1. Inclusive jet cross-sections and correlations in Au+Au and p+p collisions at sqrt(s NN ) = 200 GeV Mateusz Ploskon For the STAR Collaboration

2. Outline Motivation and strategy Datasets, jet algorithms, correction schemes Observables – Inclusive jet cross-section + Jet R AA – Jet “radius” systematics – (di-)Hadron-jet recoil spectrum and Jet I AA Discussion: implications for jet quenching 2Mateusz Ploskon (LBNL), STAR, QM'09

3. Motivation and Strategy 1 Cross-section ratio AuAu/pp Physics of full jet reconstruction in heavy ion collisions p+p Au+Au Energy shift? Absorption? R=0.4 Measure energy flow into “cone” of radius R o Total momentum is conserved even for strongly quenched jets o Unbiased jet reconstruction: recover the full jet energy within cone radius R o Compare Au+Au and p+p jet spectra o → Inclusive cross section: RAA jet ~1 o →  0 +jet conditional yield: IAA jet ~1 o Caveat: initial state nuclear effects 3Mateusz Ploskon (LBNL), STAR, QM'09 R RJet

4. Data sets Essential requirement: minimize trigger bias of jet population Inclusive spectrum data: – Au+Au (2007): online MinBias Trigger offline select 10% most central events (8 x 10 6 events) – p+p (2006): online “Jet Patch” trigger (int lumi 6.5 pb^-1) offline correct bias at low ET h+jet coincidence data: – Both p+p (2006) and Au+Au (2007): Online “BEMC High Tower” trigger Offline: hadron trigger energy from 3x3 tower cluster (ET>7 GeV) Track and Tower cuts: – BEMC towers energy > 0.2 GeV – TPC track momentum pT > 0.2 GeV/c 4Mateusz Ploskon (LBNL), STAR, QM'09

5. Jet algorithms Algorithms: k t and anti-k t from FastJet* – Resolution parameter R = 0.4, 0.2 – Jet acceptance: |  JET | < 1.-R – Recombination scheme: E-scheme with massless particles *Cacciari, Salam and Soyez, JHEP 0804 (2008) 005 [arXiv:0802.1188] Anti-k t expected to be less susceptible to background effects in heavy ion collisions 5Mateusz Ploskon (LBNL), STAR, QM'09 Sequential recombination algorithms Sequential recombination algorithms Cone based algorithms Cone based algorithms

6. Systematic corrections Trigger corrections – p+p trigger bias correction Particle level corrections: – Detector effects: efficiency and pT resolution – “Double* counting” of particle energies * electrons: - double; hadrons: - showering corrections All towers matched to primary tracks are removed from the analysis Jet level corrections: Spectrum shift: – Unobserved energy – TPC tracking efficiency BEMC calibration (dominant uncertainty in p+p) Jet patch trigger efficiency (only in p+p) Jet pT resolution Underlying event (dominant uncertainty in Au+Au) Full assessment of jet energy scale uncertainties Data driven correction scheme Weak model dependence: only for single-particle response, p+p trigger response No dependence on quenching models 6Mateusz Ploskon (LBNL), STAR, QM'09

7. Heavy Ions and background characterization 7Mateusz Ploskon (LBNL), STAR, QM'09

8. STAR Preliminary Au+Au Central   Underlying event 8 Single di-jet event from a central Au+Au: - Two jet peaks on top of the HI background Single di-jet event from a central Au+Au: - Two jet peaks on top of the HI background Event background is characterized with median p T per unit area (  ). in R = 0.4 is ~45 GeV/c. S/B~0.5 at 20 GeV/c. Event background is characterized with median p T per unit area (  ). in R = 0.4 is ~45 GeV/c. S/B~0.5 at 20 GeV/c. Central assumption: Signal and background can be factorized Central assumption: Signal and background can be factorized with resolution: True jet distribution smeared:  DATA ~ 6.8 GeV True jet distribution smeared:  DATA ~ 6.8 GeV Mateusz Ploskon (LBNL), STAR, QM'09 Systematic studies indicate variation of sigma +/-1 is a conservative bracketing of systematic uncertainties. Error bands indicate these limits. Systematic studies indicate variation of sigma +/-1 is a conservative bracketing of systematic uncertainties. Error bands indicate these limits.

