1. Di-parton probes of hot QCD matter Marco van Leeuwen, LBNL

2. 2 Hard probes and medium density Zhang, H et al, nucl-th/0701045 Di-hadrons provide stronger constraint on density Extracted transport coefficient from singles and di-hadrons consistent 2.8 ± 0.3 GeV 2 /fm  2 -minimum narrower for di-hadrons Di-hadron suppression Inclusive hadron suppression Di-hadrons Inclusive hadrons

3. 3 Model dependence of Different calculational frameworks C. Loizides hep-ph/0608133v2 2.8 ± 0.3 GeV 2 /fm Di-hadrons Inclusive hadrons Zhang, H et al, nucl-th/0701045 Multiple soft scattering (BDMPS, Wiedemann, Salgado,…) Twist expansion (Wang, Wang,…) Different approximations to the theory give significantly different results Main uncertainties: -Formalism for QCD radiation -Geometry (density profile)

4. 4 Energy loss distribution P(  E) ~15 GeV Renk, Eskola, hep-ph/0610059 Can we constrain this by experiment? Salgado and Wiedemann, Phys. Rev. D68, 014008 Depends on Intrinsic spectrumGeometry, time evolution of matter Energy loss distribution P(  E) is the fundamental quantity (e.g. ‘surface bias’)

5. 5 Two extreme scenarios p+p Au+Au pTpT 1/N bin d 2 N/d 2 p T Scenario I P(  E) =  (  E 0 ) ‘typical energy loss’ Shifts spectrum to left Scenario II P(  E) = a  (0) + b  (E) ‘partial transmission’ Downward shift (or how P(  E) says it all) P(  E) encodes the full energy loss process R AA cannot distinguish those two extreme scenarios … need more differential probes

6. 6 Di-hadrons vs  -jet Hydro profile Di-hadron emission points Box density T. Renk, K. Eskola, hep-ph/0610059 Di-hadron yield away side T. Renk, PRC74, 034906  -jet yield Away-side hadrons E  = 15 GeV Di-hadrons: little sensitivity to P(  E)  -jet provides sensitivity to P(  E) Need experimental access to parton energies to extract P(  E) (Fragmentation bias)

7. 7 Getting access to initial parton energy Jet reconstruction –(Partially) recover radiated/lost energy in cone Balancing partons –  -jet (Z-jet) –Di-jets Heavy flavour –Hard fragmentation  reduced bias? –Preserves flavour of hard scattering This talk:Pythia-based exploration basic phenomenology of di-jet, di-heavy flavour at RHIC and LHC Can we use these as instruments to learn about energy loss?

8. 8 Getting at the jet energy Simulations: Pythia 6.319 (CDF tune A) Jet energy contributions: -65% in charged particles -20% EM (mostly p0) -Small contributions from K 0 L, neutrons, etc (approx -1 leading particle) Leading particle ~15 % + Long tails ‘Ideal’ jets reconstructed using all final state particles Cone algorithm R=1 E jet =  p T

9. 9 Jet-reconstruction in Heavy Ions This talk: ‘worst case’: charged only, no p T -cut Full simulation: Include background, calo response R=0.3, p T >2 GeV (charged tracks) S.-L. Blyth et al, J Phys G = 0.61  (E ch )/ = 0.30 /E input = 0.68  (E rec )/ = 0.34 Jet-response for ‘charged-only’ case similar to expectations A+A with EMcal+tracking

10. 10 Jets on a steep spectrum Leading particle: mostly lower limit on jet energy (+finite ‘efficiency’ at larger p T ) 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, p T )

11. 11 Di-jets Di-jet angle Reconstructing dijets is ‘easy’! √s=5.5 TeV √s=200 GeV Widening of  at LHC energies: increase of initial state radiation, 3-jet events Use background level to monitor/subtract combinatorics in A+A

12. 12 Di-jets Di-jets balance in energy  Handle on initial parton energy Correlation widens at LHC: radiation + 3-jet events Energy-energy correlation √s=5.5 TeV√s=200 GeV Note: this plot can be made for data, simulation, p+p, A+A (pure observables)

13. 13 Di-jet energy balance  p T for balancing di-jets Irreducible effects: k T, mult-jet events:  ~ 5-10 GeV Sensitivity  (  E) ~ few GeV Direct measure of energy loss fluctuations  (  E) in Heavy Ion Collisions √s = 5.5 TeV Still works for charged-only jets (deteriorates quickly beyond)

14. 14 Di-jet energy balance RHIC, √s = 200 GeV Measurement can be pursued at RHIC and LHC LHC, √s = 5.5 TeV Sensitivity  (  E) ~ few GeV Note for A+A: Background energy contributions cancel in p T2 -p T1 (up to stat fluctuations)

15. 15 Di-jet energy balance Measurement allows to –Assess irreducible effects (k T, etc) in p+p –Test jet-energy reconstruction in p+p –Measure ‘random jet’ contributions in A+A –Measure width of energy loss distribution in A+A Sensivity  (  E) ~ few GeV Q: is this precise enough to test theory? Exact numbers depend on statistics, energy loss phenomenology (out-of cone radiation)

