Probability based data quality for energy reconstruction in high energy calorimetry

Abstract

In several engineering applications, the quality of the reconstruction of the information of interest directly interferes with the success of decision making. In modern high-energy physics experiments, the reconstruction of events is essential for the precise observation of particles and important discoveries for science. In this context, the signals from the calorimetry system provide information about the energy of the particles produced in collisions. Typically, the energy reconstruction quality is measured using the  method. However, in experiments operating in high luminosity conditions, such an approach is not able to operate under signals pile-up conditions, being only able to detect the presence of pile-up effect in the received signal. Therefore, in this work, a new approach to evaluate the quality of energy reconstruction under pile-up conditions is presented. The proposed method relies on the calculation of probabilities regardless of the energy reconstruction algorithm employed. Using simulated data for a general calorimeter system operating under different signals pile-up conditions, the results show that the use of the proposed method increases signals selection efficiency.