Speaker
Dr
Alexey Boldyrev
Description
Focusing Aerogel Ring Imaging CHerenkov detector (FARICH) is a promising particle identification technology for the SPD expertiment. A free-running (triggerless) data acquisition pipeline to be employed in the SPD results in a high data rate necessitating new approaches to event generation and simulation of detector responses. In this work, we propose several machine learning based approaches for fast simulation, generating high-level reconstruction observables as well as full Cherenkov rings using a generative adversarial network (GAN). The fast simulation is trained using simulated detector responses. We compare different approaches and demonstrate that ML-based methods produce high-fidelity samples.