuations) • From STAR: (1) r and s estimated by FastJet on an event-by-event basis. Doable in ALICE with the EMCal acceptance? Use only TPC tracks? Out-of-cone areas? To be studied. • From STAR: (2) medium broadens jets, most likely also out of R=0.4 How to deal with possibly spread jets in ALICE-EMCal? To be studied • Is a statistical background subtraction needed? • Fake jets: • From STAR: (1) randomizing azimuth of tracks and towers (2) “jet” spectrum at 90° w.r.t. di-jet axis • Can we do (1) and (2) in ALICE-EMCal acceptance? To be studied.

  12. Summary • Lessons from STAR: • possible bias with pTcut on tracks/towers  analysis done also with no pTcut • broadening of jets in Au+Au w.r.t. p+p  need to explore jet energy profile, sub-jets, etc. • Useful for the PPR to evaluate the ALICE-EMCal capability in handling the critical aspects found by STAR

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