Software for Optimizing Filter Stack Spectrometer Design and Unfolding Spectra

POSTER

Abstract

In this poster, we present a software suite for 1) characterizing FSS designs and 2) unfolding spectra from raw FSS data. Unfolding spectra from filter-stack spectrometers requires a detailed response matrix---the average energy deposited in each image plate per incident photon at a certain energy. In principle, the same unfolding algorithms can work for other detectors such as scintillators. We provide scripts and analysis tools that automate the creation of a response matrix using the particle transport code MCNP. We additionally provide software that, given a response matrix and raw FSS data, performs the unfold using a new perturbative minimization algorithm and produces a spectrum. This software is planned for open source release.

*Work performed under the auspices of the U.S.~DOE by Triad National Security, LLC, and Los Alamos National Laboratory. This work was supported the LANL Laboratory Directed Research and Development program. High-performance computing resources were provided by LANL's Institutional Computing program.

Publication: Wong, C-S., et al. "Reduced-order model to approximate response matrices for filter stack spectrometers." Review of Scientific Instruments 95.8 (2024).

Presenters

  • Scott V Luedtke

    • Los Alamos National Laboratory (LANL)

Authors

  • Scott V Luedtke

    • Los Alamos National Laboratory (LANL)

  • Chun-Shang Wong

    • Los Alamos National Laboratory (LANL)

  • Joseph Strehlow

    • Los Alamos National Laboratory (LANL)

  • Alemayehu S Bogale

    • University of California, San Diego

  • Avneet Sood

    • Los Alamos National Lab

  • Lin Yin

    • Los Alamos National Laboratory (LANL)

  • Brian James Albright

    • Los Alamos National Laboratory (LANL)