9. Fake jet contamination “Fake” jet rate estimation: Central Au+Au dataset (real data) Randomize azimuth of each charged particle and calorimeter tower Run jet finder Remove leading particle from each found jet Re-run jet finder “Fake” jets: signal in excess of background model from random association of uncorrelated soft particles (i.e. not due to hard scattering) STAR Preliminary 9Mateusz Ploskon (LBNL), STAR, QM'09

10. Fake jet contamination “Fake” jet rate estimation: Central Au+Au dataset (real data) Randomize azimuth of each charged particle and calorimeter tower Run jet finder Remove leading particle from each found jet Re-run jet finder STAR Preliminary 10Mateusz Ploskon (LBNL), STAR, QM'09 “Fake” jets: signal in excess of background model from random association of uncorrelated soft particles (i.e. not due to hard scattering)

11. Spectrum unfolding: method Background non-uniformity (fluctuations) and energy resolution introduce pT- smearing Correct via “unfolding”: inversion of full bin-migration matrix Check numerical stability of procedure using jet spectrum shape from PYTHIA Procedure is numerically stable Correction depends critically on background model → main systematic uncertainty for Au+Au Procedure is numerically stable Correction depends critically on background model → main systematic uncertainty for Au+Au unfolding 11Mateusz Ploskon (LBNL), STAR, QM'09 Pythia Pythia smeared Pythia unfolded

12. Spectrum unfolding Corrections for smearing of jet p T due to HI backround non- uniformities 1) raw spectrum STAR Preliminary 12Mateusz Ploskon (LBNL), STAR, QM'09

13. Spectrum unfolding Corrections for smearing of jet p T due to HI backround non- uniformities 1) raw spectrum 2) removal of “fake”- correlations STAR Preliminary 13Mateusz Ploskon (LBNL), STAR, QM'09

14. Spectrum unfolding Corrections for smearing of jet p T due to HI backround non- uniformities 1) raw spectrum 2) removal of “fake”- correlations 3) unfolding STAR Preliminary 14Mateusz Ploskon (LBNL), STAR, QM'09

15. Spectrum unfolding Corrections for smearing of jet p T due to HI backround non- uniformities 1) raw spectrum 2) removal of “fake”- correlations 3) unfolding 4) correction for p T resolution STAR Preliminary 15Mateusz Ploskon (LBNL), STAR, QM'09

16. Jet yields in p+p at sqrt(s NN ) = 200 GeV 16Mateusz Ploskon (LBNL), STAR, QM'09

17. Inclusive jet cross-section in p+p at sqrt(s NN ) = 200 GeV o Fully corrected jet cross-section reconstructed with kt algorithm o Very good agreement between the algorithms STAR Preliminary 17Mateusz Ploskon (LBNL), STAR, QM'09 Uncertainty due to BEMC calibration

18. Inclusive jet cross-section in p+p at sqrt(s NN ) = 200 GeV Comparison to published STAR data – run 2003/2004 Note: – published data reconstructed with different jet algorithm: Mid-point cone (R=0.4) STAR Preliminary 18Mateusz Ploskon (LBNL), STAR, QM'09 Phys. Rev. Lett. 97 (2006) 252001

19. Inclusive jet yields in 10% most central Au+Au at sqrt(s NN ) = 200 GeV 19Mateusz Ploskon (LBNL), STAR, QM'09

20. Inclusive jet yields in 10% most central Au+Au at sqrt(s NN ) = 200 GeV o Fully corrected jet spectrum o Exactly the same algorithms and jet definitions used as compared to p+p o Bands on data points represent estimation of systematic uncertainties due to background subtraction STAR Preliminary 20Mateusz Ploskon (LBNL), STAR, QM'09 Uncertainty due to BEMC calibration

21. Inclusive jet spectrum: p+p and central Au+Au (R=0.4 and R=0.2) p+p Au+Au central STAR Preliminary 21Mateusz Ploskon (LBNL), STAR, QM'09

