3 papers
physics.ins-det2026
Transferability of data-driven optimization results across multiple pixelated CdZnTe spectrometers
Thomas D. MacDonald, Hannah S. Parrilla, Jayson R. Vavrek
Recent work by Vavrek et al. (2025) showed that machine learning methods can be used to exploit spatial patterns of performance variations within the highly-segmented H3D M400 gamm…
physics.ins-det2025
Data-driven optimization of pixelated CdZnTe spectrometers for uranium enrichment assay
Jayson R. Vavrek, Thomas D. MacDonald, Hannah S. Parrilla +3
In recent work [Vavrek et al. (2025)], we developed the performance optimization framework spectre-ml for gamma spectrometers with variable performance across many readout channels…
physics.ins-det2025
Data-driven performance optimization of gamma spectrometers with many channels
Jayson R. Vavrek, Hannah S. Parrilla, Gabriel Aversano +3
In gamma spectrometers with variable spectroscopic performance across many channels (e.g., many pixels or voxels), a tradeoff exists between including data from successively worse-…