Preprint Open access
PTNO: Training Neural Operators with Noisy Monte Carlo Estimates for Particle Transport Problems
Particle transport under multiple scattering is central to radiative transfer and plasma physics, yet high-fidelity Monte Carlo (MC) simulations must trace prohibitively many particles. Learning-based surrogates can amortize this cost, but typically train on expensive, well-converged MC solutions. We propose the Partic …