...
- Basic version of the code: tagghosts.C
- Another version of the code, algorithm is the Johan's one, but output is a tree with number of tagged xtals and sum-of-energy of tagged xtals for the first 3 cluster Pass8 tag calorimeter ghost with trigger diagnostic information tagghosts_v1.C .
Overlay energy for tagged cluster
...
- Johan algorithm works fine!
- Clusters with at least one ghost-tagged xtal tend to have large overlay energy.
- It never happen that overlay energy is 0 and there is some ghost-tagged xtal. The 'purity' of such selection is ~1.
- Efficiency is low. We can't tag a good fraction of ghost clusters in this way.
- There are few events with low overlay energy and low ghost-tagged energy. After looking at event displays I think we can consider good cluster is the ghost-tagged energy is <~3%
- My suggestion for ghost tagging ghost clusters in is "TagGhostNumXtals>0 && (TagGhostRawEnergySum/CalawEnergySum)> 0.03"
- We can include this algorithm just after clustering, and then tag ghost clusters. Not sure how we should use this info:
- Select best cluster only if non ghost-tagged - what happen if the best cluster is also a ghost (i.e. there are no other options?)?
- Use this info in tracking ( e.g. knowing that the direction is likely to be wrong). Need Tracy here...
- Use in event-level analysis to select events with useless cal information (and treat them as tracker only if possible)
Ghost number and cluster classification
...