Neural networks trained on 3D energy deposition maps recover signal fraction and photon multiplicity from simulated ultrafast pileup, outperforming depth-ratio baselines.
Development of the MeV Thomson-scattered gamma ray source using laser plasma accelerators at the BELLA Center,
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Machine learning methods for spectroscopic information recovery under ultrafast photon pileup
Neural networks trained on 3D energy deposition maps recover signal fraction and photon multiplicity from simulated ultrafast pileup, outperforming depth-ratio baselines.