Toward a fractal spectrum approach for neutron and gamma pulse shape discrimination

TL;DR

This paper introduces a fractal spectrum method for neutron and gamma pulse discrimination, demonstrating superior noise resilience and accuracy compared to traditional techniques in simulated mixed radiation signals.

Contribution

It presents a novel fractal spectrum approach that improves discrimination performance and noise robustness over existing methods in neutron detection.

Findings

Fractal spectrum approach outperforms digital charge integration and pulse gradient methods.

The method is insensitive to high frequency noise and pulse pile-ups.

It achieves higher discriminant accuracy in simulated conditions.

Abstract

There is a key research issue to accurately select out neutron signals and discriminate gamma signals from a mixed radiation field in the neutron detection. This paper proposes a fractal spectrum discrimination approach by means of different spectrum characteristics of neutron and gamma. Figure of merit and average discriminant error ratio are adopted together to evaluate the discriminant effects. Different neutron and gamma signals with various noises and pulse pile-ups are simulated according to real data in the literature. The proposed approach is compared with the digital charge integration and pulse gradient methods. It is found that the fractal approach exhibits the best discriminant performance among three methods. The fractal spectrum approach is not sensitive to the high frequency noises and pulse pile-ups. It means that the proposed approach takes the advantages of anti-noises and high discriminant ability, and can be used to better discriminate neutron and gamma in neutron detection.