Measurements of jet quenching using the ATLAS detector

1. Measurements of jet quenching using the ATLAS detector Martin Spoustafor the ALTAS collaboration

2. Outline • Motivation • Jet reconstruction strategy • Tools to study jet quenching • fragmentation function and jT distribution • jet shapes • di-jet correlations • g-jet correlations • jet RAA • Summary

3. Motivation + + +... • Jet (leading particle) quenching well visible at RHIC experiments • LHC will deliver Pb+Pb collisions at Ös = 5.5 TeV/n • Models and predictions for the LHC energy exist, details of QCD energy loss mechanisms not well understood • Jets copiously produced at the LHC energy  possibility to study details of energy loss mechanism in QGP medium • 20 millions jets with ET>50 GeV per month of Pb+Pb running at the nominal luminosity

4. Why ATLAS ? jet reconstruction using calorimeter, full azimuth, 10 units of pseudorapidity tracking in 2T solenoid – fragmentation studies first layer of LAr EM calorimeter excellent for photon identification, other layers also well segmented

5. Jet reconstruction strategy PYTHIA dijets embedded to the unquenched HIJING events • Cone jet reconstruction: • regions of interest found (seed regions) – fast sliding window algorithm used • background computed • excluding the seed-regions • vs. h, vs. layer • background subtracted • standard p+p jet finding algorithm used (seeded iterative R=0.4 cone algorithm) one event before the background subtraction one event after the background subtraction An alternative: kT-algorithm based reconstruction strategy – also studied

6. jT z Fragmentation function and jT • Tracking efficiency ~ 70% for the most central collisions, below 10 GeV pT independent • Track to calorimeter matching used to identify tracks from a jet • Identified tracks for jT and z determination CaloTowers Tracks

7. Fragmentation function and jT ○ - truth ● - reconstructed (jet ET 70-140 GeV) ○ - truth ● - reconstructed (jet ET 70-140 GeV) jT (GeV) • jT and z computed for tracks above 2 GeV • Background distributions of jT and z are computed using tracks that match with HIJING particles, these distributions are subtracted, correction for the jet position resolution is applied jT z … we can well reproduce jT distribution and fragmentation function

8. Fragmentation function and jT Salgado, Wiedemann – jT also modified N.Armesto, et al. – modification of fragmentation functions • Both fragmentation function and jT distribution are expected to be modified due to the gluon radiation inside the medium (QCD analog of LMP effect) • Need to study the response of the detector to a possible modification – PYQUEN (see http://lokhtin.web.cern.ch/lokhtin/pyquen/)

9. Fragmentation function and jT from PYQUEN – generator level ○ - quenched ● - non-quenched (simulated events) ○ - quenched ● - non-quenched (simulated events) jT (GeV) jT (GeV) Low z enhanced, higher zsuppressed  leading particle suppressed, redistribution of energy out of a jet core Large jT suppressed  gluons radiated from large angles • Result at the generatorlevel • PYQUEN settings: default setting for quenching, b=0, pT,min(jet)=70 GeV, Pb+Pb, 5.5 TeV/n

10. Fragmentation function and jT from PYQUEN – reconstructed ○ - quenched ● - non-quenched (reconstructed events) ○ - quenched ● - non-quenched (reconstructed events) jT (GeV) jT (GeV) Low z enhanced, higher zsuppressed  leading particle suppressed, redistribution of energy out of a jet core Large jT suppressed  gluons radiated from large angles • Result at the after the reconstruction (but not embedded to the heavy ion event)– effect still well visible

11. Jet shapes • Measure the energy flow inside the jet at the calorimeter level • Well defined in QCD, measured at Tevatron jet axis ... integral jet shape ... differential jet shape

12. Jet shapes ○ - Truth jets (p+p) ● - Reconstructed jets (p+p) ○ - Jets in peripheral collisions ● - Jets in the most central collisions • Truth jet shapes are much more narrow than calorimeter jet shapes resulting from the calorimeter segmentation not from the background • We are able to reconstruct jet shapes in the most central collisions with good accuracy, a small difference at low r is due to position resolution and it should be possible to correct it using jets reconstructed with smaller cone size

13. Jet shapes I.Vitev, et al. Salgado, Wiedemann enhancement namely at the jet periphery no so sizable difference ... jet shapes expected to be modified ... PYQUEN to study the detector response

14. Jet shapes from PYQUEN – generator level ○ - non-quenched ● - quenched (simulated events) ○ - non-quenched ● - quenched (simulated events) • Result at the generator level • Almost factor of two difference in the jet core between quenched/unquenched simulations • Differential jet shape can show better the flow of the energy – energy is redistributed out of center of the jet

15. Jet shapes from PYQUEN – reconstructed ○ - non-quenched ● - quenched (reconstructed events) ○ - non-quenched ● - quenched (reconstructed events) • Results after the reconstruction (but not embedded to the heavy ion event) • Jet quenching effect still well visible … if the quenching is of that order we should be able to measure it

