ClusterID:The Project
The ClusterID package contains all the necessary functionality to do physics analysis and evaluate calorimeter designs. However, improvements to its resolution are possible in many areas. One can always try to develop additional discriminators and algorithms to increase the efficiency of identification, decrease the fake rates and improve the energy resolution. Regarding overlapped clusters which contain hits from more than one particle, there are techniques available to try to separate the cluster into two or more clusters. Regarding a particle which created a main cluster and a separate fragment cluster, there are techniques available to try to associate fragments with the primary cluster. And there are other areas for further development as well.
In the course of LCD studies several people have made studies of some of these specific issues outside of any framework for calorimeter reconstruction. The ClusterID project provides a way for people to incorporate these techniques into the ClusterID package and use the various tools for evaluating and improving the efficacy of their particular technique. Also, the project has a long list of ToDos that have arisen as it was being developed. For people who are interested in getting involved in calorimetry software selecting a project off of the ToDo list is a handy way to get familiar with the package, which is quite complex, as well as to make a contribution to the overall LCD studies.
ToDo List:
Adding stages to Particle Reconstruction:
Contributors:
Gary Bower, SLAC
Gary Bower, SLAC
Ron Cassell, SLAC
Mark Donsillman, SLAC
Ayanah George, SLAC summer student
Tony Johnson, SLAC
Ayodele Onibokun, SLAC summer student
Saurav Pathak, U Penn
LINKS to contributed projects.
List specific projects and outline how the might be done. Include tutorials to try first and tutorials to evaluate results and outline code to do the project.
Cluster Association: Start with list of frags ordered by energy and list of hads ordered by energy. Take perhaps top 10 on each list and calculate the 100 pairs worth of DOCAs
Cluster seperation: 1) increase min hit energy until it splits into two and apply CLusterID to each. First, find a way to add low energy hits back to the clusters in a rational way, or if C% of energy is cut and C1% and C2% is energy remaining in the two clusters redistribute the energy proportionally if using the reduce clusters gives better pointing resolution, otherwise add the hits back. 2) Maciel approach 3) Vishnu approach. Maybe with all three approaches start with NxN adjacency and do some kind of smoothing of energy over hits, ie, each hit gets the energy of hit + its 26 nieghbors divided by 27.