Quantum statistics from classical simulations via generative Gibbs sampling
arXiv preprint, 2026
Generative Gibbs Sampling for Path Integrals (GG-PI). arXiv preprint.
GG-PI learns the single-bead conditional density of the ring polymer from standard classical simulations and samples the imaginary-time path integral by parallel Gibbs updates. Because the conditional depends only on the imaginary-time interval, a model trained once transfers across temperatures without retraining, and sampling requires no force evaluations. On the Zundel ion, bulk water, and para-hydrogen, GG-PI matches path-integral molecular dynamics while significantly reducing wall-clock time.
Talk: Quantum statistics from classical simulations via generative Gibbs sampling, oral presentation, ACS Fall 2026, Chicago, August 2026.