Abstract
We present an inversion method capable of robustly unfolding MeV x-ray spectra from filter stack spectrometer (FSS) data without requiring an a priori specification of a spectral shape or arbitrary termination of the algorithm. Our inversion method is based upon the perturbative minimization (PM) algorithm, which has previously been shown to be capable of unfolding x-ray transmission data, albeit for a limited regime in which the x-ray mass attenuation coefficient of the filter material increases monotonically with x-ray energy. Our inversion method improves upon the PM algorithm through regular smoothing of the candidate spectrum and by adding stochasticity to the search. With these additions, the inversion method does not require a physics model for an initial guess, fitting, or user-selected termination of the search. Instead, the only assumption made by the inversion method is that the x-ray spectrum should be near a smooth curve. Testing with synthetic data shows that the inversion method can successfully recover the primary large-scale features of MeV x-ray spectra, including the number of x-rays in energy bins of several-MeV widths to within 10%. Fine-scale features, however, are more difficult to recover accurately. Examples of unfolding experimental FSS data obtained at the Texas Petawatt Laser Facility and the OMEGA EP laser facility are also presented.
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AIP Advances
Nuclear Instruments and Methods in...
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Published
Feb 01, 2024
Vol/Issue
95(2)
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Authors
Funding
Los Alamos National Laboratory Award: 20220018DR
U.S. Department of Energy Award: DE-SC0021125
Cite This Article
C.-S. Wong, J. Strehlow, D. P. Broughton, et al. (2024). Robust unfolding of MeV x-ray spectra from filter stack spectrometer data. Review of Scientific Instruments, 95(2). https://doi.org/10.1063/5.0190679
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