1. 1 Jets and High-p T Physics with ALICE at the LHC Andreas Morsch CERN Workshop on High p T Physics at the LHC, Jyväskylä, March 25, 2007

2. 2 Outline Jet reconstruction in heavy ion collisions Modified fragmentation functions with reconstructed jets Di-Hadron Correlations at LHC

3. 3 Jet Physics at RHIC In central Au-Au collisions standard jet reconstruction algorithms fail due to the large energy from the underlying event (300 GeV in R< 1.0) and the relatively low accessible jet energies (< 20 GeV). Use leading particles to tag the jet. p+p @  s = 200 GeV STAR Au+Au @  s NN = 200 GeV

4. 4 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. Phys. Rev. Lett. 91, 072304 (2003). Pedestal&flow subtracted STAR

5. 5 Sensitivity to medium parameters R AA measurements are consistent with pQCD-based energy loss calculations. However, they provide only a lower bound to the initial color charge density. Eskola et al., hep-ph/0406319 R AA ~0.2-0.3 for broad range of q Use 2-hadron correlation, 3-hadron correlation … multi-hadron correlation = Reconstructed Jets !

6. 6 Jet Physics at LHC: Motivation Study of reconstructed jets increases sensitivity to medium parameters by reducing Trigger bias Surface bias Using reconstructed jets to study Modification of the leading hadron Additional hadrons from gluon radiation Transverse heating. From toy model  = ln(E jet /p hadron ) Reconstructed Jet

7. 7 Jet reconstruction: New Challenges for ALICE Existing TPC+ITS+PID |  | < 0.9 Excellent momentum resolution up to 100 GeV Tracking down to 100 MeV Excellent Particle ID New: EMCAL Pb-scintillator Energy resolution ~15%/√E Energy from neutral particles Trigger capabilities central Pb–Pb pp

8. 8 Signal fluctuations Response function for mono-chromatic jets E T = 100 GeV, R = 0.4  E/E ~ 50%  E/E ~ 24%

9. 9 Expected resolution including EMCAL Assumes conservative multiplicity: dN/dy = 6000

10. 10 Jet yields: one LHC year Jet yield in 20 GeV bin Large gains due to jet trigger Large variation in statistical reach for different reference systems

11. 11 Background energy In cone of R = 1 RHIC: 300 GeV LHC: 1500 GeV However jet energies up to ~250 GeV accessible ! E T >N jets 50 GeV 2.0  10 7 100 GeV 1.1  10 6 150 GeV 1.6  10 5 200 GeV 4.0  10 4 Provides lever arm to measure the energy dependence of the medium induced energy loss. 10 4 jets needed to study fragmentation function in the z > 0.8 region.

12. 12 Background energy How to reconstructs jets above a large fluctuation background (  E Bg ) ? Restrict identification and reconstruction to domain in which E meas >>  E Bg Cone size R < 1 p T -cut Limiting case R=0: leading particle Advantage: background free by construction

13. 13 Optimal Cone Size Jets reconstructed from charged particles: Need reduced cone sizes and transverse momentum cut ! Energy contained in sub-cone R E ~ R 2 Jet Finders for AA do not work with the standard cone size used for pp (R = 0.7-1). R and p T cut have to be optimized according to the background conditions.

14. 14 Background Fluctuations Background fluctuations limit the energy resolution. Fluctuations caused by event-by-event variations of the impact parameter for a given centrality class. Strong correlation between different regions in  plane ~R 2 Can be eliminated using impact parameter dependent background subtraction. Poissonian fluctuations of uncorrelated particles  E =  N  [ 2 +  p T 2 ] ~R Correlated particles from common source (low-E T jets) ~R

15. 15 Background Fluctuations Evt-by-evt background energy estimation

16. 16 Jet reconstruction in reduced domain: Why does it work ? Measure only fraction of jet energy but measure it well In this case E jet  E meas Since d  /dE jet ~ 1/E T 5.7, E jet >> E meas unlikely E jet  E rec with relative small fluctuations Jets are biased into the domain in which they are reconstructed = “Trigger Bias” Works even for leading particle “jet reconstruction” p Trig = 0.6 E jet For ideal calorimetry and R=0.4: p Trig = 0.9 E jet Further restriction of domain in ALICE Charged particles only, in region without EMCAL coverage Trigger bias: enhanced charged particle component TPC + EMCAL: charged +  only small fraction of energy from neutrons and K 0 L

17. 17 Reduction of the trigger bias by collecting more energy from jet fragmentation… Unbiased parton energy fraction production spectrum induced bias

18. 18 Another good reason for jet reconstruction: Statistics ! Strong bias on fragmentation function … which we want to measure Low selectivity of the parton energy Very low efficiency, example: ~6% for E T > 100 GeV 1.1 10 6 Jets produced in central Pb-Pb collisions (|  | < 0.5) No trigger: ~2.6 10 4 Jets on tape ~1500 Jets selected using leading particles

19. 19 Jet reconstruction in restricted domain: What can go wrong ? Correction factors to go from measured to reconstructed jet energy unknown in AA ! Radiation Mainly soft particles Part of the energy goes outside of the jet cone Needs Good low-p T capabilities Measurement of the transverse jet structure. Theoretical understanding of the transverse jet-structure. Unquenched Quenched (AliPythia) Quenched (Pyquen) p T < 2 GeV Largest effect seen in low-p T particles.

