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Framework for the acceptance and efficiency corrections

This framework provides utilities to assist in deriving corrections and monitoring the quality of user selections through histograms. It includes container classes, cut classes, and functionalities for projection and integration.

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Framework for the acceptance and efficiency corrections

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  1. Framework for the acceptance and efficiency corrections S.Arcelli, I.Kraus, A.Mastroserio, R.Vernet • Outline • Description • Status • Ongoing work 14/11/2007 III Convegno Nazionale sulla Fisica di ALICE A. Mastroserio

  2. General Description • Purpose: provide general utilities to assist the user in deriving the corrections and to monitor the quality of his/her selections by histograms • Requirements: • - Container to handle N dim variables Container class • - A common (easy) way to handle cuts Cut class • (event level, acceptance, kinematics, quality, being primary) • Priority list: • - single particle analysis • - V0’s (proceeding in parallel with single particles) • - resonances, decays,… A. Mastroserio

  3. Correction Framework: Container Classes AliCFFrame: public TNamed Defines the grid “frame” and methods for addressing the grid elements AliCFGrid: public AliCFFrame The equivalent of an N-dim histogram AliCFContainer: public AliCFFrame Accumulate information at different selection stages via an array of AliCFGrid, while looping on data/MC AliCFEffGrid: public AliCFGrid Calculate efficiency maps from info accumulated on a AliCFContainer, display projections (integration over other variables) AliCFDataGrid : public AliCFGridHandle observed data accumulated in an AliCFContainer, to correct them for efficiency/contamination AliCFGrid ---> THnSparse: (http://root.cern.ch/root/html/THnSparse.html ) For more details see:http://indico.cern.ch/getFile.py/access?contribId=9&resId=1&materialId=slides&confId=13028 A. Mastroserio

  4. Correction Framework: Cut Classes • - Event level (Event class, Trigger -> preliminary, the Birmingham group is working on this) • MC (Particle, acceptance -> cooperation with other people involved in acceptance studies ) • Reconstruction (Track) following the existing code in PWG0 • Selection (PID) • Provide Setters for the selections (at the track level default values will be given), then the user will add new ones according to his/her analysis • Provide the QA histos to monitor the cuts. • Have a common “IsSelected” function that returns a boolean (kTRUE, if the object has passed all the setted cuts) All the cuts are passed as TObjArray pointers to an AliCFmanager which will check the cuts and allow the container filling during the event loop A. Mastroserio

  5. Correction Framework status TODAY • We have prepared: • Container Classes • Selection Classes • Template macro for single particle spectrum - A Task inherited from AliAnalysis Task - Usage of AliMCEventHandler • Tests on Alien (ok), tests on CAF (ongoing) (---> the code is currently being rearranged for an improved integration in the analysis framework, following the feedback we received during the last offline week.) A. Mastroserio

  6. General Analysis Diagram User AnalysisTask • Loop on: • Monte Carlo • Data xxx.root • CFoutput.root filled with • AliCFContainer • histos (QA+…) CF AnalysisTask Calculate Efficiency Maps Calculate Corrections -> Corrected Data CFmacro.C: CF cut list that initializes the CF manager Post event loop For more details see: http://indico.cern.ch/getFile.py/access?contribId=10&resId=0&materialId=slides&confId=9953 A. Mastroserio

  7. Correction Framework in local mode Data Sample: Pythia 20k pp MB using AliRoot: v4-06-Rev-03 Two variables: Pt [0, 4] GeV/c and y [-1, 1] • Selections at different steps: • Step 0 = Generated particles: pions, primary, negative charge • Step 1 = Reconstructible particles: #TrackRefs in ITS =3 , in TPC = 2 • Step 2 = Reconstructed tracks: negative charge, #clusters in TPC = 50, no KinkDaughter, MaxNSigmaToVertex=1, ITSrefit. • Step 3 = identified tracks: pions, id by TPC only without probability cut with a priori concentrations = {0.,0.,0.85,0.10,0.05} A. Mastroserio

  8. Selection Steps: Pt and y spectra Step 0 Step 1 Step 2 Step3 A. Mastroserio

  9. Correction Framework : functionalities Projection 1D (integration in y) Projection 2D A. Mastroserio

  10. Correction Framework : functionalities A. Mastroserio

  11. Correction Framework : functionalities A. Mastroserio

  12. Correction Framework ongoing work (1/2) Rearrangement of the preliminary structure ongoing… • Container classes: • - Further optimization through replacement of AliCFGrid with THnSparse • Correct error handling in projections, operations (Add, Multiply, Divide...) • done and available in the next Root release. • rebinning and interpolation. Cut classes: - Inheritance from AliAnalysisCuts - Group current elementary cut classes as cuts bundles (Kinematic, Quality, being Primary,...) - Usage of AliVParticle interface wherever possible - QA histograms embedded in selection classes A. Mastroserio

  13. Correction Framework ongoing work (1/2) • Integration in the Analysis Framework • Tests on Alien done, tests on CAF ongoing • Integration of more refined acceptance selections in the CF framework cut classes • The revisited code will be committed in CVS in the first week of December After that….every user comment will be appreciated to improve the framework functionalities! A. Mastroserio

  14. Step 1 / Step 0 A. Mastroserio

  15. Step 2 / Step 1 A. Mastroserio

  16. Step 3 / Step 2 A. Mastroserio

  17. Random bin size A. Mastroserio

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