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Decision of bad or hot in FMS
- Goal: set the standards for bad/hot channels to be excluded before calibration
- Conclusion:
a. Judging hot / bad from # of entries or ADC spectra alone looks inappropriate
b. I suggest at the beginning of the iteration (calibration) exclude only "apparently bad" cases,
then judge / exclude additional bad channels based on 1st reco. mass along with ADC spectrum
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- Hot channels
1-a. Conventional bad/hot channels decision
- Collected ADC vs. channel by using "physics stream + single MB trigger (st_physics + VPDMB30) ".
- Saved ADC range: " 3 < ADC < 250 ". To cut out pedestal tail & To see the spectra clearly
- For the decision, use "# of ADC entries of a cell / # of trigger (left)" and "Each cell's ADC spectrum (right)".
1- b. Complication- High online calibration case: a cell with relatively large # of entries does NOT guarantee it's hot.
i.e. a cell with high online gainCorr -> more frequently triggered, ends up with more entries,
but it can be properly corrected in offline calibration. Simply masking it out can be dangerous.- Possible instability in pedestal subtraction: out pedestal subtraction precision isn't 100 %.
If a cell has relatively long pedestal tail, it is likely the cell's # of entries will be larger than its vicinity.- Channels with high bit shift: if I try to judge hot channels by comparing each ADC spectrum,
channels with positive (+) bit shift will have relatively larger entries in same ADC bin. - Bad channels
2-a. Channels apparently bad
- Some channels' ADC distribution looks utterly bad. These cells definitely need to be excluded
- Following plot shows marked "apparently bad" in currently ongoing iteration (Apr. 29)
- Channels d11_209 and d11_210 were decided bad by independent QA
2-b. Channels with high bit shift >= 4- BS = 4 channels in RUN15 day 80-81, ADC (left) and reco. mass (right, ongoing iteration)
- Cells with gainCorr = 1.0 means they were reintroduced to check if they can be used
- 10 / 14 look decent to be used- BS = 5 channels, in RUN15 day 80-81
- 11 of 14 look bad
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