1. Experience with analysis of TPC data Marian Ivanov

2. Outlook TPC analysis Tasks Strategy Component model “Pseudo” online analysis of data TPC planning

3. TPC analysis tasks Reconstruction Calibration QA Physics analysis

4. Component model (0) Analysis tasks to be run in different environment Production – scope > 10^7 events Alien - calibration and QA using tracks DAQ – calibration and QA using raw data HLT - calibration and QA using tracks Code development, fine tuning – scope ~ 10^5 events Main goal – prepare stable code for Production mode Test the code before software releases Enable fast feedback for hardware experts Functionality of a component doesn't depend on the environment Clearly defined Input and Output e.g components developed for DAQ can run in HLT

5. Component model (1) Interface: Input Process(AliESD *) Process(AliTPCseed*) Process(AliRawReader*) Postprocessing Merge() Analyze() ExportQA() Output – Component itself, or QA folder

6. Component model (2) Event loop outside of components – light wrappers on top of components Offline implementation AliAnalysisTask->AliTPCAnalysisXXX DA (Calibration) maker schema to be adopted – merged with QA framework HLT implementation – AliHLTTPCComponentXXX DAQ implementation – TPCXXXda.cxx Macros - TPCXXX.C

7. “Pseudo”-online analysis (0) Input - Options Files registered in Alien file catalog - Default Directly Castor Output - Options Alien storage element – Default (usually GSI::SE) XRD cluster Data volume Output size / Input size ~ 10^-3 Timing – appropriate “pseudo”-online analysis to be triggered by TPC software shifter after registration of the data in the file catalog

8. “Pseudo”-online analysis (1) Job list Job agent Job description: Input Output Action Status Job description – text file created by AlienToolkit (interface to TAlien,TAlienCollection) Action – corresponds to the name of a root analysis macro (rec.C,KRClusterFinder.C,...) Job agents – can be run locally (first tests) or on a batch system Loop on agent: ● until(GetNextJob()){ ● Check the availability of job input data ● if(!staged) {stage(); continue;} ● Lock the job ● Process job ● Transfer output data } Job agent init: ● Check the environment ● Aliroot,Root,Alien,gcc ● Check the Output SE ● Make report ● if (problem) exit AlienToolkit t t.MakeCollection t.MakeJobList

9. “Pseudo” online analysis (2) Presented schema (agent + pull mechanism) similar to AliEn Main application: Tuning of the reconstruction algorithm – custom AliRoot Verification of the Calibration algorithm In case of suspicious results of online calibration (DAQ or HLT) the reasons have to be understood Performance scaling – linearly with the amount of the job agents One lsf job – one job agent Actual jobs – in special process created by agent Robust - In case of particular job crash – job agent non affected

10. “Pseudo” online analysis (3) TPC February test 2 job types used rec – 2 reconstruction passes KrClusterFinder – 2 reconstruction passes 200 agents submitted to the CERN batch farm (GSI farm also tested) Feed-back time ~ hour(s) Modified reconstruction code committed to the svn To be used in the following central production on Alien Direct usage of the TPC algorithm on Alien Possible to use plain Root + TPC par + all needed AliRoot libraries Not possible before, because par file couldn't be compiled

11. TPC planning for May, June

12. Plans for tests in May, June - Production DAQ calibration algorithm – Ready Full chain – DA=>FXS=>OCDB Calibration results and algorithm well tested Possible to use results of such calibration in production reconstruction Calibration using tracks and Laser Not verified yet using real data – Will be not used for first iteration Gain calibration using Krypton Procedure tested – but, until now only C-side Planned to be used immediately after finishing Kr calibration on both sides Event type information needed for automatic reconstruction not yet implemented – Waiting for new RCU format

13. Plans for tests in May, June - Production General strategy – In production reconstruction, use only reliable, well tested calibration parameters The influence to the physic performance summarized during Prague Physic week

14. Gain calibration ● Krypton calibration ● A. Matyja, MI, J.Otwinowski, (S. Gaertner) ● Time dependence of the gain using GOOFIE ● Reconstruction: Simple multiplication to be performed on the dE/dx level ● Components: J. Castillo, M.Siska, MI ● FXS-SHUTTLE: Haavard ● Verify algorithms for calibration using tracks with the Krypton calibration (until now only verification using MC data) ● Components: MI, (S.Gaertner), A. Kalweit ● HLT component: J.Otwinowski, MI, M. Richter ● Calibration using tracks as a quality assurance ● QA extension of calibration components: A. Kalweit, MI

15. ExB effect ● Construct ExB correction table using measured magnetic field – Done ● Verify correction table using laser scan with different B fields (-0.5.. -0.2.. 0..0.2 0.5 T) ● To be done ● Adjust omega-tau factor (uncertainty ~20 %) ● Fit the mean angle between E and B vector (2 order correction) ● Estimate systematic effects ● Systematic effect to be added to the Covariance matrix of the track ● MI, M.Mager

16. Drift velocity ● Options: ● Goofie calibration + DCS values (T, P) - (ONLINE) ● Time dependence (Goofie) - to be corrected for the T and P at TPC ● Space dependence DCS values (T,P) – linear fit ● Relative precision 0.05% (1 mm at vertex) ● Laser Central electrode - (ONLINE) ● Space and time dependence of drift velocity ● Relative precision ~ 0.01 cm/250cm ~ 0.004 % ● Byproduct – unlinearities calibration – tuning of skirt voltage ● Calibration using tracks – (OFFLINE) ● Track crossing central electrode ● Reconstructed primary vertex position using the tracks from A and C side of the TPC ● Relative precision ~ 2 mm / sqrt(Nevents) ● ITS alignment – Kalman filter with w drift as parameter– under investigation ● MI, J.Wiechula, J.Castillo, M.Siska, M.Mager, ITS responsible(...)

17. Conclusion Central first pass reconstruction will be performed with partially calibrated TPC Expected performance of the partially calibrated TPC sufficient for Physic papers The presented software schema for fast development and tests of analysis code enable us to shorten time between the first pass reconstruction and second pass, with a fully calibrated and understood TPC