1. Jonathan BouchetBerkeley School on Collective Dynamics 1 Performance of the Silicon Strip Detector of the STAR Experiment Jonathan Bouchet Subatech STAR Collaboration Jonathan Bouchet Subatech STAR Collaboration

2. Jonathan BouchetBerkeley School on Collective Dynamics 2 Outline  Physics Motivation  Strangeness, Charm.  Experiment  STAR, Inner tracking device.  Description of the SSD  Components, Hit reconstruction, Calibration.  Results  Efficiency, Distance of Closest Approach (DCA), V0 reconstruction using silicon information.  Outlook  Physics Motivation  Strangeness, Charm.  Experiment  STAR, Inner tracking device.  Description of the SSD  Components, Hit reconstruction, Calibration.  Results  Efficiency, Distance of Closest Approach (DCA), V0 reconstruction using silicon information.  Outlook

3. Jonathan BouchetBerkeley School on Collective Dynamics 3 Strangeness Primary designed to do strange particles physics. Proposed and designed to enhance the STAR tracking capabilities in the central region. Improve the momentum resolution. Simulation AuAu@200GeV Enhancement of  reconstruction by a factor of 4 TPC TPC+SVT+SSD TPC+SVT

4. Jonathan BouchetBerkeley School on Collective Dynamics 4 Why not Charm ? Since few years, recent interest to measure open charm production in STAR. Pointing accuracy is the key point. How ?  Direct topological identification ex : D 0 -->K -  +  R AA of non photonic electron from B and D.  Models agree with data when only Charm is taken into account.  Need to disentangle charm and beauty contributions.  A direct measurement D-mesons is required. Nucl-ex/060712 D0D0 K-K- ++ c  = 123  m R AA

5. Jonathan BouchetBerkeley School on Collective Dynamics 5 Solenoid Magnet (0.5 T) Time Projection Chamber Silicon Vertex Detectors SVT+SSD Solenoid Tracker at RHIC

6. Jonathan BouchetBerkeley School on Collective Dynamics 6 Solenoid Magnet (0.5 T) Time Projection Chamber Inner Tracker (1) Silicon Vertex Tracker 3 layers (7,11,15 cm) of 216 Silicon Drift Detector Radiation length : 1.8%X 0 per layer

7. Jonathan BouchetBerkeley School on Collective Dynamics 7 Solenoid Magnet (0.5 T) Time Projection Chamber Inner Tracker (2) Silicon Strip Detector 1 layer (23 cm from the vertex) of 320 detection modules. Arranged in 20 ladders. Pseudo-rapidity range : -1< η < 1, Surface ~ 1 m 2.. Radiation length : 1%X0

8. Jonathan BouchetBerkeley School on Collective Dynamics 8 Silicon Strip Detector  double sided detector : P/N junction reversely biased. When a particle goes through the detector, electron-hole pairs are generated. 768 strips per side with a pitch of 95  m. Size = 42 x 73 mm 2. Intrinsic resolution : 20  m in r  (transverse plan), 700  m in Z (along the beam axis). Stereo angle : 35 mrad between strips of P and N sides for tracking constraints.  2 hybrid circuits : Support the FEE. Challenge to deal with 0.5 M readout channels !

9. Jonathan BouchetBerkeley School on Collective Dynamics 9 Hit reconstruction CuCu@200GeV (2005) Hits are essentially of type 1. (hit density is small, no ambiguity) Type 3: partial overlapping (charge matching needed) Cluster Finder Type 1Type 3 X X X X X X : real hits X : ghosts hits Cluster size distributions are good. The tail is induced by the noise 90% 10%

10. Jonathan BouchetBerkeley School on Collective Dynamics 10 Gain calibration  Since SSD are double-sided detectors, we expect the same charge deposit by MIP/particles on P and N side for each module.  Slight difference from P to N side charge (in ADC value due to electronic read-out.  Charge matching (correlation between P and N side) is used to discriminate hits from ghosts.  Gain calibration has been done for the CuCu data. Mean=0.3 adc  =11 adc

