Jet Physics in Heavy Ion Collisions at the LHC

1. Jet Physics in Heavy Ion Collisions at the LHC Andreas MorschCERN QGP Meeting’06, VECC, Kolkata, India, February 5-7th 2006

2. Outline • Reconstructed jets versus leading particles at the LHC • Jet reconstruction • Jet structure analysis

3. Jets • Jets are characterized by the fact that transverse momenta of associated particles transverse to jet axis (jT) are small compared to jet momentum (collimation). • Collimation increases with energy. Energy outside cone R=0.3

4. Jet Reconstruction: Full reconstruction • Jet finders, in general, • Uses collimated structure of the jet to find jet axis and subsequently maximizes energy inside a jet cone. • Jet cone in h-f: R = Dh2+Df2 • Typical jet cones 0.7-1 • 80% of jet energy in R < 0.3 !

5. Access to parton properties using leading particles • Leading particle has approximately the direction of the original parton. • In case of heavy flavors (b,c,t) it also carries a large fraction of the parton momentumm, due to a hard fragmentation. • Ideally reconstruction of the b,c-meson • Alternatively muons (electrons) from semileptonic decays. • In case of light flavors, it carries a large fraction of the parton energy only due to the bias induced by the steeply falling production spectrum. b mX

6. Jet Physics at RHIC STAR Au+Au @ sNN = 200 GeV p+p @ s = 200 GeV Standard jet reconstruction algorithms fail due to the large energy from the underlying event (125 GeV in R< 0.7) and the relatively low accessible jet energies (< 30 GeV). RHIC experiments use leading particles as a probe.

7. Quantities studied Hadron Suppression Similar RCP: Ratio central to peripheral “away side” pT(assoc) Hadron Correlations: pT(trig) – pT(assoc) Df(trig, assoc) … “same side” pT (trig)

8. STAR Phys. Rev. Lett. 91, 072304 (2003). Pedestal&flow subtracted Evidence for Jet Quenching • In central Au+Au • Strong suppression of inclusive hadron yield in Au-Au collisions • Disappearance of away-side jet • No suppression in d+Au • Hence suppression is final state effect.

9. Two good reasons for analyzing reconstructed jet instead of leading particles at high ET • Bias on fragmentation function • Efficiency

10. Leading Particles at LHC • Strong bias on fragmentation function • … which we want to measure • Selects partons over a wide range of energies. • Very low efficiency ~6% for ET > 100 GeV • 1.1 106 Jets produced in central Pb-Pb collisions (||h| < 0.5) • No trigger: ~2.6 104 Jets on tape • ~1500 Jets selected using leading particles

11. A. Dainese, C. Loizides, G. Paic s = 5500 GeV Leading Particle: Surface emission bias Leading Particle • A further consequence of the bias toward hard fragmentation: surface emission “trigger bias” leading to • Small sensitivity of RAA to variations of transport parameter q^. • Yields only lower limit on color charge density. Reconstructed Jet • Ideally, the analysis of reconstructed jets will allow us to measure the original parton 4-momentum and the jet structure (longitudinal and transverse). From this analysis a higher sensitivity to the medium parameters (transport coefficient) is expected.

12. What are the expected jet production rates at the LHC ? Up to which energies do we have enough statistics for jet structure analysis ?

13. Jet rates at LHC NLO by N. Armesto

14. Jet rates at LHC Copious production: Several jets per central PbPb collisions for ET > 20 GeV Central PbPb / 106 s However, for measuring the jet fragmentation function close to z = 1, >104 jets are needed. In addition you want to bin, i.e. perform studies relative to reaction plane to map out L dependence.

15. How does the background from the underlying event limit jet reconstruction ? • Need for smaller cone sizes and transverse momentum cuts. • Incomplete reconstruction.

16. Jet identification • It has been shown (by embedding Pythia jets into HIJING) that even jets of moderate energies (ET > 50 GeV) can be identified over the huge background energy of the underlying HIJING event of central PbPb. • Reasons: • Collimation: Sizable fraction (~50%) of the jet energy is concentrated around jet axis (R< 0.1). • Background energy in cone of size R is ~ R2 and background fluctuations ~ R. • For dNch/dy = 5000: • Energy in R = √(Dh2+Df2) < 0.7: • 1 TeV !

