Sébastien Racanière

Sampling QCD field configurations with gauge-equivariant flow models

2022 · arXiv (Cornell University)

Machine learning methods based on normalizing flows have been shown to address important challenges, such as critical slowing-down and topological freezing, in the sampling of gauge field configurations in simple lattice field theories. A critical …

Applications of flow models to the generation of correlated lattice QCD ensembles

2024 · arXiv (Cornell University)

Machine-learned normalizing flows can be used in the context of lattice quantum field theory to generate statistically correlated ensembles of lattice gauge fields at different action parameters. This work demonstrates how these correlations can be …