Description
The PADME apparatus has been built at the Frascati National Laboratory of INFN to search a dark photon (A’) produced via the process e+ e− → A'γ.
The central component of the PADME detector is an electromagnetic calorimeter made of 616 BGO crystals dedicated to the measurement of the energy and the position of the final state photons.
The high beam particle multiplicity over a short bunch duration requires reliable identification and measurement of overlapping signals.
A regression machine learning based algorithm has been developed to disentangle with high efficiency, close-in-time events and precisely reconstruct the amplitude of the hits and their time with a sub-nanosecond resolution.
The performance of the algorithm and the sequence of improvements leading to the achieved results will be presented and discussed.
