Deconvolution of multi-Boltzmann x-ray distribution from linear absorption spectrometer via analytical parameter reduction

Tools

Armstrong, C. D. and Neely, D. and Kumar, D. and McKenna, P. and Gray, R. J. and Pirozhkov, A. S. (2021) Deconvolution of multi-Boltzmann x-ray distribution from linear absorption spectrometer via analytical parameter reduction. Review of Scientific Instruments, 92 (11). p. 113102. 113102. ISSN 0034-6748 (https://doi.org/10.1063/5.0057486)

[thumbnail of Armstrong-etal-RSI-2021-Deconvolution-of-multi-Boltzmann-x-ray-distribution-from-linear-absorption-spectrometer]
Preview
 Text. Filename: Armstrong_etal_RSI_2021_Deconvolution_of_multi_Boltzmann_x_ray_distribution_from_linear_absorption_spectrometer.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo
Download (5MB)| Preview

Abstract

Accurate characterization of incident radiation is a fundamental challenge for diagnostic design. Herein, we present an efficient spectral analysis routine that is able to characterize multiple components within the spectral emission by analytically reducing the number of parameters. The technique is presented alongside the design of a hard x-ray linear absorption spectrometer using the example of multiple Boltzmann-like spectral distributions; however, it is generally applicable to all absorption based spectrometer designs and can be adapted to any incident spectral shape. This routine is demonstrated to be tolerable to experimental noise and suitable for real-time data processing at multi-Hz repetition rates.

ORCID iDs

Armstrong, C. D., Neely, D., Kumar, D., McKenna, P. ORCID logoORCID: https://orcid.org/0000-0001-8061-7091, Gray, R. J. ORCID logoORCID: https://orcid.org/0000-0003-0610-9595 and Pirozhkov, A. S.;
CORE (COnnecting REpositories)