Physics Analysis With AliRoot

1. Physics Analysis With AliRoot Peter Hristov ALICE Collaboration NEC2005, September 16, Varna

2. Outline • The framework: AliRoot • Analysis examples • Distributed analysis and parallel analysis facility • Summary of the analysis tools in AliRoot • Conclusions P.Hristov

3. Up-to-date description of Alice detectors (geometry, physics processes, detector response, etc.) Rich set of event generators, easily extensible Possibility to use different transport packages Robust IO scheme User friendly steering classes for simulation and reconstruction Efficient tracking in the barrel detectors and in the MUON arm Elaborated reconstruction of the neutral particles Reconstruction of V0’s Combined PID based on the Bayesian approach ESD classes suitable for further analysis Detailed analysis examples Possibility to explore wide spectrum of heavy-ion and pp physics The framework:AliRoot P.Hristov

4. AliRoot Layout G3 G4 Fluka PDF HIJING GRID EGEE+AliEn VZERO CRT STRUCT HLT Virtual MC PYTHIA6 START EVGEN DPMJET RAW Monit STEER AliSimulation AliReconstruction ESD classes PMD ISAJET Analysis HBTAN JETAN FMD ITS TPC TRD TOF PHOS EMCAL RICH MUON ZDC ROOT CINT HIST GRAPH TREES CONT IO MATH … P.Hristov

5. AliRoot: Execution Flow Initialization Event Generation Particle Transport Hits AliSimulation Clusters Digits/ Raw digits Event merging Summable Digits AliReconstruction Tracking PID ESD Analysis P.Hristov

6. Event Model • RAW data; Written once, read up to 3 times. • Size: 1(pp)- 50(PbPb) MB per event. • Event Summary Data (ESD); Written up to 3 times, read many times. Contains all the information needed for analysis, fine-tune calibration and further processing into AOD. Single version for everybody. • Size: ~ 1/10 of raw per event. • Analysis Object Data (AOD); Written many times, read many times. Specific for a set of analysis tasks. • Size: ~ 1/10 of ESD per event. • Tag; Written few times, read many times. • Size: 100 B – 1 kb per event, exist many per event. • Done for fast event data selection: global experiment tags, physics working group tags, user defined tags. P.Hristov

7. Existing Analysis Examples in AliRoot • ESD analysis: • V0 & cascade reconstruction/analysis • Open charm • Specific AOD-based analysis: • HBT • Jet • V0 • MUON • Any user can contribute with additional examples and extending the functionalities P.Hristov

8. PT Distributions of ,K,p • Experimental PT distributions. • Selection of tracks from the primary vertex: cuts on impact parameters • PID: using probabilities as weights, taking the most probable type, taking type above a probability threshold,… • Corrections: • Contamination: comparison of the PID and true MC particle type. Depends on the way one obtains the exp. PT spectra. • Combined acceptance ~ Geometrical acc. x Decays x Reconstruction efficiency x PID efficiency. Depends on the primary vertex position, momentum, and occupancy => Comparison between MC kinematics tree and reconstructed particles. • Resolution: comparison between the MC and reconstructed momenta. • => The framework provides easy access to the kinematics tree. P.Hristov

9. Example Histograms: PbPb events P.Hristov

10.  Meson Mass, Width, PT Distribution, Yield • Selection of tracks from the vertex, PID of kaons. • Cuts to increase the significance (5 parameters for each pair: PT, azimuthal and polar angles, azimuthal and polar angles in the rest frame). • Effective mass distribution for all pairs of kaon candidates (global and for different PT intervals). • Effective mass distribution for the (combinatorial) background. • Event mixing: positive particles from the same event, negative from a different, but “similar” one. Similarity: close eventimpact parameters and number of negative particles. Eventplane? One might rotate all the negative tracks accordingly. • Mass resolution, combined acceptance from MC. • => The framework provides easy access to events for mixing. P.Hristov

11.  Meson Mass in pp Events P.Hristov

12. V0s and Cascades: PT Spectra, Yields • V0: pair of tracks with opposite charge, selected according to the following criteria: • Min. Allowed impact parameter(in XY) for each track. • Max. Allowed DCA between the two tracks. • Max. Allowed cosine of the V0 pointing angle. • Min. And max. Radius of fiducial volume. • Max. 2 => needs covariance matrices of the track parameters. • Cascades: V0 and “bachelor” track selected according the cuts above and in addition. • Mass window for V0. • Effective mass distribution in different PT intervals -> fit (or background subtraction from mixed events) -> experimental PT. • Corrections => Need for MC for combined acceptance, resolutions,… P.Hristov

