Electron Identification with the ALICE TRD

1. Electron Identification with the ALICE TRD Clemens Adler Physikalisches Institut Heidelberg For the TRD collaboration HCP2005, Les Diablerets, July, 6 2005

2. ALICE TRD: Identification of electrons (p>1GeV) -0.9<η<0.9 ITS TPC TRD

3. ALICE TRD principle

4. TRD in numbers • Purpose: • Electron ID in the central barrel at p > 1 GeV/c • Fast (6 μs) trigger for high-pt Particles (pt > 3 GeV/c) +PID • Parameters: • 540 modules → 767 m2 area • 18 “supermodules” • 6 layers, 5 longitudinal stacks • Length: 7 m • 28 m3 Xe/CO2 (85:15) • 1.2 million read out channels • 15 TB/s on-detector bandwidth

5. Together with TPC and ITS (dE/dx, good momentum resolution), the TRD provides electron identification sufficient to study: Di-electron channel: production of J/Psi, Upsilon and continuum (complementary to muon arm measurement). + Displaced vertex from ITS: E.g. Identify J/Psi from B decays Single electron channel: semi-leptonic decays of open charm and beauty: Handle on c+b production x-section TRD alone: L1 trigger on high-Pt particles+electron identification: Factor 100 Enhancement of potentially interesting events (PbPb). Upsilon enrichment Jets: Study “jet quenching” under LHC conditions Physics with the TRD TPC dE/dx:~7% resolution TRD pion efficiency Test beam data: 90% electron efficiency Goal

6. Quarkonia performance Central Barrel Pt-resolution B = 0.5 T Dpt/pt < 2% up to 10 GeV/c < 9% up to 100 GeV/c Signal/Background Significance Phd. thesis Tariq Mahmoud, Heidelberg

7. central AA Complete primary J/Psi suppression expected Plenty of c+b to start with • Strong (centrality dependant) secondary J/Psi production (statistical hadronization) • ->strong QGP Signal hard gluon induced quarkonium breakup hep-ph/0311048 Upsilon suppression should be observable at LHC RHIC LHC What is new at LHC

8. Large area chambers (1-1,7 m²) -> need high rigidity Low rad. length (15%Xo) -> low Z, low mass material -> Carbon reinforced sandwich construction Read Out Chambers

9. 5 chamber production sites: Bucharest (NIPNE) Dubna (JINR) GSI (Darmstadt) Heidelberg (University) Frankfurt (University) Read out chambers II • QA: • Standardized chamber building prescription • Chambers have to pass well defined set of Quality control steps Dubna 2d gain uniformity Bukarest

10. 1.2 million channels 18 channels in 1 MCM 16(+1) MCMs per readout board (4104 pc.) 260 000 CPUs working in parallel during readout Electronics

11. Electronics Status • PASA and TRAP chips ready • PASA: have full quantity • TRAP: several Wafers TRAP PASA • Readout boards: last design changes • Integration of electronics on chambers ongoing

12. Total charge spectra Counts Integrated Charge Depos. Energy (keV) Max. cluster position Likelihood distribution Extract probabilities Distribution of maximum cluster position Electron ID Typical signal of single particle LQ Method: Likelihood with total charge LQX Method: 2d-Likelihood: Total charge + position of maximum cluster

13. PID with Neural Network I Each neuron of one Layer is connected to every neuron of the following Layer. Input Layer: Charge per timebin One hidden Layer: 22 neurons Output layer per chamber: Probability to be Electron/Pion Connect 6 Chambers by NN, or multiplication of Probabilities. Submitted to NIM A, arXiv:physics/0506202v1

14. PID with Neural Network II So far analysis done for Testbeam data with 4 small prototype chambers ->extrapolation to 6 Chambers Momentum dependence of Pion efficiency • To do: • Test with higher statistics and on generalized dataset (new Testbeam data) • Try to understand this significant improvement analytically

15. Testbeam Oct. 2004 • 4 small size prototype chambers (Transition radiation spectra measurement). • 6 real size production chambers (2 different size types) • (Almost) final electronics

16. Signal in production chambers Online Event display Electrons Pions

17. Large chambers Prototype Position/Angle Resolution Angle Resolution: <0.5° Position resolution (y): 200-300 micron

18. Pion efficiency Pion efficiency slightly worse than in previous test beam Pions Points: 2002 data Lines: 2004 data 2004 Test beam data compared to 2002 Test beam data: Somewhat worse separation Electrons

19. Transition radiation Transition radiation Energy spectrum data simulation Number of produced TR photons with different Radiators Regular: foil stacks Sandwich: ALICE TRD radiator

20. Online Tracking Comparison: Online tracking ↔ Offline tracking Very Good Agreement! Outliers on per mille level due to Calculation precision Offlilne Online

21. TRD enhances ALICE Heavy flavour physics capabilities Detector mass production under way. Electronics finalized Electronics Integration in final iteration First Supermodule to be assembled end of the year Testbeam: Detector performance is well understood and satisfies design considerations Neural network approach: New test beam data (6 real size chambers, different angles, higher statistics) Can information used by NN be extracted analytically? Summary

22. TRD Collaboration Main Contributions: Germany: • Frankfurt University (IKF) • Gesellschaft für Schwerionenforschung (GSI) Darmstadt • Heidelberg University (Physikalisches Institut, Kirchhoff Institut) • Münster University (IKP) Russia: • JINR Dubna Romania: • NIPNE Bukarest Additional Subsystems: Japan: Tokyo University, Nagasaki University Greece: Athens University Germany: FH Köln, University Kaiserslautern, FH Worms, TU Darmstadt