Continuous normalizing flows for lattice gauge theories
This work addresses sampling challenges in lattice field theories for physicists, but it is incremental as it builds on previous methods.
The authors tackled the problem of sampling in lattice gauge theories by developing a continuous normalizing flow architecture for matrix Lie groups that is equivariant under group transformations, demonstrating competitive performance in two-dimensional lattice gauge theories as a proof-of-principle.
Continuous normalizing flows are known to be highly expressive and flexible, which allows for easier incorporation of large symmetries and makes them a powerful tool for sampling in lattice field theories. Building on previous work, we present a general continuous normalizing flow architecture for matrix Lie groups that is equivariant under group transformations. We apply this to lattice gauge theories in two dimensions as a proof-of-principle and demonstrate competitive performance, showing its potential as a tool for future lattice sampling tasks.