GAN-Based Simulation of Triple GEM Detector in the BM@N Experiment

The triple GEM detector is one of the basic components of the hybrid tracking system in the BM@N experiment. It consists of gas chambers located perpendicular to the beam axis, designed to detect particles passing through matter. The present work describes a method for the simulation of detector response using Generative-Adversarial Networks (GAN). Special focus is given to the data preparation for training the model and forming a feature vector for the Conditional GAN (C-GAN).