22. Cross-section ratios in p+p and Au+ Au with R=0.2/R=0.4 p+p: “Narrowing” of the jet structure with increasing jet energy Au+Au: Strong broadening of the jet energy profile 22Mateusz Ploskon (LBNL), STAR, QM'09 STAR Preliminary p+p Au+Au Many systematics effects cancel in the ratio

23. Nuclear modification factor for jets 23Mateusz Ploskon (LBNL), STAR, QM'09

24. R = 0.4 5% uncertainty on BEMC calibration o Significant energy recovered as compared to R AA ~0.2 for hadrons o Visible trends: o different sensitivity of the algorithms o Central values drop as a function of jet p T STAR Preliminary 24Mateusz Ploskon (LBNL), STAR, QM'09 R AA Jets

25. R AA Jets and Energy flow in smaller “cone” radii Significant drop of R AA as a function of jet p T for R=0.2 as compared to R=0.4 Jet energy not fully recovered in small “cones” – shift towards lower p T Significant drop of R AA as a function of jet p T for R=0.2 as compared to R=0.4 Jet energy not fully recovered in small “cones” – shift towards lower p T 25Mateusz Ploskon (LBNL), STAR, QM'09 STAR Preliminary R=0.4 R=0.2

26. Hadron-jet coincidences 26Mateusz Ploskon (LBNL), STAR, QM'09

27. Di-hadron – jet correlations 27 Yield per trigger STAR, PRL 97, 162301 (2006)  STAR high pT dihadrons: bias towards non- interacting jet population A A B B Recoil Mateusz Ploskon (LBNL), STAR, QM'09

28. Hadron+jet coincidence 1 Cond. yield ratio AuAu/pp p+p Au+Au Energy shift? Absorption? R=0.4 o Trigger on hard, leading   (p T >6 GeV/c) o 3x3 tower cluster in BEMC o Construct spectrum of recoil jets o normalized per di-hadron trigger This event selection will maximize the recoil path length distribution in matter Conditional yield 28Mateusz Ploskon (LBNL), STAR, QM'09 R R Jet

29. H – recoil jet coincidences A A B p T > 0.5 GeV/c Recoil jet A A B p T > 6 GeV/c Recoil jet Use jet fragmentation bias to vary jet path length distribution? 29Mateusz Ploskon (LBNL), STAR, QM'09

30. H – recoil jet coincidences A A B B STAR Preliminary 30Mateusz Ploskon (LBNL), STAR, QM'09 (Au+Au: 10% central) Anti-kt R=0.4

31. H – recoil jet coincidences STAR Preliminary 31Mateusz Ploskon (LBNL), STAR, QM'09 (Au+Au: 10% central) Anti-kt R=0.4 A A B B

32. H – recoil jet coincidences STAR Preliminary 32Mateusz Ploskon (LBNL), STAR, QM'09 (Au+Au: 10% central) Anti-kt R=0.4 A A B B

33. H – recoil jet coincidences STAR Preliminary 33Mateusz Ploskon (LBNL), STAR, QM'09 (Au+Au: 10% central) Anti-kt R=0.4 A A B B Significant suppression of the bias free recoil jet spectrum

34. STAR Preliminary Summary o Qualitatively new measurement of jet quenching in terms of energy flow (rather than hadronic observables) has been established o What we have shown: o Minimum bias dataset: RAA~0.5 or larger o Significant broadening of jet energy profile R=0.2 -> R=0.4 o Strong suppression of recoil jet rate at maximum path-length o Consistent interpretation: o quenching induces jet broadening o R=0.4 (with the presented jet definitions) is insufficient for unbiased reconstruction 34Mateusz Ploskon (LBNL), STAR, QM'09 STAR Preliminary Au+Au 10% central R Au+Au 10% central

35. Outlook Rich new set of observables to confront calculations New MC jet quenching models (qPythia, JEWEL, T. Renk) New jet algorithms for HI collisions? – Post-processing – integration of significant energy flow outside the “initial” jet areas (however probably hard to calculate/resolve theoretically 35Mateusz Ploskon (LBNL), STAR, QM'09

36. Extra slides 36Mateusz Ploskon (LBNL), STAR, QM'09

37. Spectrum unfolding - correction for smearing of jet p t due to bg nonuniformities R=0.4 R=0.2 37Mateusz Ploskon (LBNL), STAR, QM'09