NeSST is a new open-source Python tool that computes primary and scattered neutron spectra plus synthetic nToF signals for ICF experiments by integrating ENDF cross sections, relativistic corrections, and asymmetry modeling.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2representative citing papers
SINAPSE uses a dual-branch neural network with a 1D convolutional autoencoder for denoising and a classifier for neutron-gamma discrimination, trained via random augmentations on high-SNR data and validated with SHAP explanations.
citing papers explorer
-
NeSST: A Python Tool for Neutron Spectra and Synthetic Diagnostics in Inertial Confinement Fusion
NeSST is a new open-source Python tool that computes primary and scattered neutron spectra plus synthetic nToF signals for ICF experiments by integrating ENDF cross sections, relativistic corrections, and asymmetry modeling.
-
SINAPSE: A lightweight deep learning framework for accurate and explainable neutron-$\gamma$ discrimination
SINAPSE uses a dual-branch neural network with a 1D convolutional autoencoder for denoising and a classifier for neutron-gamma discrimination, trained via random augmentations on high-SNR data and validated with SHAP explanations.