New STAR jet measurements and their implications for EMCal trigger and offline

New STAR jet measurements and their implications for EMCal trigger and offline

Peter Jacobs, LBNL

EMCAl Meeting Nantes, July 15-17 2008 Jet probes of the Jet in STAR and EMCal 1

EMCAl Meeting Nantes, July 15-17 2008

Jet probes of the Jet in STAR and EMCal

2

This talk is almost entirely about recent analysis of STAR data on full jet reconstruction in central Au+Au data

based on Hard Probes talks by Sevil Salur and Joern Putschke plus additional material from Mateusz Ploskon

Important lessons for ALICE EMCal jet program: trigger and offline

STAR jet spectrum

3

STAR: published inclusive jet for √s=200 GeV p+p has statistical reach beyond 40 GeV: based on 0.2 pb-1.

STAR 2007 Au+Au 200 GeV dataset ~ 5 pb-1 “p+p equivalent”: jets must be there!!

Phys. Rev. Lett. 97 (2006) 252001

Systematic uncertainty ~50% due to trigger xsections

Unbiased jet reconstruction in AuAu: cross section must scale as Nbinary relative to p+p

Jet reconstruction algorithms



4

5

Jets and the presence of underlying event

= Diffuse noise, = noise fluctuations

STAR Preliminary

Au+Au Central

Fact from the data:• 200 GeV central Au+Au: R=0.4 → Bkg Energy ~ 40 GeV

Backgrounds estimated event by event.

Cone: Look at <pT> out-of jet cones A=πR2

Sequential Recombination: Estimate the active area of each jet by addition of zero energy particles of known density.M. Cacciari, G. Salam, G. Soyez 0802.1188 [hep-ph]

MP, 18th of June 2008 STAR @ UC Davis 6

Resolution and backgrounds: Pythia jets embedded in real Au+Au events

LOHSC KT CAMBpTcut =1 GeV

R=0.4

Seed=4.6 GeV

Cou

nts

∆E ∆E ∆E

Event by event comparison of PyTrue vs PyDet vs PyEmbed.

pTcut =1 GeV

R=0.4pT

cut =1 GeV R=0.4

ST

AR

P

relim

inar

y

ST

AR

P

relim

inar

y

ST

AR

P

relim

inar

y

ET=35±5 GeV ET=35±5 GeV ET=35±5 GeV

E = EPyDet – EpyTrue Shift of median due to un-measured particles (n, K0

L) and the pT cut.E = EPyEmbed – EpyDet Smearing due to background subtraction in Au+Au.E = EPyEmbed - EPyTrue Tail at positive ∆E causes a kick in the spectrum.


Jet spectrum: effects of energy resolution and pT cut

Increase pT threshold: Reduce the effect of background fluctuations jet reconstruction in 0-10% Au+Au is similar in p+p

However, the pT cut introduces (strong) biases…

Similar effects observed for KT & Cambridge/Aachen

pTcut

=0.1 GeV

dNJe

t/dE

T (

per

even

t)

LOHSC

seed=4.6 GeVR=0.4

PyDetPyEmbedPyTrue

PyDetPyEmbedPyTrue

PyDetPyEmbedPyTrue

pTcut

=1.0 GeV

LOHSC

seed=4.6 GeVR=0.4

LOHSC

seed=4.6 GeVR=0.4

ET [GeV]

STAR Preliminary STAR Preliminary STAR Preliminary

pTcut

=2.0 GeV


Jet areas and background fluctuations

• Au+Au bkgd: reduction in area & increase in fluctuations• Pythia jets embedded in real Au+Au bkgd: same area and fluctuations as real Au+Au jets• Cacciari+Salam: understood analytically – prefer anti-kT and SISCone algorithms

Cou

nts

MB-trigPyEmbedPyTrue

R=0.4

KT pT cut = 0.1 GeV

Jet Area

Cou

nts

STAR Preliminary

Jet ET> 20 GeV

Au+Au 0-10%

Background Fluctuations

R=0.4KT

pT cut = 0.1 GeV

MB-trigPyEmbedPyTrue

Sigma

STAR Preliminary

Au+Au 0-10%

M. Cacciari, G. Salam, G. Soyez 0802.1188 [hep-ph]

Jet Area

9

Cross section compared to binary-scaled p+p

Two Au+Au online trigger conditions:

• MB-Trig: minimum-bias, offline centrality selection (no EMC tower cuts)

•HT-Trig: ET>7.5 GeV in 3x3 EMC tower cluster

Inclusive spectrum correction based on PYTHIA

ET [GeV]

dNJe

t/dE

T (

per

even

t) Nbin scaled p+p

Au+Au 0-10%

MB-TrigO HT-Trig

R=0.4pT

cut =1 GeVSeed=4.6 GeV

LOHSC

Statistical Errors Only

• MB-Trig: Good agreement (within errors) with binary-scaled p+p → unbiased jet reconstruction?

