Advances in Analysis of Microcalorimeter Gamma-Ray Spectra

Abstract

Microcalorimeters based on transition-edge sensors (TESs) have been successfully deployed in numerous spectroscopic instruments that operate over a large range of incident photon energies. TES microcalorimeter arrays combine unmatched energy resolution with broadband spectral coverage and high quantum efficiency. An important application requiring these characteristics is nondestructive isotopic analysis via gamma-ray spectroscopy of the complex mixtures of actinide isotopes found in the nuclear fuel cycle. Steady progress has been made over the last ten years to develop TES microcalorimeter instruments for this application, leading to arrays that demonstrate significantly better energy resolution than the state-of-the-art high-purity germanium (HPGe) sensors. However, further algorithm development and automation of the data analysis procedure have been required to bring these systems closer to being ready for production use. In this article, we describe recent advances in data analysis techniques for gamma-ray data acquired with microcalorimeter systems. In particular, we discuss new approaches to automated calibration of our spectra, and a new approach for quantifying the uncertainty of peak area estimation for isolated peaks. Our data analysis pipeline has also been automated, requiring minimal manual intervention for full processing of data sets, with performance that is sufficient to allow future deployment of real-time spectrum generation. We show that, using this pipeline, we are able to achieve ~0.25% statistical uncertainty in isotope ratios, which indicates that if systematic errors are controlled, microcalorimeter arrays can achieve better than 1% total uncertainty in these measurements.