1 / 29

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

remedios-valdez
Télécharger la présentation

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

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. New STAR jet measurements and their implications for EMCal trigger and offline Peter Jacobs, LBNL 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 SevilSalur and JoernPutschke plus additional material from Mateusz Ploskon • Important lessons for ALICE EMCal jet program: trigger and offline Jet probes of the Jet in STAR and EMCal

  3. STAR jet spectrum Phys. Rev. Lett. 97 (2006) 252001 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!! Unbiased jet reconstruction in AuAu: cross section must scale as Nbinaryrelative to p+p Systematic uncertainty ~50% due to trigger xsections

  4. Jet reconstruction algorithms Jet probes of the Jet in STAR and EMCal

  5. Jets and the presence of underlying event • 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] STAR Preliminary Au+Au Central    = Diffuse noise,  = noise fluctuations

  6. Resolution and backgrounds: Pythia jets embedded in real Au+Au events Event by event comparison of PyTruevsPyDetvsPyEmbed. Seed=4.6 GeV pTcut =1 GeV R=0.4 KT pTcut =1 GeV R=0.4 CAMB LOHSC pTcut =1 GeV R=0.4 Counts ET=35±5 GeV ET=35±5 GeV ET=35±5 GeV STAR Preliminary STAR Preliminary STAR Preliminary ∆E ∆E ∆E E = EPyDet – EpyTrue Shift of median due to un-measured particles (n, K0L) 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. STAR @ UC Davis

  7. Jet spectrum: effects of energy resolution and pT cut pTcut=0.1 GeV pTcut=1.0 GeV pTcut=2.0 GeV seed=4.6 GeV seed=4.6 GeV seed=4.6 GeV R=0.4 R=0.4 R=0.4 LOHSC LOHSC LOHSC dNJet/dET (per event)‏ PyDet PyEmbed PyTrue PyDet PyEmbed PyTrue PyDet PyEmbed PyTrue STAR Preliminary STAR Preliminary STAR Preliminary ET [GeV] 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 STAR @ UC Davis

  8. Jet areas and background fluctuations M. Cacciari, G. Salam, G. Soyez 0802.1188 [hep-ph] Jet Area Background Fluctuations Au+Au 0-10% Au+Au 0-10% Counts MB-trig PyEmbed PyTrue MB-trig PyEmbed PyTrue Counts Jet ET> 20 GeV pT cut = 0.1 GeV KT KT R=0.4 R=0.4 pTcut = 0.1 GeV STAR Preliminary STAR Preliminary Jet Area Sigma • Au+Aubkgd: reduction in area & increase in fluctuations • Pythiajets embedded in real Au+Aubkgd: same area and fluctuations as real Au+Aujets • Cacciari+Salam: understood analytically – prefer anti-kT and SISCone algorithms STAR @ UC Davis

  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 Nbin scaled p+p Au+Au 0-10%  MB-Trig O HT-Trig dNJet/dET (per event)‏ LOHSC R=0.4 pT cut =1 GeV Seed=4.6 GeV 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…) ET [GeV]

  10. Scaling for sequential recomb. w/ low pT cut STAR Preliminary STAR Preliminary Nbin scaled p+p Nbin scaled p+p Au+Au 0-10% Au+Au 0-10%  MB-Trig O HT-Trig  MB-Trig O HT-Trig dNJet/dET (per event)‏ dNJet/dET (per event)‏ KT CAMB R=0.4 pT cut =0.1 GeV R=0.4 pT cut =0.1 GeV Statistical Errors Only Statistical Errors Only ET [GeV] ET [GeV] • Also good agreement with binary-scaled p+p! • Interesting because: • seedless algorithms: no seed bias • pT>100 MeV (!): minimal pTcut bias • spectrum correction factors (much) closer to unity

  11. Systematics of pT-cut bias Au+Au 0-10%MB-Trig Nbin Scaled p+p Au+Au 0-10%MB-Trig Nbin Scaled p+p Au+Au 0-10%MB-Trig Nbin Scaled p+p STAR Preliminary LOHSC LOHSC LOHSC STAR Preliminary STAR Preliminary STAR Preliminary Au+Au 0-10% Au+Au 0-10%MB-Trig Nbin Scaled p+p Au+Au 0-10%MB-Trig Nbin Scaled p+p Au+Au 0-10%MB-Trig Nbin Scaled p+p STAR Preliminary STAR Preliminary STAR Preliminary KT KT KT PT Cut 11 Imprecise subtraction of underlying event? How sensitive are we to fragmentation model in corrections (PYTHIA) ?

  12. Next step: medium modification of the fragmentation function STAR @ UC Davis

  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) • ξnot corrected for ET shift due to quenching • need 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 GeVp0 in jet) • Factor 20 more MB-trig data on tape – crucial to analyse it!

  16. Dijets in central Au+Au data From HT-trig sample Jet probes of the Jet in STAR and EMCal

  17. Dijet azimuthal and energy balance: p+p vs central Au+Au • 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 Jet probes of the Jet in STAR and EMCal

  18. Theory remarks U. Wiedemann, HP08 STAR @ DAVIS

  19. New jet observable: subjet distributions Look at multiplicity of “subjets” as fn of Durham/Cambridge metric: K. Zapp, U. Wiedemann et al, arXiv:0804.3568 medium-enhanced jet splitting Jet probes of the Jet in STAR and EMCal

  20. Lessons from STAR jet measurements for ALICE EMCal • 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

  21. Lessons for EMCal II • 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: • g+jet • Revisit Z+jet? 100 central Pb+Pb events already useful • Utilize geometric bias: hard p0+jet? • ….

  22. Lessons for EMCal III • 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)

  23. Extra slides Jet probes of the Jet in STAR and EMCal

  24. One of the critical issues: background fluctuations – LOHS Cone

  25. Jet probes of the Jet in STAR and EMCal

  26. Jet probes of the Jet in STAR and EMCal

  27. Jet probes of the Jet in STAR and EMCal

  28. Jet probes of the Jet in STAR and EMCal

  29. Jet probes of the Jet in STAR and EMCal

More Related