Genetic Algorithm for determination of the event collision time and particle identification by time-of-flight at NICA SPD

TL;DR

This paper presents a genetic algorithm-based method for fast and accurate determination of collision time and particle identification using time-of-flight data at the NICA SPD experiment, improving computational efficiency.

Contribution

The paper introduces a novel genetic algorithm approach for collision time determination, enhancing speed and accuracy over traditional methods.

Findings

Genetic algorithm achieves high accuracy in collision time estimation.

The method improves particle identification efficiency.

Computational speed is significantly increased.

Abstract

Particle identification is an important feature of the future SPD experiment at the NICA collider. In particular, identification of particles with momenta up to a few GeV/c by their time-of-flight will facilitate reconstruction of events of interest. High time-resolution of modern TOF detectors dictates the need to obtain the event collision time t0 with comparable accuracy. While determination of the collision time is feasible through the use of TOF signals supplemented by track reconstruction, it proves to be computationally expensive. In this work we have developed a dedicated Genetic Algorithm as a fast and accurate method to determine the pp-collision time by the measurements of the TOF detector at the SPD experiment. By using this reliable method for t0 determination we compare different approaches for the particle identification procedure based on TOF-signals.