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15. D*  D0 • Search for D0 candidate with some “loose” cuts. (See the D0 analysis classes.) combined with pion from the primary vertex -> Distribution of m(D0) - m(D0) • Secondary vertex close to the primary one. Need for precise secondary vertex finding/fitting, especially in the case of proton-proton events. • Estimation of the background distributions => event mixing • Combined acceptance, resolutions, etc. => from MC • => Classes for precise secondary vertex finding/fitting are available within the framework P.Hristov

16. Example: Jets • Leading hadrons correlations • Jet reconstruction algorithm: UA1 cone algorithm modified for HI • Cone size: R < 1 • pt cut • Background subtraction • Event by event jet identification • Jet parameters: multiplicity, kt, f(z), g-jet • Jet spectrum P.Hristov

17. Jets Pythia Hijing P.Hristov

18. Tag event • Information (meta-data) to select and analyze events of interest only via user-selected conditions • The framework (inspired from STAR) • Collects the file identifiers where to find the events • Localizes the files • Passes the events to the analysis program • Metadata (> 70 parameters) • Run specific information • Information concerning the state of LHC per ALICE run • Detector information per run • Information about each event being collected from PWG • Populated during and after ESD creation • Architecture defined, partially implemented, analysis cuts tested P.Hristov

19. Distributed analysis • Prototype demonstrated to work • Used routinely by one single user • Not yet released to general users because of major middleware reorganization (Alien2/gLite)  end 2005 • For most of the analyses the files have been “moved” to a single location to be analysed • Proposal for a Parallel Analysis Facility • Fast on line processing of data (calibration, tuning of algorithms, online physics results) • Few users (detectors and PWG experts), many x a few events, short latency • Low cost farm of dual core processors P.Hristov

20. Sub-job 1 Output file 1 Analysis Job Structure File Catalogue query User job (many events) Data set (ESDs, other) Job output Job Optimizer Grouped by SE files location Sub-job 2 Sub-job n Job Broker Submit to CE with closest SE CE and SE CE and SE CE and SE processing processing processing Output file 2 Output file n File merging job P.Hristov

21. User Interface (gShell) Universal: only one for accessing all the Grids Complete: Provides all the functionality a user might need Robust: Does not crash or hang up in case of misuse Simple: Does not require expert knowledge to run it New catalog: Fast Reliable Secure data managment: encrypted access envelopes Job agents: Response to analysis requests Priorities Quotas Transport protocol: xrootd Uniformity with Root and PROOF API: under active development, available now in Root Installation: new installation utility for easy installation AliEn2 Development P.Hristov

22. Parallel Analysis Facility • Interactive prompt analysis • Data recorded at CERN T0 • After first reconstruction pass analyze results using PROOF on CERN T1 • Check detector functioning and hot channels, calibration, alignment, physics • Prototyping in progress • Redesign of the existing analysis classes using Root selectors P.Hristov

23. PROOF PROOF PROOF PROOF Interactive Analysis with PROOF on a Large Cluster PROOF SLAVE SERVERS PROOF SLAVE SERVERS PROOF SLAVE SERVERS Slave servers access data via xrootd from local disk pools PROOF SUB-MASTER SERVER Proofd Startup Grid Service Interfaces PROOF MASTER SERVER TGrid UI/Queue UI Guaranteed site access through PROOF Sub-Masters calling out to Master (agent technology) Grid Access Control Service Grid/Root Authentication Grid File/Metadata Catalogue USER SESSION Client retrieves list of logical files (LFN + MSN) P.Hristov

24. Summary of Analysis Tools • The tools work on ESD/AOD. • Basic kinematics from Root: 3-vectors, 4-vectors, rotations, boosts, eff. masses, PT calculations • Geometrical tools: propagation of tracks, DCA, primary and secondary vertexes. • Specific: V0s, cascades -> AliV0vertexer, AliCascadeVertexer. • General: AliITSVertexerTracks. P.Hristov

25. Summary of Analysis Tools • Impact parameter of the interaction: based on ZDC energies and number of participants from ESD. • Event plane: AliFlowAnalysis. • Typical tasks: • Comparison with MC and access to the kinematics tree. Creation of “MC AOD”; • Calculation of combined acceptance (“physics efficiency”); • Background studies using the event mixing technique. P.Hristov

26. (Trivial) Practical Advises • Instantiate the objects outside the analysis loops and use setters inside. Use references instead of new objects. • Do the pre-selection of tracks and particles in single loop before the main analysis. Use indexes to access the original objects. • Use standard tools for sorting, minimization, etc. Do not rewrite the existing ROOT tools! • Load to memory when possible (example: tree->LoadBaskets()) • Foresee checks for the data consistency P.Hristov

27. Conclusions • The main tools for data analysis are available in Root and AliRoot • The analysis code based on ESD / AOD’s seems adequate, and is evolving according to feedback • The infrastructure tools for distributed analysis are under active development • Several detailed analysis examples are available • Analysis infrastructure for distributed data will be offered to test users 1Q06 P.Hristov