Normalizing flows have recently demonstrated the ability to learn the Boltzmann distribution of the Hubbard model, opening new avenues for generative modeling in condensed matter physics. In this work, we investigate the steps required to extend such simulations to larger lattice sizes and lower temperatures, with a focus on enhancing stability and efficiency. Additionally, we present the scaling behavior of stochastic normalizing flows and non-equilibrium Markov chain Monte Carlo methods for this fermionic system.
@article{arxiv.2601.18273,
title = {Toward Scalable Normalizing Flows for the Hubbard Model},
author = {Janik Kreit and Andrea Bulgarelli and Lena Funcke and Thomas Luu and Dominic Schuh and Simran Singh and Lorenzo Verzichelli},
journal= {arXiv preprint arXiv:2601.18273},
year = {2026}
}
Comments
10 pages, 5 figues, The 42nd International Symposium on Lattice Field Theory