16. 16 Back-to-back heavy flavours √s=5.5 TeV p T > 5 GeV PYTHIA 6.319 MSEL=4,5 (biased sample) ISR gluon Initial state radiation/flavour excitation leads to near-side heavy q-qbar pairs ‘flavour excitation’ Important contribution  Need to select back-to-back for di-parton measurement Pythia: near side q-qbar peak

17. 17 Heavy flavour CLEO, PRD70, 112001 ALEPH, PLB 512, 30 Effective fragmentation in Pythia rather soft Charm expect ~0.6 Beauty: expect ~0.8 Softer than data indicate Back-to-back heavy flavour poorly constrains initial kinematics According to Pythia; can be verified on data

18. 18 Conclusion Di-jet energy balance can provide new insight into energy loss process Promising instrument –Large statistics –Self-calibrating –Good reference from p+p Heavy flavour more difficult –Effective fragmentation quite soft (in Pythia, may not be realistic) –Smaller x-sec, efficiency Keep developing ideas/tools: -Optimise observables -Optimise jet-E reconstruction in A+A -Find ‘working point’ (large signal, low background) at RHIC and LHC -Explore additional observables, e.g. acoplanarity (k T, multiple scattering in QGP) -Is Pythia OK for di-heavy flavour correlations? Need p+p measurements Question to theory: what sensitivity do we need? Event-generator with energy-loss or in-medium fragmentation would be extremely helpful! Sensitive to  (  E)

19. 19 Extra slides

20. 20 Hard probes of QCD matter Use the strength of pQCD to explore QCD matter Use partons from hard scatterings to probe QCD matter Interactions between parton and medium: -Radiative energy loss -Collisional energy loss -Hadronisation: fragmentation and coalescence Sensitive to medium density, transport properties

21. 21 Energy loss in QCD matter  : R AA = 1  0, h ± : R AA ≈ 0.2 Au+Au 200 GeV, 0-5% central Compare Au+Au spectra to properly scaled p+p spectra: ‘nuclear modification factor’ D. d’Enterria Hard partons lose energy in the hot matter High-p T hadron production suppressed in Au+Au collisions  : no interactions Hadrons: energy loss R AA = 1 R AA < 1

22. 22 Why measure P(  E)? ~15 GeV  E=15 GeV Energy loss distributions very different for BDMPS and GLV formalisms Renk, Eskola, hep-ph/0610059 Wicks et al, nucl-th/0512076v2 BDMPS formalism GLV formalism Need experimental access to the radiation distribution P(  E) Which one is correct?

23. 23 What can we learn about energy loss? Need to reconstruct parton energy, to disentangle terms, extract P(  E) Full jet reconstruction  at RHIC: use di-hadrons as proxy  -jet Heavy quarks Fragment hard, preserve flavour Partonic spectrum E jet Nuclear geometry ,L Energy loss  E(E jet, ,L) Fragmentation D(E jet,  E) General form:    Need full calculation of geometry and energy loss fluctuations to compare (PQM, WHDG, Renk) Observables are a convolution of Summarised in P(  E) (components not observable) Further separation only possible by varying geometry Note: P(  E) includes geometry and quantum energy loss variations

24. 24 Density profiles T. Renk, K. Eskola, hep-ph/0610059 Di-hadron correlations sensitive to density profile and P(  E) Hydro profile Di-hadron emission points Box density Near-side yield Away-side yield Work in progress; detailed comparison to data expected

25. 25 Fixing the jet energy:  -jet events T. Renk, PRC74, 034906  -jet: monochromatic source  sensitive to P(  E) Expectations for different P(  E) E  = 15 GeV   -jet events are rare, need large luminosity First measurements expected from RHIC run-7 p+p result

26. 26 Fragmentation bias PHENIX PRD74: 072002 LEP: Quarks: D(z) ~ exp(-8.2 z) Gluons: D(z) ~ exp(-11.4 z) Small difference in dN/dx E or dN/dz T from large difference in D(z) slopes Shape determined by power-law exponent n Di-hadron measurements do not constrain the parton energy  Limited sensitivity to P(  E) For exp(-b z) fragmentation: For exponential fragmentation Explains similarity of z T -slopes in d+Au and Au+Au

27. 27 Next-generation observables G-jet (Z-jet) –Use g to measure Eparton before Eloss –‘golden probe’, but difficult (small x-sec, large bkg for g) Jet-reconstruction –Use jet-energy to get handle on initial parton energy –Expected to work well at LHC –Potential biases on DE from jet-reco (‘surface-effect’) Di-jet –Use away-side jet to calibrate –Allows to check effect of Eloss on jet energy reconstructions Di-heavy meson? –Hard fragmentation might reduce frag bias effect –Heavy quark jets to get initial parton energy? –Disadv: not easy Explore in simu, this talk

28. 28 Di-parton observables Introduction –Energy loss distribution P(DE) is crucial quantity –Need access to initial parton energy to

29. 29 Gluon fluctuations: GLV PLB538, 282