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- Code and method
- Overlay energy for tagged clusters (MonteCarlo AG)
- Efficiency with Periodic Triggers
- Effect on Flight Data IMPORTANT
- Ghost number and cluster classification
- Event display
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- open digi, recon, merit and relation files
Wiki Markup - open recon and loop on clusters, then for each cluter
- open the corresponding crystal collection
- check if any crystal end has more than 100 MeV (or whatever other threshold)
- if any, then look if the corresponding layer end has a trigger bit set
- if not so, fill in a map of missing trigger bits and add 1 to a so called "cal ghost number"
- for each cluster, the higher the ghost number, the higher the probability that it's a ghost... but it looks like that above 2, they're all ghosts.
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A cut is applied to select good gamma rays:
"FswGamState==0 && TkrNumTracks > 0 && CalEnergyRaw > 5 && CalCsIRLn>4 && CTBCORE>0 && CTBBestEnergyProb>0.1 && CTBClassLevel>2 && FT1ZenithTheta>112 && FT1ZenithTheta<115"
Cal xtals are tagged with the most conservative algorithm described above: energy >120MeV and no cal_lo trigger in both xtal ends.
Top panel of plot below shows the distribution of (log10 of) deposited energy for:
all sample, events with at least 1 ghost-tagged xtal, events with at least 1 ghost-tagged xtal & > 50% of ghost-tagged energy fraction
Bottom panel of plot below shows the correlation between number of ghost-tagged xtals and ghost-tagged energy (zero suppressed)
It looks like that almost all good gamma events have at least one ghost-tagged xtal and even requiring a large ghost-tagged energy we select a large fraction of events
I also looked at a couple of events that are "ghosty" according to this algorithm:
they look like perfect gamma-ray in which also the old reconstruction works fine
Evt Id 130047 | Evt Id 333286 |
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8 tagged xtals | 32 tagged xtals |
In conclusion, this algorithm cannot be applied to flight data.
Ghost number and cluster classification
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