Robust unfolding of MeV x-ray spectra from filter stack spectrometer data.

Area of Science:

• Nuclear Physics
• Plasma Physics
• Spectroscopy

Background:

• Filter stack spectrometers (FSS) are used to measure MeV x-ray spectra.
• Previous inversion methods often require a priori spectral shape assumptions or arbitrary algorithm termination.
• The perturbative minimization (PM) algorithm has limitations with non-monotonic attenuation coefficients.

Purpose of the Study:

• To present a novel inversion method for robustly unfolding MeV x-ray spectra from FSS data.
• To improve upon existing PM algorithms by removing the need for spectral shape specification or arbitrary termination.
• To enable accurate spectral recovery without requiring a physics model for initial guesses or fitting.

Main Methods:

• The developed method is based on the perturbative minimization (PM) algorithm.
• Improvements include regular smoothing of the candidate spectrum and addition of stochasticity to the search.
• The only assumption is that the x-ray spectrum is near a smooth curve.

Main Results:

• The inversion method successfully recovers primary large-scale features of MeV x-ray spectra.
• Accuracy for broad energy bins (several MeV) is within 10% for synthetic data.
• Fine-scale spectral features are more challenging to recover accurately.

Conclusions:

• The new inversion method provides a robust approach for unfolding MeV x-ray spectra from FSS data.
• It overcomes limitations of previous methods by not requiring a priori spectral information or arbitrary termination.
• The method demonstrates successful application to experimental data from high-power laser facilities.