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From yesterday

Explore the properties of jets in heavy ion collisions through jet tomography techniques, investigating the parton energy loss, kinematics, and medium response. Analyze results from RHIC and LHC experiments.

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From yesterday

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  1. Why jets in heavy ion collisions? Jet Tomography! • Jet quenching observed at RHIC & LHC via single high-pT hadron and di-hadrons • Access kinematics of the binary hard-scattering • Characterize the parton energy loss in the hot QCD medium • Study medium response to parton energy loss Jet I: Intro & Motivations From yesterday • Jet-finding connects Theory and Experiment • Many Jet Finders on the market •  need to be collinear/infrared safe • Choice of R matters Jet II: Full Jet Reconstruction Elena Bruna (Yale&INFN Torino)

  2. Jet-finding connects Theory and Experiment • Many Jet Finders on the market •  need to be collinear/infrared safe • Choice of R matters • Goal: set the Jet Energy Scale • Different systematics to take into account (tracking,…) • Background fluctuations: the challenge Jet II: Full Jet Reconstruction Today and tomorrow Jet III: Results Jet IV: The Present: from RHIC to LHC Elena Bruna (Yale&INFN Torino)

  3. Jets in Heavy-Ion Collisions at RHIC and LHC Central Au+Au √sNN=200 GeV Central Pb+Pb√sNN=2.76 TeV ALICE tracking data STAR preliminary STAR EMC + tracking data ETjet ~ 21 GeV • Why measure jets in heavy ion collisions? [inclusive, di-jets, jet-hadron, g-jet,..] • Access kinematics of the binary hard-scattering • Characterize the parton energy loss in the hot QCD medium • modified fragmentation, energy flow within jets, quark vs gluon jet difference • flavor and mass dependence • Study medium response to parton energy loss – establish properties of the medium Elena Bruna (Yale&INFN Torino)

  4. p+p JP trigger ATLAS Nov/Dec 2009 ~ 21 GeV Jets in p+p RHIC p+p @ √s = 200 GeV √s=2.36 TeV Jet p+p pt per grid cell [GeV] η ϕ Tevatron: CDF @ √s = 1.8 TeV STAR Preliminary p+p: the reference measurement  need well calibrated probes Elena Bruna (Yale&INFN Torino)

  5. Jet-finding and systematics.. Hadronic and electron double counting • Electrons and hadrons can deposit • energy in the EMC and leave tracks in • the TPC. • Be aware of double counting! • Avoid double counting (p+p and A+A): • remove EMC towers that match to an electron • remove fraction f of tower energy for tower that match to hadrons choice of f to be determined by experiment. f=100%, MIP,… Elena Bruna (Yale&INFN Torino)

  6. Jet Energy resolution – the Jet Energy Scale PYTHIA: p+p √s=200 GeV X axis=Pythia jet pT (Particle Level) Y axis=Pythia thru STAR detector simulation (Detector Level) • Reconstructed Jet pT on average smaller than the Input (PYTHIA) jet pT • The reconstructed jet pT is smeared • Need to know (1) and (2) to correct the measured jet pT back to the “true” jet pT Can use PYTHIA to determine the jet energy resolution Elena Bruna (Yale&INFN Torino)

  7. Jet-finding and systematics.. Tracking efficiency [Remark: PYTHIA is OK for p+p. Data-driven correction scheme preferred for A+A] Charged jet component has to be corrected for the pT dependent tracking efficiency: ε(pT)= tracking efficiency pT,hi= single track transverse momentum N = # of jet constituents Simulation: p+p @ 5.5 TeV in ALICE Other systematics: tracking performance at high-pT, high-luminosity track distortion, unobserved neutral energy, … [see backup slides] Elena Bruna (Yale&INFN Torino)

  8. Jets in A+A ~ 21 GeV STAR preliminary pt per grid cell [GeV] η ϕ Goal Reconstruct the full jet kinematics of hard scattering in unbiased way, even in presence of (underlying) heavy-ion collision. di-jet event Elena Bruna (Yale&INFN Torino)

  9. Background in A+A ~ 21 GeV STAR preliminary Au+Au 0-20% Rc=0.4, no pt cut, out-of-cone area rA[Gev] pt per grid cell [GeV] Reference multiplicity (~centrality) η ϕ STAR Preliminary STAR preliminary Out-of-cone area pT (Jet Measured) ~ pT (Jet) + ρA ± F STAR Preliminary di-jet event Three main components: Background energy in R=0.4 ~ 45 GeV at RHIC, ~90 GeV at LHC Substantial region-to-region background fluctuations described by F “Fake” jets: random association of uncorrelated soft particles (i.e. not due to hard scattering) Elena Bruna (Yale&INFN Torino)

