Speaker
Janik Kreit
(University of Bonn)
Description
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. We further present the scaling behavior of stochastic normalizing flows for this fermionic system.
| Parallel Session (for talks only) | Algorithms and artificial intelligence |
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Authors
Janik Kreit
(University of Bonn)
Andrea Bulgarelli
(University of Bonn)
Lena Funcke
(University of Bonn)
Thomas Luu
(Forschungszentrum Jülich)
Dominic Schuh
(University of Bonn)
Simran Singh
(University of Bonn)
Lorenzo Verzichelli
(Università di Torino, INFN sezione di Torino)
