Bdst analyse

From: Claus O. E. Jorgensen (ekman@nbi.dk)
Date: Tue Nov 19 2002 - 11:00:38 EST

  • Next message: murray@comp.tamu.edu: "Re: Bdst analyse"
    Hi analyzer,
    
    After some correspondence on the analysis of the dbsts I have 
    now written up some thoughts on how to get on with the analysis 
    from the bdsts. The ambition is to end up with some kind of
    standard analysis method in the future.
    As Jens-Ivar pointed out this discussion should be on the dev-list
    and as Flemming pointed out we should (think a bit and) agree 
    before we do the coding (thanks for the comments).
    
    What we want to do:
    
    - Select events
    - Select good tracks
    - Identify particles
    - Evaluate efficiencies
    - ???
    
    I like the way it is done in the Bdst{Mrs,Fs}Ana (the new versions of
    Br{Mrs,Fs}DstAna) modules. The basic idea is to scan the data and
    determine various constants for event selection, momentum
    determination, track selection and pid selection (in the code these
    scans is called the prepreloop and preloop). The found constants are
    then used when selecting events, tracks and identified particles in the
    final loop over all events and tracks.
    
    What are these constants and how are they determined?
    
    Event Selection:
    
       - Difference in bb and zdc vertex (mean and sigma).
         Determined by fitting a simple histogram (bbVtxZ - zdcVtxZ)
         which is filled in the preloop.	
         A nSigma cut can then by applied in the "real" loop.
    
       - Vertex range. Set by the user.
    
       - Centrality range. Set by the user.
    
       - Good trigger.
    
    
    Track Selection:
    
       - Track to vertex (meanZ, sigmaZ, meanY, sigmaY)
         Determined by fitting histograms filled in the preloop.
    
       - Good track status.
    
       - Fiducial cuts?
    
    
    Pid Selection:
    
       - Constant determining the expectation curves (for example mass2)
         for each particle for each pid detector. Found by fitting
         histograms filled in the preloop.
    
       - Sigma from expectation curve (momentum dependent).
    
       We can maybe have a method that return the number of sigmas from
       the expectation curve for a given particle specie, or? 
       I don't think there's anything wrong in "fine-tuning the 
       calibrations" at this point (the alternative is several iterations
       of the calibrations to get the 100% correct values).
    
    Efficiency:
    
       - Pawel is the expert in this and I'll not try to describe it, but
         I think it should be in a separate module.
    		
    This stuff described above is actually not so far from what is in
    the code now. Maybe we can split the tasks into several modules, or?
    I would like to try to put the skeleton together, then we can always
    discuss the details...any comments or suggestions?
    
    How can we implement the pp (or d+Au) in such a framework? How do want 
    to pass on the information (at this point it's saved in a ntuple which
    adds another step in the analysis chain)?
    
    Cheers,
    
    Claus
    
    +------------------------------------------------------------+
    | Claus E. Jørgensen                                         |
    | Cand. Scient.                  Phone  : (+45) 33 32 49 49  |
    |                                Cell   : (+45) 27 28 49 49  |
    | Niels Bohr Institute, Ta-2,    Office : (+45) 35 32 54 04  |
    | Blegdamsvej 17, DK-2100,       E-mail : ekman@nbi.dk       |
    | University of Copenhagen       Home   : www.nbi.dk/~ekman/ |
    +------------------------------------------------------------+
    


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