A genetic algorithm approach to reconstructing spectral content from filtered x-ray diode array spectrometers

TL;DR

This paper introduces a genetic algorithm method for reconstructing spectral content from filtered x-ray diode array spectrometers, overcoming limitations of traditional models and improving spectral accuracy and robustness.

Contribution

The paper presents a novel genetic algorithm approach that reconstructs spectral intensity distributions without relying on predefined basis functions or prior spectral knowledge.

Findings

Enhanced spectral reconstruction accuracy

Robustness to hardware configuration variations

Ability to handle non-Planckian spectral distributions

Abstract

Filtered diode array spectrometers are routinely employed to infer the temporal evolution of spectral power from x-ray sources, but uniquely extracting spectral content from a finite set of broad, spectrally overlapping channel spectral sensitivities is decidedly nontrivial in these underdetermined systems. We present the use of genetic algorithms to reconstruct a probabilistic spectral intensity distribution and compare to the traditional approach most commonly found in literature. Unlike many of the previously published models, spectral reconstructions from this approach are neither limited by basis functional forms, nor do they require a priori spectral knowledge. While the original intent of such measurements was to diagnose the temporal evolution of spectral power from quasi-blackbody radiation sources, where the exact details of spectral content was not thought to be crucial, we demonstrate that this new technique can greatly enhance the utility of the diagnostic by providing more physical spectra and improved robustness to hardware configuration for even strongly non-Planckian distributions.