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High-p T probes of QCD matter

High-p T probes of QCD matter. Marco van Leeuwen, Utrecht University. Plan of Lecture IV. Yesterday’s summary:. Best achievable goal: determine P( D E) experimentally. (Or at least some features of it). Difficult in practice: R AA (at RHIC) not sensitive

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High-p T probes of QCD matter

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  1. High-pT probes of QCD matter Marco van Leeuwen, Utrecht University

  2. Plan of Lecture IV Yesterday’s summary: Best achievable goal: determine P(DE) experimentally (Or at least some features of it) Difficult in practice: RAA (at RHIC) not sensitive IAA limited sensitivity (fragmentation bias) Today’s lecture: • New approaches to reduce fragmentation bias • Multi-hadron correlations • g-jet measurements at RHIC and LHC • Jet measurements at LHC Mix of existing results and ideas for future

  3. pQCD illustrated fragmentation jet spectrum ~ parton spectrum CDF, PRD75, 092006

  4. Naive picture for di-hadron measurements Out-of-cone radiation: PT,jet2 < PT,jet1 In-cone radiation: PT,jet2 = pT,jet1 Softer fragmentation Fragment distribution (fragmentation fuction) Ref: no Eloss PT,jet,1 PT,jet,2 Naive assumption for di-hadrons: pT,trig measures PT,jet So, zT=pT,assoc/pT,trig measures z

  5. Fragmentation bias in di-hadrons Test case: Calculate away-side spectra Use two different frag functions LEP: Quarks: D(z) ~ exp(-8.2 z) Gluons: D(z) ~ exp(-11.4 z) pTa pTt Away-side spectra not sensitive to slope of fragmentation function More detailed analysis shows: mainly depends on power n of partons spectrum

  6. Di-jet triggered analysis pTt1 pTa1 a.u. Raw, uncorrected signal 0.6 0.4 pTt2 0.2 -2 -1 2 0 1 3 4 5 Df T1T2 correlation O. Barannikova, F. Wang, QM08 Idea: use back-to-back hadron pair to trigger on di-jet and study assoc yield T1: pT>5 GeV/c T2: pT>4 GeV/c p±0.2 Tune/control fragmentation biasand possibly geometry/energy loss bias di-hadron trigger pairs contain combinatorial background

  7. 3-hadron analysis backgrounds ZDC central Au+Au 12% a.u. T1T2 Signal + Background Background Signal 0 4 2 Df (T1T2) 2 1 _dN_ Ntrigd(Df ) -2 -1 2 0 1 3 4 5 T2A1_T1 flow subt. pTt1 T1A1 T2A1 1 pTa1 0 pTt2 STAR Preliminary Df (T2A1) T1: pT>5GeV/c, T2: pT>4GeV/c, A: pT>1.5GeV/c O. Barannikova, F. Wang, QM08 Subtract two combinatorial terms: random T1, random T2

  8. Di-jet triggered in d+Au d+Au 200 GeV -2 -1 2 0 1 3 4 5 pTt1 pTa1 pTt1 pTa1 pTt2 T1: pT>5 GeV/c, T2: pT>4 GeV/c, A: pT>1.5 GeV/c O. Barannikova, F. Wang, QM08 1 _dN_ Ntrigd(Df ) T2A1_T1 T2A1 Di-jet trigger 2 1 0 STAR Preliminary Df (T2A1) Requiring away-side trigger increases yield Fragmentation bias changes: higher Q2 Single hadron trigger

  9. Di-jet triggers in Au+Au Single trigger: broad away-side Di-jet trigger: jet peaks on both near and away side -2 -1 2 0 1 3 4 5 pTt1 pTa1 pTt1 pTa1 pTt2 Df T1: pT>5 GeV/c, T2: pT>4 GeV/c, A: pT>1.5 GeV/c Di-jet trigger 1 _dN_ Ntrigd(Df ) 4 central 0-12% T2A1_T1 T2A1 2 0 Single hadron trigger STAR Preliminary -2 Di-jet trigger selects different events, has different bias

  10. Au+Au vs d+Au comparison 200 GeV Au+Au, 12% central 1 _dN_ Ntrigd(Df ) STAR Preliminary 200 GeV Au+Au & d+Au T1A1_T2 T2A1_T1 1 _dN_ Ntrigd(Df ) STAR Preliminary Au+Au d+Au 2 3 2 0 1 0 -2 -2 -1 -1 2 2 0 0 1 1 3 3 4 4 5 5 Df Df T1: pT>5 GeV/c, T2: pT>4 GeV/c, A: pT>1.5 GeV/c Distributions wrt to both triggers similar Au+Au similar to d+Au Di-jet trigger selects jet pairs with little or no energy loss

