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Reduced-order model to approximate response matrices for filter stack spectrometers
C-S Wong1, S V Luedtke1, D P Broughton1
1Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA.
Abstract:
We present a reduced-order model to calculate response matrices rapidly for filter stack spectrometers (FSSs). The reduced-order model allows response matrices to be built modularly from a set of pre-computed photon and electron transport and scattering calculations through various filter and detector materials. While these modular response matrices are not appropriate for high-fidelity analysis of experimental data, they encode sufficient physics to be used as a forward model in design optimization studies of FSSs, particularly for machine learning approaches that require sampling and testing a large number of FSS designs.
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