17. Background energy “hides” jets Jets reconstructed from charged particles: Energy contained in sub-cone R Need reduced cone sizes and transverse momentum cut !

18. Signal and background energy as a function of pT Energy carried by particle with pT > pTmin Transverse momentum cut reduces background and, to a lesser extent, the signal.

19. Background fluctuations limit resolution • Fluctuations caused by event-by-event variations of the impact parameter for a given centrality class. • Strong correlation between different regions in h-f plane • ~R2 • Poissonian fluctuations of uncorrelated particles • DE = N [<pT>2 +spT2] • ~R • Correlated particles from common source (low-ET jets) • ~R

20. Background fluctuations Evt-by-evt background energy estimation

21. Jet Reconstruction with reduced cone-size • Identify and reconstruct jets using small cone sizes R = 0.3 – 0.4 subtract energy from underlying event and correct using measured jet profiles. • Reconstruction possible for Ejet >> DEBg • Caveat: • The fact that energy is carried by a small number of particles and some is carried by hard final state radiation leads to out-of-cone fluctuation. • Reconstructed energy decreased. • Hence increase of DE/E • Additional out-of-cone radiation due to medium induced radiation possible. Jet profiles as measured by D0

22. Jet Finder Principle Rc Loop1: Background estimation from cells outside jet cones Loop2: UA1 cone algorithm to find centroid using cells after background subtraction

23. Jet Finder • Input: List of cells in an h-f grid sorted in decreasing cell energy Ei • Estimate the average background energy Ebg per cell from all cells. • For at least 2 iterations and until the change in Ebg between 2 successive iterations is smaller than a set threshold: • Clear the jet list • Flag cells outside a jet. • Execute the jet-finding loop for each cell, starting with the highest cell energy. If Ei – Ebg > Eseed and if the cell is not already flagged as being inside a jet: • Set the jet-cone centroid to be the center of the jet seed cell (hc, fc) = (hi, fi) • Using all cells with (hi-h)2+(fi-f)2 < Rc of the initial centroid, calculate the new energy weighted centroid to be the new initial centroid. • Repeat until difference between iterations shifts less than one cell. • Store centroid as jet candidate. • Recalculate background energy using information from cells outside jets.

24. Background energy estimation r.m.s. of difference between estimated and real energy in jet cone. (Fixed mean energy/area) x cone area Energy outside jet cone after pT - cut x (area inside) / (area outside) As ,but energy estimated from energy outside jet-cones without pT cut.

25. Consequences of incomplete jet reconstruction: Signal fluctuations • Charged jets: dominated by charged-to-neutral fluctuations • Even with ideal calorimetry: out-of-cone fluctuations.

26. Intrinsic resolution: Out-of-cone fluctuations ET = 100 GeV

27. Effect of no or incomplete calorimetry ET = 100 GeV

28. Intrinsic resolution limit for ideal calorimetry. pT > 0 GeV 1 GeV 2 GeV

29. So what do we gain with respect to leading particle analysis ? • Reduced bias. • Improved selectivity on parton energy.

30. Production spectrum induced bias

31. Production rate weighted resolution function • Intrinsic resolution limited to DE/E ~ (15-20)% • Production rate changes factor of 3 within DE • Production rate weighted resolution function has to be studied. Input spectrum for different cone energy of charged jets.

