1. Elena Bruna Yale University
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
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
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 – f x 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 pT or 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
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 pT cut on tracks and towers
r (GeV/area)
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
R=0.4: significant energy recovered, but visible trend
R=0.2: jet energy not fully recovered in small R
p+p: jet more collimated with increasing jet pT
Au+Au: suggests strong broadening of the energy profile

10. Lessons from di-jets and FF
STAR Preliminary
ratio of di-jet spectra AuAu/pp
ratio of Fragmentation Functions AuAu/pp
STAR Preliminary
pt,rec(AuAu)>25 GeV
⇒ < pt,rec(pp)> ~ 25 GeV
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”
No significant modification of FF of recoil jets with pTrec>25 GeV
Dominated by non-interacting jets?

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