Abridged spectral matrix inversion: parametric fitting of X‐ray fluorescence spectra following integrative data reduction

Recent improvements in both X‐ray detectors and readout speeds have led to a substantial increase in the volume of X‐ray fluorescence data being produced at synchrotron facilities. This in turn results in increased challenges associated with processing and fitting such data, both temporally and comp...

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Bibliographic Details
Published in:Journal of synchrotron radiation 2021-11, Vol.28 (6), p.1881-1890
Main Authors: Crawford, Andrew M., Huntsman, Ben, Weng, Monica Y., Ponomarenko, Olena, Kiani, Cheyenne D., George, Simon J., George, Graham N., Pickering, Ingrid J.
Format: Article
Language:English
Subjects:
abridged matrix inversion
Algorithms
Data reduction
Fluorescence
INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY
Linear algebra
M-BLANK
Mathematical analysis
Matrices (mathematics)
Research Papers
Spectra
Synchrotrons
X‐ray fluorescence
X‐ray fluorescence imaging
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Summary:Recent improvements in both X‐ray detectors and readout speeds have led to a substantial increase in the volume of X‐ray fluorescence data being produced at synchrotron facilities. This in turn results in increased challenges associated with processing and fitting such data, both temporally and computationally. Herein an abridging approach is described that both reduces and partially integrates X‐ray fluorescence (XRF) data sets to obtain a fivefold total improvement in processing time with negligible decrease in quality of fitting. The approach is demonstrated using linear least‐squares matrix inversion on XRF data with strongly overlapping fluorescent peaks. This approach is applicable to any type of linear algebra based fitting algorithm to fit spectra containing overlapping signals wherein the spectra also contain unimportant (non‐characteristic) regions which add little (or no) weight to fitted values, e.g. energy regions in XRF spectra that contain little or no peak information. An approach is described that both abridges and partially integrates X‐ray fluorescence data sets to obtain a fivefold total decrease in processing time.
ISSN:1600-5775
0909-0495
1600-5775
DOI:10.1107/S1600577521008419