September 27, 2021 to October 1, 2021
ECT* - Trento
Europe/Rome timezone

Training Topological Samplers for Lattice Gauge Theories

Sep 30, 2021, 3:50 PM
Aula Renzo Leonardi (ECT* - Trento)

Aula Renzo Leonardi

ECT* - Trento

Strada delle Tabarelle, 286 38123 - Villazzano (TN) Italy


Sam Foreman (Argonne National Laboratory)


The ability to efficiently draw independent configurations from a general density function is a major computational challenge that has been studied extensively across a variety of scientific disciplines. In particular, for High Energy Physics, the effort required to generate independent gauge field configurations is known to scale exponentially as we approach physical lattice volumes.

We discuss ongoing developments towards developing a generalized version of the Hamiltonian Monte Carlo (HMC) algorithm that efficiently leverages invertible neural network architectures to help combat this effect, and demonstrate its success on a two-dimensional U(1) lattice gauge theory.

Our implementation is publicly available at

Presentation materials