no code implementations • 29 Nov 2024 • Andrea Bulgarelli, Elia Cellini, Alessandro Nada
Non-equilibrium Markov Chain Monte Carlo (NE-MCMC) simulations provide a well-understood framework based on Jarzynski's equality to sample from a target probability distribution.
no code implementations • 18 Oct 2024 • Andrea Bulgarelli, Elia Cellini, Karl Jansen, Stefan Kühn, Alessandro Nada, Shinichi Nakajima, Kim A. Nicoli, Marco Panero
We introduce a novel technique to numerically calculate R\'enyi entanglement entropies in lattice quantum field theory using generative models.
no code implementations • 24 Sep 2024 • Michele Caselle, Elia Cellini, Alessandro Nada
Flow-based architectures have recently proved to be an efficient tool for numerical simulations of Effective String Theories regularized on the lattice that otherwise cannot be efficiently sampled by standard Monte Carlo methods.
1 code implementation • 3 Jul 2023 • Michele Caselle, Elia Cellini, Alessandro Nada
Effective String Theory (EST) represents a powerful non-perturbative approach to describe confinement in Yang-Mills theory that models the confining flux tube as a thin vibrating string.
no code implementations • 21 Jan 2022 • Michele Caselle, Elia Cellini, Alessandro Nada, Marco Panero
Normalizing flows are a class of deep generative models that provide a promising route to sample lattice field theories more efficiently than conventional Monte Carlo simulations.
