Signal and Noise Analysis in TRION -Time-Resolved Integrative Optical Fast Neutron Detector

TL;DR

This paper analyzes the signal and noise characteristics of the TRION fast neutron imaging detector, revealing that energy integration introduces additional noise factors beyond quantum noise, affecting detector performance across various neutron energies.

Contribution

The study provides a detailed Monte-Carlo analysis of signal and noise processes in the TRION detector, highlighting the impact of energy integration on noise beyond quantum limits.

Findings

Excess noise factor varies with neutron energy, from 1.9 to 4.3.

Energy fluctuations significantly contribute to noise in integrative detectors.

Quantum noise limitation is not achievable in energy-integrating neutron detectors.

Abstract

TRION is a sub-mm spatial resolution fast neutron imaging detector, which employs an integrative optical time-of-flight technique. The detector was developed for fast neutron resonance radiography, a method capable of detecting a broad range of conventional and improvised explosives. In this study we have analyzed in detail, using Monte-Carlo calculations and experimentally determined parameters, all the processes that influence the signal and noise in the TRION detector. In contrast to event-counting detectors where the signal-to-noise ratio is dependent only on the number of detected events (quantum noise), in an energy-integrating detector additional factors, such as the fluctuations in imparted energy, number of photoelectrons, system gain and other factors will contribute to the noise. The excess noise factor (over the quantum noise) due to these processes was 4.3, 2.7, 2.1, 1.9 and 1.9 for incident neutron energies of 2, 4, 7.5, 10 and 14 MeV, respectively. It is shown that, even under ideal light collection conditions, a fast neutron detection system operating in an integrative mode cannot be quantum-noise-limited due to the relatively large variance in the imparted proton energy and the resulting scintillation light distributions.