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A genetic algorithm approach for reconstructing spectral content from filtered x-ray diode array spectrometers.
Kemp, G E; Rubery, M S; Harris, C D; May, M J; Widmann, K; Heeter, R F; Libby, S B; Schneider, M B; Blue, B E.
Afiliação
  • Kemp GE; Lawrence Livermore National Laboratory, Livermore, California 94550, USA.
  • Rubery MS; Atomic Weapons Establishment, Reading RG7 4RS, United Kingdom.
  • Harris CD; Lawrence Livermore National Laboratory, Livermore, California 94550, USA.
  • May MJ; Lawrence Livermore National Laboratory, Livermore, California 94550, USA.
  • Widmann K; Lawrence Livermore National Laboratory, Livermore, California 94550, USA.
  • Heeter RF; Lawrence Livermore National Laboratory, Livermore, California 94550, USA.
  • Libby SB; Lawrence Livermore National Laboratory, Livermore, California 94550, USA.
  • Schneider MB; Lawrence Livermore National Laboratory, Livermore, California 94550, USA.
  • Blue BE; Lawrence Livermore National Laboratory, Livermore, California 94550, USA.
Rev Sci Instrum ; 91(8): 083507, 2020 Aug 01.
Article em En | MEDLINE | ID: mdl-32872957
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 under-determined 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 the 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 were 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.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article