  10. Background in A+A Au+Au 0-20% Rc=0.4 ρA [Gev] Reference multiplicity (~centrality) pT (Jet Measured) ~ pT (Jet) + ρA ± F • Event-wise background estimate: • reconstruct event with kT(jets+bkg) • all jets in acceptance {pT,i} • A = jet area in η-ϕ STAR Preliminary STAR preliminary Why the median? The background estimate has to be independent of the ‘true signal jets’. The ‘true jets’ do not pull the median compared to the mean. Elena Bruna (Yale&INFN Torino)

  11. Background in A+A ~ 21 GeV STAR preliminary pt per grid cell [GeV] η ϕ pT (Jet Measured) ~ pT (Jet) + ρA ± F In a given Area, the background is subject to fluctuations around the median ρ How to quantify fluctuations and fake jets? STAR Preliminary di-jet event Elena Bruna (Yale&INFN Torino)

  12. Background in A+A pT (Jet Measured) ~ pT (Jet) + ρA ± F STAR preliminary In a given Area, the background is subject to fluctuations around the median ρ How to quantify fluctuations and fake jets? di-jet event pt per grid cell [GeV] η STAR Preliminary • Embed a probe particle in the event:pTemb • Reconstruct hybrid event with anti-kT • Match reconstructed jet with embedded probe in (h,f): • pTcluster, Acluster • Quantify response via: ϕ Elena Bruna (Yale&INFN Torino)

  13. Assessing background fluctuations Gaussian fluctuations No fluctuations “Thermal” fluctuations Akt, R=0.2 Simulation T=290 MeV dN/dη=650 R=0.2 σ=3.5 GeV pT,clusMeas – ρA pT,clusMeas – ρA pT,clusMeas – ρA How to characterize the full shape of the bkg fluctuations? f (pT,clusMeas – ρA – pTemb) Example: pT,clus for only background clusters (no true jet) pTemb=0 Elena Bruna (Yale&INFN Torino)

  14. Background fluctuations: δpT • Single particle embedding • in real Au+Au • pT=30 GeV • h=-0.2 • Gaussian fit to left-hand side (LHS): • LHS: good representation • RHS: non-Gaussian tail (real jets are there!) • centroid non-zero(~ ±1 GeV) •  contribution to jet energy scale uncertainty Elena Bruna (Yale&INFN Torino)

  15. Background fluctuations: δpT Simple model: uncorrelated particle emission Poisson • M(A) = particle multiplicity in area A  • <pT> = mean pT in a given area A  M. Tannenbaum Phys. Lett. B498 (2001) 29 Gamma Background fluctuation distribution in a given area A in (η,ϕ): • No hard scattering • No correlations • Two parameters Simple uncorrelated-emission model accounts for the bulk of background fluctuations (!) Elena Bruna (Yale&INFN Torino)

  16. Background fluctuations: δpT Systematics • So far, embedded single particles • But jet ≠ single particles • investigate dependence on fragmentation patterns: • PYTHIA, QPYTHIA δpT insensitive to different fragmentation Crucial for quenched jets, whose fragmentation is unknown! arXiv:1012.2406 What do we do once we know the dpT shape? Elena Bruna (Yale&INFN Torino)

  17. Unfolding the underlying event Pythia Pythia smeared • Jet Energy resolution distorts measured jet cross section • Background distorts measured jet cross section • Unfolding technique used to extract the ‘true’ jet spectrum  jet energy scale Pythia unfolded unfolding Elena Bruna (Yale&INFN Torino)

  18. Unfolding/deconvoluting/unsmearing Example of response matrix used for unfolding the underlying event. [dpT=Gaussian, s=6.5 GeV] (m) - RooUnfold: http://hepunx.rl.ac.uk/~adye/software/unfold/RooUnfold.html - 5 methods: D. D’Agostini, NIM.A362:487 (2005), … (n) Given true measure mj (i.e. true jet pT) and response function Rij (inefficiencies, irresolutions, …) the experiment will measure: Ideally (i.e. with infinite statistics) we can determine mj from ni by inverting Rij Don’t have infinite stats. so need to solve for m iteratively. Elena Bruna (Yale&INFN Torino)

