RICH Run 2 performance paper

Here we will list the progress towards a RICH performance paper for Run 2

General structure

We need to talk about the things that go into the PID, i.e. resolutions, photon yields, calibrations and alignments, then give the PID performance.

Available tasks

Overview Description Time estimateSorted ascending People
Mirror alignments Mirror alignments are getting their own paper, so maybe nothing needed here? 0 min?  
Time alignment All time alignment data has been analysed, so the minimum here is to track down the output and make a pretty plot. We could study how the timing of boards have varied throughout the years, that could be nice. All the processed timing scans are in /group/rich/timing/, the details of each run in that directory can be found in the RICH logbook. For the plot there is a script in the RichTimingScanAnalysis package called makeOfficial.py that make plots like: that can be used and updated. 20 min - 1 day?  
Resolutions Conceptually simple (a gaussian peak with a background), the tricky part is dealing with the background. This could be reduced by working with low occupancy events, e.g. the low multi dimuon line, which is pretty clean. An example is here: . The difference between a flat background and a quadratic would give a systematic of 2-3%. Would hope to improve that, but maybe we just live with it. Even so relative studies can still be done, comparing the resolutions in different running conditions, for different sections of the detector, as a function of time, etc.    
Photon counting This often gets stuck in definitions of which tracks matter and what a yield is. We can pick a definition... Also there has been some success in using a a background subtraction rather than assuming a signal shape. Similar to the resolutions, relative studies can be done in space, time and conditions.    
Calibration Studies of refractive index stability, etc. HPD image movements    
MDCS corrections Study the stability in time? Maybe formalise the psuedo data driven parameter choice (i.e. we stuck them in the mirror alignment to see what happened). I don't think data based optimisation we played with was developed far enough. Maybe the RAL studies. Donal's 3% radius correction studies didn't make it into the last paper?    
PID performance Reuse the framework Iwan created. Again, stability in time and with conditions    

Drafts and presentations

Something something overleaf

Topic attachments
I Attachment History Action Size Date Who Comment
PNGpng low_mult_dimuon_res.png r1 manage 26.3 K 2019-02-12 - 15:09 MichaelMcCann  
PNGpng timing_scan_205938.png r1 manage 56.7 K 2019-02-18 - 12:24 MichaelMcCann  
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Topic revision: r4 - 2019-02-18 - MichaelMcCann
 
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