Neutron Reconstruction in the BM@N Experiment Using Machine Learning

Abstract

At present, new compact highly granular neutron detector is being developed for the BM@N experiment. This detector will be used to identify neutrons, to measure their energies using time-of-flight method, neutron yields and azimuthal flow of neutrons in heavy-ion collisions at beam energies up to 4 A GeV. Application of machine learning techniques and preliminary results of neutron identification and energy reconstruction are discussed. First predictions of the anisotropic flow of neutrons using the DCM-QGSM-SMM model of heavy-ion collisions are shown.