  11. Di-jet trigger model calculation Renk, Phys. Rev. C 75, 054910 (2007) <DE> for back-to-back jets T1 Thorsten Renk, private comm. 2 density models T2 Model agrees: ptT1 ~ ptT2 reduces energy loss Next step: increaseptT1 - ptT2

  12. Multi-hadron cluster triggers R Seed Associated track Secondary Seeds Idea: Reduce fragmentation bias by clustering hadrons ‘proto-jet’ Away-side spectrum 0-12% Au+Au Add 12-15 GeV trigger B. Haag, QM08 Multi-hadron trigger STAR Preliminary Use cluster energy for trigger: - R = 0.3 - pT,seed > 5 GeV - pT,sec seed > 3 GeV Single-hadron and multi-hadron triggers give similar result Fragmentation bias does not change? - Needs further study

  13. Probing the photon energy with g-jet events  T. Renk, PRC74, 034906 Nuclear modification factor Away-side spectra in g-jet Eg = 15 GeV RAA insensitive to P(DE) Away-side spectra for g-jet are sensitive to P(DE) g-jet: know jet energy  sensitive to P(DE)

  14. g-jet in Au+Au Use shower shape in EMCal to form p0 sample and g-rich sample Combinatorial subtraction to obtain direct-g sample

  15. Away-side suppression with direct-g triggers A. Hamed et al QM08 First g-jet results from heavy ion collisions are becoming available* Measured suppression agrees with theory expectations Next step: measure pTassoc dependence to probe DE distribution * both PHENIX and STAR

  16. Large Hadron Collider at CERN CMS 2008: p+p collisions @ 14 TeV 2009: Pb+Pb collisions @ 5.5 TeV ALICE ATLAS 3 Large general purpose detectors ALICE dedicated to Heavy Ion Physics, PID p,K, out to pT > 10 GeV ATLAS, CMS: large acceptance, EM+hadronic calorimetry

  17. From RHIC to LHC RHIC: s=200 GeV Au+Au LHC: s=5.5 TeV Pb+Pb Pion spectra Hard process yields much larger at LHC 10k/year (orders of magnitude at high-pT) Most abundant probe: jets, light hadrons Robust yields to pT>200 GeV for jets Larger initial density Validate understanding of RHIC data

  18. RAA at LHC GLV BDMPS T. Renk, QM2006 RHIC RHIC S. Wicks, W. Horowitz, QM2006 LHC: typical parton energy > typical E Expected rise of RAA with pT depends on energy loss formalism Nuclear modification factor RAA at LHC sensitive to radiation spectrum P(E)

  19. Medium modification of fragmentation MLLA calculation: good approximation for soft fragmentation extended with ad-hoc implementation medium modifications Borghini and Wiedemann, hep-ph/0506218 pThadron ~2 GeV for Ejet=100 GeV =ln(EJet/phadron) z 0.37 0.14 0.05 0.02 0.007 Trends intuitive: suppression at high z, enhancement at low z Recent progress: showering with medium-modified Sudakov factors, see Carlos’s talk and arXiv:0710.3073

  20. Jet modifications at LHC Jet reconstruction Expectations from QCD+jet quenching PQM with fragmentation of radiated gluons (A. Morsch) Fragmentation function Radial profile Ejet = 125 GeV Energy loss depletes high-zand populates low-z Low-z fragments from gluon radiation at large R =ln(EJet/phadron)‏ z 0.37 0.14 0.05 0.02 0.007 In-medium energy loss redistributes momenta in jets Model has the main phenomenology included; use as benchmark

  21. Need for a calorimeter Jet energy response ALICE PPR, part II 100 GeV Jets R=0.4 Note: tail due to jet-splitting Charged particle tracking only sees ~50 % of jet energy TPC+EMCal recovers large fraction of jet energy Moreover: EMCal provides important trigger capability

  22. ALICE EMCal US-France-Italy project ALICE-EMCal project: • Approved in 2007 • Full detector by 2011 EMCal module Testbeam: Support frame installed Lead-scintillator sampling calorimeter ||<0.7, =110o ~13k towers (x~0.014x0.014)‏ Improves jet energy resolution Provides jet triggers

