Learning Trivializing Flows in a $\phi^4$ theory from coarser lattices

Understand

The so-called trivializing flows were proposed to speed up Hybrid Monte Carlo simulations, where the Wilson flow was used as an approximation of a trivializing map, a transformation of the gauge fields which trivializes the theory.

• It was shown that the scaling of the computational costs towards the continuum did not change with respect to HMC.
• The introduction of machine learning tecniques, especially normalizing flows, for the sampling of lattice gauge theories has shed some hope on solving topology freezing in lattice QCD simulations.
• In this talk I will present our work in a $\phi^{4}$ theory using normalizing flows as trivializing flows (given its similarity with the idea of a trivializing map), training from a trivial distribution as well as from coarser lattices, and study its scaling towards the continuum, comparing it with standard HMC.