  19. Jet III: Results Elena Bruna (Yale&INFN Torino)

  20. p+p JP trigger ~ 21 GeV Jets in p+p: calibrated probes? RHIC p+p @ √s = 200 GeV √s=2.36 TeV Jet p+p pt per grid cell [GeV] η ϕ ATLAS Nov/Dec 2009 Tevatron: CDF @ √s = 1.8 TeV STAR Preliminary p+p: the reference measurement  need well calibrated probes Elena Bruna (Yale&INFN Torino)

  21. Jets are calibrated probes RHIC Tevatron Jet cross section in p+p (STAR), p+p, DIS, well described by pQCD Jets in p+p are a good reference for A+A Elena Bruna (Yale&INFN Torino)

  22. Fragmentation Functions in p+p Preliminary Preliminary Preliminary Preliminary Data not corrected to particle level. “PYTHIA” = PYTHIA +GEANT R=0.4 20 <Jet pTreco< 30 GeV/c 30 <Jet pTreco< 40 GeV/c Reasonable agreement between data and PYTHIA Jets in p+p are a good reference for A+A Elena Bruna (Yale&INFN Torino)

  23. The underlying event in p+p |Δφ| − Angle relative to leading jet • “Toward” |Δφ|< 60o • “Away” |Δφ|> 120o • “Transverse” 60o < |Δφ| < 120o • TransMax -Trans. region withhighest ΣpT or ΣNtrack • TransMinTrans. region with least ΣpT or ΣNtrack Underlying event = what is contained in the Transverse region, i.e. everything BUT the hard scattering Elena Bruna (Yale&INFN Torino)

  24. The underlying event in p+p Agreement between PYTHIA and data Underlying event is decoupled from the hard scattering Elena Bruna (Yale&INFN Torino)

  25. The underlying event in p+p Agreement between PYTHIA and data Underlying event is decoupled from the hard scattering Elena Bruna (Yale&INFN Torino)

  26. Jets in d+Au: why? Jet d+Au Control experiment: Measure possible initial state/Cold Nuclear Matter (CNM) effects Probe the “cold medium” via d+Au collisions (compare to p+p) Elena Bruna (Yale&INFN Torino)

  27. Jets in d+Au σkT,raw (p+p) = 2.8 ± 0.1 GeV/c σkT,raw (d+Au) = 3.0 ± 0.1 GeV/c No strong Cold Nuclear Matter effect on jet kT broadening seen Systematics under investigation Elena Bruna (Yale&INFN Torino)

  28. Jets in d+Au No significant deviation from Nbin scaling in d+Au Initial state/Cold nuclear matter effects in the kinematic range as measured in d+Au seem to be small Systematics under investigation Elena Bruna (Yale&INFN Torino)

  29. So far, so good Jet Jet p+p d+Au ✓ p+p: the reference measurement  calibrated probes ! d+Au: the control measurement  No strong Cold Nuclear Matter effect ✓ Elena Bruna (Yale&INFN Torino)

  30. Jets in Au+Au: what to expect? • Jet energy fully recovered even in case of quenching • Jet is a hard process, scales as Nbin • Inclusive spectra: • Di-jet analyses: • Ratio of recoil spectra Au+Au/p+p = 1 • Modified fragmentation in case of dense medium - for unbiased jet reconstruction - Elena Bruna (Yale&INFN Torino)

  31. Inclusive measurements • Inclusive Jet spectrum measured in central Au+Au collisions at RHIC • Extended the kinematical reach to study jet quenching phenomena to jet energies > 40 GeV Elena Bruna (Yale&INFN Torino)

  32. Inclusive measurements • Inclusive Jet spectrum measured in central Cu+Cu collisions at RHIC • Extended the kinematical reach to study jet quenching phenomena to jet energies > 40 GeV Elena Bruna (Yale&INFN Torino)

  33. Jet RAA Inclusive RAA • RAAjet<1 We see a substantial fraction of jets - in contrast to x5 suppression for light hadron RAA (RAAjet > RAA) • kT and Anti-kT known to have different sensitivities to background Elena Bruna (Yale&INFN Torino)

  34. Jet energy profile: first look Solid lines: Pythia – particle level Jet inclusive measurements: 0.2 vs 0.4 R=0.4 R=0.2 p+p: • jets more collimated with increasing pT • PYTHIA (fragmentation + hadronization) describes the data Elena Bruna (Yale&INFN Torino)

  35. Jet energy profile: first look Solid lines: Pythia – particle level Jet inclusive measurements: 0.2 vs 0.4 NLO ≈ PYTHIA parton level PYTHIA hadron level ≈ HERWIG hadron level G. Soyez – priv. comm. 2010 Be careful when comparing to theory: Hadronization broadens the jet Elena Bruna (Yale&INFN Torino)