20. 20 ALICE performance studies and preparation for first analysis Full detector simulation and reconstruction of HIJING events with embedded Pythia Jets Implementation of a core jet analysis frame work Reconstruction and analysis of charged jets. Quenching studies with fragmentation function TPC only and TPC + EMCAL

21. 21 Energy spectrum from charged jets Cone-Algorithm: R = 0.4, p T > 2 GeV Selection efficiency ~30% as compared to 6% with leading particle ! No de-convolution, but Gauss  E -n ~ E -n

22. 22 Modification of the fragmentation function: Toy Model Pythia hard scattering Initial and Final State Radiation Afterburner A Afterburner B Afterburner C...... Pythia Hadronization Quenching of the final jet system and radiation of 1-5 gluons. (AliPythia::Quench using Salgado/Wiedemann - Quenching weights) Nuclear Geometry (Glauber) Jet (E) → Jet (E-  E) + n gluons (“Mini Jets”)

23. 23 R AA (  ) ratio

24. 24 Example: p+Pb reference With EMCal: jet trigger+ improved jet reconstruction provides much greater E T reach

25. 25 Trigger Bias Production spectrum weighted response matrix: Out-of-domain fluctuations are damped with 1/E n symmetrizing the distribution.

26. 26 Jet energy resolution and dN/dz Direct comparison with the MC truth for the same selected track. The dotted line shows the point spread function for z = 0.4. Model1Model2

27. 27 Systematic shift in R AA (  ) More energy is radiated outside the cone. On average the input energy has to be higher in order to give a reconstructed energy of 100 GeV. As a consequence  is shifted to lower values. Systematics has to be controlled using measurements of the transverse jet structure and R AA Jet (E T ) unquenched quenched E rec = 100 GeV

28. 28 Systematic Error from Background Subtraction 2 GeV Soft Background

29. 29 Background Fluctuation log(E/GeV) log(dN/dE) Background fluctuates up Jet input spectrum Background fluctuates down Bias towards higher Bg

30. 30 Influence on Jet axis dR Under Ideal detector response – Not quenching R. Diaz Valdes

31. 31 Influence for a jet input spectrum p-p 120.0 ± 17.23 0.856 ± 0.0815 Pb-Pb 116.2 ± 19.21 0.894 ± 0.1169 R. Diaz Valdes

32. 32 Bias on R AA (  ) Corrections should be applied on p-p distribution to compare it with quenched Pb-Pb jet fragmentation R. Diaz Valdes

33. 33 Di-hadron Correlations: from RHIC to LHC Di-hadron correlations will be studied at LHC in an energy region where full jet reconstruction is not possible (E < 30 GeV). What will be different at LHC ? Number of hadrons/event (P) large Leads to increased signal and background at LHC Background dominates, significance independent of multiplicity Increased width of the away-side peak (NLO) Wider  -correlation (loss of acceptance for fixed  -widow) Power law behavior d  /dp T ~ 1/p T n with n = 8 at RHIC and n = 4 at LHC Changes the trigger bias on parton energy PYTHIA 6.2 See also, K. Filimonov, J.Phys.G31:S513-S520 (2005)

34. 34 Scaling From RHIC to LHC S/B and significance for away-side correlations Scale rates between RHIC and LHC Ratio of inclusive hadron cross-section N(p T ) ~ p T 4 p T trig > 8 GeV RHIC/STAR-like central Au-Au (1.8 10 7 events) LHC/ALICE central Pb-Pb (10 7 events), no-quenching From STAR p T trig = 8 GeV/c

35. 35 Di-hadron Correlations STARLHC, ALICE acceptance HIJING Simulation “Peak Inversion” O (1)/2  4 10 5 events M. Ploskon, ALICE INT-2005-49

36. 36 Summary Copious production of jets in Pb-Pb collisions at the LHC Jets can be reconstructed over the background from the underlying event Sufficient dynamic range (50 – 250 GeV) to make systematic studies of energy dependence. Background conditions require jet identification and reconstruction in reduced domain R = 0.4. We will measure jet structure observables (j T, fragmentation function, jet-shape) for reconstructed jets. In AA, high-p T (calorimetry) and low-p T capabilities needed for unbiased measurement of parton energy. Strength of ALICE Excellent low-p T capabilities to measure particles from medium induced radiation. PID to measure the particle composition of quenched jets Dedicated pp experiments have larger E T reach

37. 37 Jet Finder based on cone algorithms Input: List of cells in an  grid sorted in decreasing cell energy E i Estimate the average background energy E bg per cell from all cells. For at least 2 iterations and until the change in E bg 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 E i – E bg > E seed 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 (  c,  c ) = (  i,  i ) Using all cells with  (  i -  ) 2 +(  i -  ) 2 < R c 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.

38. 38 Jet Finder in HI Environment:Principle Loop1: Background estimation from cells outside jet cones Loop2: UA1 cone algorithm to find centroid using cells after background subtraction RcRc

39. 39 Putting things together: Intrinsic resolution limit p T > 0 GeV 1 GeV 2 GeV Resolution limited by out-of-cone fluctuations common to all experiments ! E jet = 100 GeV Background included

40. 40 ALICE Set-up HMPID Muon Arm TRD PHOS PMD ITS TOF TPC Size: 16 x 26 meters Weight: 10,000 tons

41. 41 Trigger performance Trigger on energy in patch  x  Background rejection set to factor of 10 =>HLT Centrality dependent thresholds

42. 42 Summary of statistical reach Ratio  >4 With EMCALW/O EMCAL R AA 225165 R pA 225125 R AA (5.5 TeV)225100 R AA (  ) 150110 R CP 150 (70) Ratio z>0.5With EMCALW/O EMCAL R AA 150100 R pA 150 (70) R AA (5.5 TeV)140 (60) Large  : ~10% error requires several hundred signal events (Pb central) and normalization events (pp,pA). Large z>0.5 requires several thousand events The EMCAL extends kinematic range by 40–125 GeV improves resolution (important at high z) Some measurements impossible w/o EMCAL