•HT-Trig: large trigger bias persists beyond 30 GeV → use with caution!

Conclusion: MB-Trig is essential for unbiased measurement good news: factor ~20 more on tape than shown here! (QM2009…)

10

Scaling for sequential recomb. w/ low pT cut

Also good agreement with binary-scaled p+p!Interesting because:

• seedless algorithms: no seed bias• pT>100 MeV (!): minimal pT cut bias• spectrum correction factors (much) closer to unity

ET [GeV]dN

Jet/d

ET (

per

even

t)ET [GeV]

dNJe

t/dE

T (

per

even

t)

Au+Au 0-10%

STAR Preliminary

R=0.4pT

cut =0.1 GeV

KT


Au+Au 0-10% STAR Preliminary

R=0.4pT

cut =0.1 GeV

CAMB


Nbin scaled p+p Nbin scaled p+p

MB-TrigO HT-Trig

MB-TrigO HT-Trig

11

Imprecise subtraction of underlying event?How sensitive are we to fragmentation model in corrections (PYTHIA) ?

Systematics of pT-cut bias

11

STAR Preliminary

PT Cut

KT

LOHSC

Au+Au 0-10% MB-Trig Nbin Scaled p+p

LOHSC LOHSC

KT KT

STAR Preliminary STAR Preliminary STAR Preliminary

ST

AR

Pre

limin

ary

Au+Au 0-10%



ST

AR

Pre

limin

ary

ST

AR

Pre

limin

aryAu+Au 0-10%

MB-Trig Nbin Scaled p+p




Next step: medium modification of the fragmentation function

13

FF for PYTHIA jet in centralAu+Au bkgd

14

FF for Central Au+Au (data) Jet ET > 30 GeV

15

FF: compare p+p to central Au+Au (HT-trig)

ξ not corrected for ET shift due to quenchingneed quenching model + “data-driven” cross checks (gamma+jet, dijet)

Provisional conclusion: apparently no medium-induced FF modification!but consistent with HT-trig being highly biased (require 7.5 GeV 0 in jet)

Factor 20 more MB-trig data on tape – crucial to analyse it!

Dijets in central Au+Au data



16

From HT-trig sample

Dijet azimuthal and energy balance: p+p vs central Au+Au



17

Clear di-jet signal for ET> 20 GeV

• utilize ET-balance for model-independent measurement of resolution? → already in progress for STAR p+p

data• acoplanarity may be the most fundamental jet quenching measurement

MP, 19th of June 2008 STAR @ DAVIS 18

Theory remarks U. Wiedemann, HP08

New jet observable: subjet distributions



19

Look at multiplicity of “subjets” as fn of Durham/Cambridge metric:

222 cos1,min2 CMijjiij EEEy K. Zapp, U. Wiedemann et al, arXiv:0804.3568

medium-enhanced jet splitting

Lessons from STAR jet measurements for ALICE EMCal

20

The (very) good news: • significant theory progress in reconstruction algorithms (Salam, Cacciari, et al.), driven largely by high lumi p+p but of great utility for heavy ions • jet reconstruction over heavy ion backgrounds appears to work well…much better than expected?

But strong biases evident due to• Cluster triggers• Seeded jet reco algorithms• pT cuts on tracks contributing to jets

→ need to be careful with triggers and reco algorithms – you will always get what you ask for but perhaps not what you want

Lessons for EMCal II

21

EMCal jet trigger: large patch clearly essential• revisit with modern quenching MCs (JEWEL,…) tuned on STAR data (available Sept ’08?)

Offline jet reco: •Standard seeded algorithm is sub-optimal• unseeded algorithms clearly prefered: FastJet package (anti-kT, SISCone are optimal)

Crucial to develop “data-driven” calibrations of jet reco in heavy ion collisions:

• +jet• Revisit Z+jet? 100 central Pb+Pb events already useful• Utilize geometric bias: hard 0+jet?

….

Lessons for EMCal III

22

Medium-induced modification of Fragmentation Function is a tricky measurement

• has been useful benchmark but perhaps not the first generation of jet quenching measurements?• how good is theoretical control?

→ consider new, theoretically well-controlled observables, e.g. subjet distributions (well studied at LEP)


Jet probes of the Jet in STAR and EMCal 23

Extra slides

24

One of the critical issues: background fluctuations – LOHS Cone











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New STAR jet measurements and their implications for EMCal trigger and offline

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