  36. Jet energy profile: first look Jet inclusive measurements: 0.2 vs 0.4 R=0.4 R=0.2 p+p: jets more collimated with increasing pT PYTHIA (fragmentation + hadronization) describes the data Au+Au: ratio lower than p+p “Deficit” of jet energy for jets reconstructed with R=0.2 Elena Bruna (Yale&INFN Torino)

  37. Jet energy profile: first look Jet inclusive measurements: 0.2 vs 0.4 R=0.4 R=0.2 Red: p+p Blue: Au+Au Suggests strong broadening of the energy profile Elena Bruna (Yale&INFN Torino)

  38. Jets in p+p and Cu+Cu in PHENIX PHENIX uses a Gaussian filter approach Cone-like, but no fixed angular cut-offs Implements fake jet rejection Elena Bruna (Yale&INFN Torino)

  39. Jets in A+A: possible biases CAVEAT: jet-finder based on unmodified jet-shapes ⇒ veto against modified/quenched jets “Anti-quenching” biases! pT cut to minimize background ⇒ bias towards less-interacting jets Can we exploit the biases? Elena Bruna (Yale&INFN Torino)

  40. Di-jet measurements Trigger jets are biased towards the surface. Recoil jets are exposed to a maximum path-length in the medium. Large energy loss expected. Anti-kT, R=0.4 Trigger Jet: pT,cut=2 GeV/c, pT(trig)>20 GeV/c Trigger jet σ=6.5 GeV/c EMC trigger Coincidence rate: how often I measure a recoil jet once the trigger jet is found Recoil jet Elena Bruna (Yale&INFN Torino)

  41. BACKUP Elena Bruna (Yale&INFN Torino)

  42. Jet Energy resolution with di-jets Particle-Detector jet Res: pTJet(Part.Lev) – pTJet(Det.Lev) ~10-25 % di-jet Res: pTJet 1– pTJet 2 (PY Det. Lev.) ~ (dijet data) : good! But: (dijet PY Det. Lev.) > (Part-Det) • di-jet imbalance includes both energy resolution and kT (initial state) effect! • [kT=pTjet sinDfdijet] • kT: good agreement between data and simulation Use PYTHIA to determine the jet energy resolution Elena Bruna (Yale&INFN Torino)

  43. Jet-finding and systematics.. Tracking performance • Tracking is limited by misalignment, luminosity, resolution… • Rare processes as high-pT jets are likely to come from high luminosity runs • Example of high-luminosity distortion? Space-charge effect  accumulation of space charge in the TPC that causes an anomalous transport of drifting electrons in the TPC, affecting the tracking performance by shifting the momentum up or down (depending on the charge) • Tracking resolution at high-pT is • expected to deteriorate  need to apply • an upper pT cut on tracks PYTHIA simulation: p+p 200 GeV effect of upper pT cut on jet energy scale Elena Bruna (Yale&INFN Torino)

  44. Jet-finding and systematics.. Unobserved neutral energy Experiments like STAR and ALICE do not detect neutral, long-lived particles (neutrons, K0L) • PYTHIA simulation: • p+p at 200 GeV • mean missed E ~ 9% • median missed E <0.3 % • 50% of jets loose no energy • model dependent Elena Bruna (Yale&INFN Torino)

  45. Fragmentation Functions Jet energy determined in R=0.4 large uncertainties due to background (further systematic evaluation needed) • pT Jet(trig)>20 GeV • pTcut=2 GeV AuAu (Jet+Bkg) AuAu (Bkg) high z low z Charged particle FF: R(FF)=0.7 STAR preliminary xrec=ln( pT,Jet rec / pT,hadr) AuAu: FF(Jet)=FF(Jet+Bkg)-FF(bkg) Bkg estimated from charged particle spectra out of jet cones Bkg dominates at low pT Elena Bruna (Yale&INFN Torino)

  46. Fragmentation Functions “trigger” jet “recoil” jet EMC trigger No apparent modification of FF of recoil jets with pTrec>25 GeV would imply non-interacting jets, but: Jet broadeningEnergy shift harder FF Need to better determine the jet energy Elena Bruna (Yale&INFN Torino)

  47. Jet Yields in ALICE Elena Bruna (Yale&INFN Torino)

  48. DCal for Di-Jet analysis @ ALICE Elena Bruna (Yale&INFN Torino)

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