A stochastic process approach to multilayer neutron detectors

TL;DR

This paper introduces a stochastic process framework for analyzing multilayer neutron detectors, enabling estimation of neutron energy and absorption probabilities with proven statistical properties.

Contribution

It develops a maximum likelihood estimation method for key parameters in multilayer neutron detectors, demonstrating consistency and asymptotic normality.

Findings

MLE for absorption probability is consistent and asymptotically normal.

Derived wavelength estimator is consistent and asymptotically normal.

Provides a statistical foundation for neutron energy measurement in multilayer detectors.

Abstract

The sparsity of the isotope Helium-3, ongoing since 2009, has initiated a new generation of neutron detectors. One particularly promising development line for detectors is the multilayer gaseous detector. In this paper, a stochastic process approach is used to determine the neutron's energy from the additional data afforded by the multilayer nature of these novel detectors. The data from a multi-layer detector consists of counts of the number of absorbed neutrons along the sequence of the detector's layers, in which the neutron absorption probability is unknown. We study the Maximum Likelihood estimator for the intensity and absorption probability, show its consistency and asymptotic normality, as the experiment time (or the number of incoming neutrons) goes to infinity. We combine these results with known results on the relation between the absorption probability and the wavelength to derive an estimator of the wavelength and to show consistency and asymptotic normality for the estimator.