16. Di-jet correlations … conditional yield of detecting an associated jet (B) to a leading jet (A) as a function of their relative azimuth |Df| and pOUT = ETB sinR • Large h acceptance  large rates, important for low x-region • Similar variables studied already at RHIC with hadrons • 60% probability for detecting an associated jet (ETB>70 GeV, ETA>100 GeV)

17. Di-jet correlations from PYQUEN ○ - non-quenched ● - quenched (reconstructed events) ○ - non-quenched ● - quenched (reconstructed events) … conditional yield of detecting an associated jet (B) to a leading jet (A) as a function of their relative azimuth |Df| and pOUT = ETB sinR • No dramatic difference between PYTHIA and PYQUEN • PYQUEN radiative energy loss modifies rather the structure inside the jet, the radiation doesn’t extend much outside of the jet cone

18. g-jet correlations, direct g isolation • Direct photons form hard processes (qggq, qqgg) x large background from p0,h decays • Benefits from excellent longitudinal segmentation (0.003 for the first sampling of EMCAL) – it is possible to separate direct photons from the background using: • shower shape cuts (factor of 3-5 rejection) • applying a set of isolation criteria (factor of 10 rejection) • combination of both

19. single p0 single g p0 gg same p0 in Pb+Pb (dN/dh = 2700) same g in Pb+Pb (dN/dh = 2700) p0 gg g-jet correlations, direct g isolation • Excellent g – p0 separation • The occupancy from the underlying event is very low due to the segmentation of the strips

20. g-jet correlations g g jet jet Medium Vacuum • We make precise measurements of g-jet correlations • g doesn’t interact strongly with the medium  can be used to measure original energy and direction of a jet interacting with the medium • Can help jet analysis at low ET – can be used for the fake rejection

21. Jet RAA I.P. Lokhtin, et al. Jet RAA is sensitive to the collisional energy loss (i.e. multiple elastic scattering). Any energy loss not recoverable by the jet reconstruction leads to the softening of the spectrum. Reconstructed to input spectra without fake jet rejection. Required correction (<20% for ET,jet>80 GeV) much lower then the predicted suppression.

22. RAA and jet shapes have sensitivity to different energy loss mechanisms jet shape jet energy spectrum ○ - non-quenched ● - quenched PYQUEN with only radiative energy loss x - non-quenched x - quenched jet energy spectrum jet shape PYQUEN with only collisional energy loss ○ - non-quenched ● - quenched x - non-quenched x - quenched

23. Summary • Algorithms for the jet reconstruction in heavy ion collisions are part of the official software of the ATLAS experiment • We have implemented two independent jet finding algorithms (iterative cone and fast kT algorithms) • Variety of different measurements possible using ATLAS: • fragmentation function • jT distribution • differential jet shape • di-jet and g-jet correlations • jet RAA ... these measurements should distinguish among different energy loss mechanisms • ATLAS will make a significant impact on understanding of parton energy loss with the ability to reconstruct full jets and their properties

24. Backup slides Backup slides

25. Jet energy resolution • Cone algorithm R=0.4, 5 GeV seed, reconstructed jets matched to truth jets using DR=0.5 cut • Jet energy scale within 5% above 50 GeV, default p+p calibration used • Jet energy resolution bellow 25% for 70 GeV jets in the most central collisions (dN/dh~2700 – unquenched HIJING) Backup slides

26. Jet energy resolution, position resolution • Jet energy resolution as a function ofpseudorapidity • Forward jets reconstructed with comparable resolution as in midrapidity • Jet position resolution in f • Improves with increasing jet energy • Jet position resolution in h is comparable Backup slides

27. Efficiency and fake-rate • Efficiency is almost centrality independent – easier interpretation of jet properties vs. centrality • Above 70 GeV the efficiency is above 90% • Above 70 GeV practically no fake jets (after the fake rejection) Backup slides

28. Jet reconstruction strategy II. kT algorithm i j … reconstructs jets backwards along fragmentation chain • kT jet reconstruction: • run fast kT algorithm • separate jet from the background • subtract background from jets • calibrate jet energy

29. Comparison between kT and cone algorithm • kT algorithm has better energy resolution and efficiency at low ET • kT algorithm still under the study – running kT algorithm before the subtraction delivers smaller jets (energy at a jet periphery truncated) Backup slides

30. Backup slides: jet position resolution Backup slides

31. Backup slides: tracking performance Backup slides

32. Backup slides: jet’s tracks Shape of the jet from tracking Backup slides

33. Backup slides: Sensitivity to the jet position ○ - truth ● - reconstructed ○ - truth ● - reconstructed jet ET 70-140 GeV jet ET 70-140 GeV Background distributions subtracted but the correction on the jet position resolution not applied => visible underestimation at small jT (z is not affected much by the jet position resolution). Discrepancy can be removed using jet position determined by the cone reconstruction with smaller R. Backup slides