The Highly-Granular Time-of-Flight Neutron Detector for the BM@N experiment

TL;DR

This paper introduces a new highly-granular time-of-flight neutron detector designed for the BM@N experiment, detailing its design, performance, and potential reconstruction methods including machine learning.

Contribution

The paper presents the design, development, and performance evaluation of a novel highly-granular neutron detector for heavy-ion collision experiments.

Findings

Successful neutron identification and reconstruction demonstrated

Simulation comparisons of detector layouts conducted

Various neutron reconstruction methods, including machine learning, discussed

Abstract

A new Highly-Granular time-of-flight Neutron Detector (HGND) is being developed and constructed to measure azimuthal neutron flow and neutron yields in nucleus-nucleus interactions in heavy-ion collisions with energies up to 4A GeV in the fixed target experiment BM@N at JINR. Details of the detector design and results of performance studies for neutron identification and reconstruction are shown. Comparison of simulations for different options of the HGND layout at the BM@N is presented. Several proposed methods of neutron reconstruction including machine learning and cluster methods are discussed.