Unverified
2026
Conservative amortized collision layer
Add a learned stochastic pair-interaction layer to a particle graph neural network, with a conditional normalizing flow generating the post-interaction relative state. Parameterize the update in center-of-mass and invariant relative coordinates so every sampled interaction preserves pair momentum and kinetic energy exactly. The flow learns the transition law directly from observed scattering or trajectory data, replacing repeated numerical collision solves or unconstrained message-passing…
Paper: A particle method for the Boltzmann equation via amortized sampling from Green's function of the lifted linear operator
arXiv:2608.22880