11. Jonathan BouchetBerkeley School on Collective Dynamics 11 Tracking Efficiency using SSD  Defined as a binomial distribution between number of tracks coming from the TPC with a SSD hit used over all tracks in the SSD acceptance.  Different hit reconstruction efficiency ladder by ladder.  Repass alignement procedure.  Defined as a binomial distribution between number of tracks coming from the TPC with a SSD hit used over all tracks in the SSD acceptance.  Different hit reconstruction efficiency ladder by ladder.  Repass alignement procedure. AuAu@200GeV Hijing CuCu@200GeV MC CuCu@200GeV

12. Jonathan BouchetBerkeley School on Collective Dynamics 12 Lorentz effect Observation : shift in the drift direction for SSD according to the magnet polarity. Lorentz effect : drift direction of the charge carriers affected by magnetic field. Observation : shift in the drift direction for SSD according to the magnet polarity. Lorentz effect : drift direction of the charge carriers affected by magnetic field.  Scale the values from CMS 4T magnetic field to STAR 0.5 T [1] Improvement of the efficiency caused by picking the good hit. : hit position -track position [  m] +B -B [ 1]:physics/0204078 beforeafter t

13. Jonathan BouchetBerkeley School on Collective Dynamics 13 Distance of Closest Approach  Resolution of DCA in the transverse plan limited by MCS.  Due to :  Mass (thickness of layer), distance to primary vertex.  Our case : (includes vertex resolution after alignment )  Resolution of DCA in the transverse plan limited by MCS.  Due to :  Mass (thickness of layer), distance to primary vertex.  Our case : (includes vertex resolution after alignment )  ( Dca xy )~140  m/p T (GeV) Almost to our goal in vertex resolution. Improvement on mass resolution when including at least 1 silicon hit. CuCu@200GeV K 0 s invariant mass TPC TPC+SSD+SVT

14. Jonathan BouchetBerkeley School on Collective Dynamics 14 Outlook  Microvertexing techniques using the Silicon Detector of STAR are developed for the first time in heavy ion environment for charm/beauty identification.  SSD+SVT work well, and successfully took data 2005 (CuCu).  Reprocess CuCu data with improvements is on- going [1]  Ready to analyze the current AuAu data.  The Future : STAR upgrade HFT.  Microvertexing techniques using the Silicon Detector of STAR are developed for the first time in heavy ion environment for charm/beauty identification.  SSD+SVT work well, and successfully took data 2005 (CuCu).  Reprocess CuCu data with improvements is on- going [1]  Ready to analyze the current AuAu data.  The Future : STAR upgrade HFT. [1] : Margetis et al,"Alignment Experience in STAR” to be published in CERN Yellow Report

15. Jonathan BouchetBerkeley School on Collective Dynamics 15

16. Jonathan BouchetBerkeley School on Collective Dynamics 16 Results on the hits properties by the calibration  Hits are “cleaner”  Deviation decreases with the calibration.  Hits are “cleaner”  Deviation decreases with the calibration. Calibration applied

17. Jonathan BouchetBerkeley School on Collective Dynamics 17 Efficiency vs centrality cucu@62GeV Centrality (%) 0-1010-2020-3030-40>40 Efficiency58.956.858.954.456.2 0-10 20-30 10-20 >40 30-40

18. Jonathan BouchetBerkeley School on Collective Dynamics 18 Density CuCu62, CuCu200 : Nhits/wafer ~ 4,5 AuAu200 : Nhits/wafer ~6 CuCu@62GeV CuCu@200GeV AuAu@200GeV

19. Jonathan BouchetBerkeley School on Collective Dynamics 19 Tape Automated Bonding  It allows flexible connections.  It serves as a pitch adaptator.  Good yield of production.  It allows flexible connections.  It serves as a pitch adaptator.  Good yield of production.

20. Jonathan BouchetBerkeley School on Collective Dynamics 20 CuCu data reprocess