  23. Jets in heavy ion events Simulation: 100 GeV jet in Hijing Finding jets is relatively easy Energy (GeV) • Challenges: • Measuring the energy in presence of cuts to reduce background • Reconstructing lower energy jets, jets with softer fragmentation

  24. Reducing the background 80% PYTHIA pTcharged>30 GeV HERWIG pTcharged>5 GeV 80% Radial distribution of jet energy Charged background energy fluctuations no pt -cut pt > 2 GeV/c • saturation model scaling (Eskola et al, hep-ph/0506049) CDF, PRD65, 092002 (2002) CDF: ~80% of jet energy contained in R < 0.2 Apply pT-cut to reduce background Use smaller cone size, e.g. R=0.4 to reduce bkg Disadvantage: Not infrared safe • Background from 5.5 TeV Pb+Pb: • dET/dh ~ 3700 GeV, ET(R<0.2) ~ 75 GeV

  25. Small cones: split jets Reconstructed energy Split jet fraction all particles, R=0.3, pT > 2GeV # Jets R=0.3, pt>2GeV all particles charged+pi0 charged • input • - Njets,rec=1 • - Njets,rec>=1 highest jet • Njets,rec>=1 mid-cone • - Njets,rec>=1 sum Fraction of events Njets,rec.>1 Jet Energy (GeV) Jet Energy (GeV) Jet-splitting affects energy recnstruction Jet shape fluctuate; need stable algorithm (infrared safe?) Possible solutions: SISCone, anti-kT Still lots of room to improve jet-finding in heavy ions (if you’re interested, let me know)

  26. Full jet reconstruction performance Simulation input reference Simulated result Medium modified (APQ)‏ Full jet reco in ALICE is sensitive to modification of fragmentation function E > E, explore dynamics of energy loss process

  27. Under Study: Di-jet Correlations Acoplanarity pp PbPb: PYQUEN T = 1 GeV charged jets J. Casalderrey-Solana and XNW, arXiv:0705.1352 [hep-ph]. BDMPS Effect seems to be measurable, but large effect from initial state radiation

  28. g-jet rates at RHIC and LHC g, p0 rates Jacak, Vogelsang, QM06 gdirect/gdecay small at LHC: ~10% at 100 GeV Challenging measurement: g/p < 0.1 in accessible kinematic region

  29. Identifying prompt g in ALICE signal  5 Backgrounds are large, need isolation cut • pp • R = 0.3, SpT < 2 GeV/c • Efficiency: 69% • Background rejection: 1/170 • PbPb • R = 0.2, pTthresh = 2 GeV/c • Efficiency: 50% • Background rejection: 1/14

  30. Summary/conclusions • Goal of high-pT measurements (my opinion) • Measure/constrain P(DE) • Detemine medium properties • Dominant limitations of current measurements: • Fragmentation bias: single, di-hadron not very sensitive to P(DE) • At RHIC: DE ~ Ejet • Promising new measurements: • g-jet at RHIC and LHC • jet reconstruction at LHC (maybe also at RHIC) Experimental methods and theory understanding are under continuous development Make sure you don’t miss out!

  31. Heavy-ion backgrounds Background energy fluctuations Jet cone energy pT > 2 GeV ALICE PPR Vol II 100 GeV 50 GeV Dominant source: Impact parameter fluctuations already taken out for these plots 50 GeV jets: need to restrict cone size >100 GeV jets: can use larger size (R=0.5-1) Note: also here large uncertainty: multiplicity and mean-pT can only be guessed

  32. Getting at the jet energy Simulations: Pythia 6.319 (CDF tune A) ‘Ideal’ jets reconstructedusing all final state particles Cone algorithm R=1 Ejet = SpT • Jet energy contributions: • 65% in charged particles • 20% EM (mostly p0) • Small contributions from K0L , neutrons, etc (approx -1 leading particle) + Long tails Leading particle ~15 %

  33. Jets on a steep spectrum Leading particle: mostly lower limit on jet energy (+finite ‘efficiency’ at larger pT) Charged jets: ‘sharp’ turn-on. Still mainly lower cut at RHIC Charged+EM selects narrow range in E-jet at RHIC & LHC Caveat: energy loss may transport energy outside cuts (cone, pT)

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