Re: ZDC data reduction

From: Christian Holm Christensen (cholm@hehi03.nbi.dk)
Date: Mon Jan 08 2001 - 13:23:18 EST

  • Next message: Bjorn H Samset: "Re: ZDC cut efficency vs multiplicity"

    Hi all, 
    
    I'd like comment on the centrality determination in general. I
    should point out, that this is work in progress (Claus, Erik, and I
    are looking in to it), and should not be taken as final. Also I like
    to make no claim to correctness, and will appreciate any
    thought/input/corrections any of you may have. 
    
    There are several things to consider when trying to determine the
    centrality at BRAHMS. These has to do with the infamous vertex
    location, minimum bias, trigger and so on, in short - not easy.
    
    First of, we'd like to say something like "this event is 0-5% central,
    and that one is within 10-15%". This obviously require that you scan a
    large number of events and in some way try to characterise the
    centrality of the events. The current consensus is to use the total
    ADC of the scintilator tiles in the multiplicity array (PTMA -
    Photo multiplier Tube, Multiplicity Array). 
    
    Then one should say what "0-5%" really means. That is, I believe sort
    of obvious: Histogram the number minimum bias events based on the ADC
    sum from the PTMA, integrate that, find the top most 5% of that
    integral, and make a cut there. That's the threshold ADC from the PTMA
    characterising the 5% most central events. 
    
    Then comes the question "What is a minimum bias trigger?". Well,
    Flemming has previously stated that trigger 4 (ZDC coincidence) is the
    minimum bias trigger. However, trigger 4 is drastically down scaled in
    later runs, giving very poor statistics for the histogram(s) (more on
    the histograms below), so one is tempted to include all triggers
    (1, 4, 5, and 6) which however isn't trivial since one need to correct
    for the down scaling. 
    
    So what one can do, is to take runs where trigger 4 isn't down scaled,
    find the ratio of trigger 6 to trigger 4, and use only trigger 6
    events on later runs, correcting with the factor previously found. 
    
    Also, one should note the format of the trigger word: It's a 16 bit
    number, composed of two 8 bit bit masks, the lower 8 bits constitutes
    the first 0xXX, and the upper 8 bits the second 0xYY00. The first mask
    is the triggers that the DAQ actually got - i.e., before scale down -
    and the second is the triggers after the scale down was
    performed. E.g., if the 16 bit trigger word is 
    
    	   8240  =  0x2030      = 00100000 00110000
    	   (dec) = (0xYYXX hex) = (xxxxxxx yyyyyyyy bin)
    
    then the DAQ got trigger 5 and 6, but the trigger 5 was scaled
    down. The class BrEventManager tests the first 8 bits (0xXX), which
    can be misleading I believe. 
    
    I'd like to take this opportunity to encourage Flemming to put
    something on the web describing the triggers, Konstantin to put
    something on down scaling and the trigger words, and for everyone to
    think about how to normalise down scaled triggers - if anyone has any
    idea, please let me know, since I'm not sure I got it yet. 
      
    So assuming we've got min bias events - currently, Claus takes trigger
    6, plus trigger 4 without trigger 6 (scaled) as min bias events and
    histogram those - we're not home free yet, and this has to do with the
    infamous wide distribution of the vertex! 
    
    The point is, an event with a high numerical z-component of the vertex
    (Vz) will have another ADC response in the PTMA then an event with low
    Vz and the same centrality. This is evident if one make the 2D
    histogram of events, based on ADC and Vz. Hence, the 5% cut is
    dependent on where the vertex is at a given event! This is not a small
    effect! The 5% limit varies 33% from |Vz| ~ 0-6cm to 33-45cm. 
    
    This vertex dependent threshold - we believe - is the most
    assumption-free way of obtaining the 5% limit - or any other for that
    matter - since it only assumes translational invariance and rotation
    invariance around the z-axis! 
    
    So we also need to determine Vz before we can determine the
    centrality. Here we _must_ use the ZDCs to determine Vz, so that we
    do not introduce a further bias, as would be the case had we chosen
    the Beam-Beam method to obtain Vz. 
    
    Finally, we need to correct the ADC values from the individual tiles
    for the variation in the path length in the tiles - as outlined by
    J. H., Jens Jorgen & Erik. This correction, is probably not very big
    in terms of the 5% threshold, but for a single event is may be
    extremly important, and Erik has some code that does this. 
    
    I should also like to point out the statistical difficulties in
    this. One may feel tempted to do al sorts of weird corrections, like 
    reflecting tiles to create pseudo-tiles, ignoring some tiles either
    because of geometry or high response, and so on. All such cuts will
    inevitably bias the result unwantedly. 
    
    Again, this is work in progress and any comments will be greatly
    appreciated. Although most of the code is written, is generally in
    the form of scripts, and are not really ready for inclusion into
    BRAT. We anticipate two modules: one that calculates the threshold at
    certain points in (Vz, centraility)-space - basically a sort of
    calibration - and one, given an event, determinds the lower and upper
    bound of the centraility - based on the calibration - and stores it in
    the output eventnode, for other modules to inspect.  
     
    Yours, 
    
    Christian  -----------------------------------------------------------
    Holm Christensen                             Phone:  (+45) 35 35 96 91 
      Sankt Hansgade 23, 1. th.                  Office: (+45) 353  25 305 
      DK-2200 Copenhagen N                       Web:    www.nbi.dk/~cholm    
      Denmark                                    Email:       cholm@nbi.dk
    



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