An important part of calorimetry will be finding electron and photon showers. These showers are very similar, depositing most of their energy in the EM calorimeter, but electron showers have tracks leading to them. The first step is to find clusters that lie mainly in the EM calorimeter and use information about these clusters to train an HMatrix which can be used to categorize them. I will be using the electron and pion datasets to find appropriate measurements to distinguish the two and then test this heuristic with rho -> gamma + gamma and rho+ -> pi+ + gamma events.
Clustering
The first step is to create clusters. Since we are looking for small clusters in the EM cal, we can hope they will be contiguous. Thus we use a Nearest Neighbor clusterer which only adds cells to the cluster which are directly adjacent to those within it:
nnClusterer = new NearestNeighborClusterer(1,1,1,0,0.0);