32. Reconstructed ET-Spectrum

33. Jet Structure Analysis

34. Transverse structure • Central question • Does the collimated structure of the jets survive so that they can be reconstructed event by event ? • Study nuclear suppression factor RAAJet(ET, R) • Total suppression (i.e. surface emission only) or do we reconstruct modified jets ? • Have the observed jets a modified transverse structure ? • Measure jet shape dE/dR • Measure momentum distribution perpendicular to the jet axis dN/djT (“Transverse Heating”)

35. Transverse Structure Salgado, Wiedemann, hep-ph/0310079 DE = 20 GeV

36. Longitudinal structure • Measure parton energy as the energy of the reconstructed jet • Measure energy loss • Remnant of leading partons in the high-z part of the fragmentation function • Measure radiated energy • Additional low-z particles

37. Jet production point b < 5 fm “Bremsstrahlung” Spectrum exemplified using results from Salgado and Wiedemann no loss complete loss Code for Quenching Weights from C. Salgado and U. Wiedemann Longitudinal structure • No trivial relation between energy loss and jet observables • Intrinsic to the system • Path length is not constant • Need measurements relative to reaction plane and as a function of b. • More importantly: Intrinsic to the physics • Finite probability to have no loss or on the contrary complete loss • Reduced cone size • Out-of-cone fluctuations and radiation • To relate observables to energy loss we need shower MC combining consistently parton shower evolution and in-medium gluon radiation.

38. Afterburner A Pythia hard scattering Initial and Final State Radiation Afterburner B Pythia Hadronization Afterburner C . . . Toy Models • Two extreme approaches • Quenching of the final jet system and radiation of gluons. (AliPythia::Quench + Salgado/Wiedemann - Quenching weights with q= 1.5 GeV2/fm) • Quenching of all final state partons and radiation of many (~40) gluons (I. Lokhtin: Pyquen)* Nuclear Geometry (Glauber) Jet (E) → Jet (E-DE) + n gluons (“Mini Jets”) )*I.P. Lokhtin et al., Eur. Phys. J C16 (2000) 527-536 I.P.Lokhtin et al., e-print hep-ph/0406038 http://lokhtin.home.cern.ch/lokhtin/pyquen/

39. Example: Hump-backed Plateau N. Borghini, U. Wiedemann From toy model

40. Salgado, Wiedemann, hep-ph/0310079 Unquenched Quenched (AliPythia) Quenched (Pyquen) jT Q Transverse Heating: jT - Broadening • Unmodified jets characterized by <jT> = 600 MeV ~ const(R). • Partonic energy loss alone would lead to no effect or even a decrease of <jT>. • Transverse heating is an important signal on its own.

41. Energy-Loss Spectrum E = 100 GeV DE = 20 GeV Unquenched Quenched (AliPythia) Quenched (Pyquen) z = pL/E Interpretation of Fragmentation Functions • Intrinsic limit on sensitivity due to higher moments of the expected DE/E distribution. • Possible additional bias due to out-of-cone radiation. • Erec < Eparton • zrec = p/Erec > zhadron

42. Limit experimental bias ... • By measuring the jet profile inclusively. • Low-pT capabilities are important since for quenched jets sizeable fraction of energy will be carried by particles with pT < 2 GeV. • Exploit g-jet correlation • Eg = Ejet • Caveat: limited statistics • O(103) smaller than jet production • Does the decreased systematic error compensate the increased statistical error ? • Certainly important in the intermediate energy region 20 < ET < 50 GeV. Quenched (AliPythia) Quenched (Pyquen) g, Z Energy radiated outside core Not visible after pT-cut.

43. Role of background in jet structure analysis • Uncorrelated background particles • Bias due to incomplete reconstruction

44. Hump-back Plateau

45. Hump-back plateau Bias due to incomplete reconstruction. Statistical error Erec > 100 GeV 2 GeV

46. jT-Spectra

47. jT-Spectra Bias due to incomplete reconstruction. Statistical error Erec > 100 GeV

48. Conclusions • Copious production of jets in PbPb collisions at the LHC • < 20 GeV many overlapping jets/event • Inclusive leading particle correlation • Background conditions require jet identification and reconstruction in reduced cone R < 0.3-0.5 • At LHC we will measure jet structure observables (jT, fragmentation function, jet-shape) for reconstructed jets. • High-pT capabilities (calorimetry) needed to reconstruct parton energy • Good low-pT capabilities are needed • to measure particles from medium induced radiation. • to reduce systematic bias from out-of-cone radiation • EMCal would add trigger capabilities and improve jet reconstruction • ... and this would make it the ideal detector for jet physics at the LHC covering the needed low and high-pT capabilities + particle ID.