45 citations · 86 across the 17 of their papers we have counts for
18 papers
Ergodic topology sampling toward the continuum with Stochastic Normalizing Flows
Claudio Bonanno, Andrea Bulgarelli, Elia Cellini +4
In this work we provide numerical evidence that topological freezing in Yang-Mills theory can be mitigated with a flow-based approach, as tested at lattice spacing…
Scalable Generative Sampling and Multilevel Estimation for Lattice Field Theories Near Criticality
A. Singha, J. Kauffmann, E. Cellini +2
Sampling lattice field theories near criticality is severely hindered by critical slowing down, which makes standard Markov chain methods increasingly inefficient at large lattice…
Intrinsic Width of the flux tube in 2+1 dimensional Yang-Mills theories
Lorenzo Verzichelli, Michele Caselle, Elia Cellini +2
We present our updated results on the intrinsic width of the profile of the flux tube in (2+1)-dimensional Yang-Mills theory with SU(2) gauge group. We identify the intrinsic width…
A scalable flow-based approach to mitigate topological freezing
Claudio Bonanno, Andrea Bulgarelli, Elia Cellini +4
As lattice gauge theories with non-trivial topological features are driven towards the continuum limit, standard Markov Chain Monte Carlo simulations suffer for topological freezin…
Intrinsic Width of the Flux Tube as a tool to explore confining mechanisms in Lattice Gauge Theories
Michele Caselle, Elia Cellini, Alessandro Nada +2
We study the profile of the flux tube in the SU(2) gauge model in 2+1 dimensions, with a particular attention to the so called "intrinsic width" which drives the exponential decay…
Computing quantum entanglement with machine learning
Andrea Bulgarelli, Elia Cellini, Karl Jansen +5
Entanglement calculations in quantum field theories are extremely challenging and typically rely on the replica trick, where the problem is rephrased in a study of defects. We demo…
Scaling flow-based approaches for topology sampling in gauge theory
Claudio Bonanno, Andrea Bulgarelli, Elia Cellini +4
We develop a methodology based on out-of-equilibrium simulations to mitigate topological freezing when approaching the continuum limit of lattice gauge theories. We reduce the auto…
Studying Effective String Theory using deep generative models
Michele Caselle, Elia Cellini, Alessandro Nada
Effective String Theory (EST) offers a robust non-perturbative framework for describing confinement in Yang-Mills theory by treating the confining flux tube between a static quark-…
Multilevel Generative Samplers for Investigating Critical Phenomena
Ankur Singha, Elia Cellini, Kim A. Nicoli +3
Investigating critical phenomena or phase transitions is of high interest in physics and chemistry, for which Monte Carlo (MC) simulations, a crucial tool for numerically analyzing…
Stochastic normalizing flows for Effective String Theory
Michele Caselle, Elia Cellini, Alessandro Nada
Effective String Theory (EST) is a powerful tool used to study confinement in pure gauge theories by modeling the confining flux tube connecting a static quark-anti-quark pair as a…
Intrinsic width of the flux tube in 2+1 dimensional Yang-Mills therories
Michele Caselle, Elia Cellini, Alessandro Nada +2
We study the shape of the flux tube in lattice Yang-Mills theories and in particular its intrinsic width. In the framework of the Effective String Theory description of the confini…
Scaling of Stochastic Normalizing Flows in lattice gauge theory
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. B…
Sampling SU(3) pure gauge theory with Stochastic Normalizing Flows
Andrea Bulgarelli, Elia Cellini, Alessandro Nada
Non-equilibrium Monte Carlo simulations based on Jarzynski's equality are a well-understood method to compute differences in free energy and also to sample from a target probabilit…
Flow-Based Sampling for Entanglement Entropy and the Machine Learning of Defects
Andrea Bulgarelli, Elia Cellini, Karl Jansen +5
We introduce a novel technique to numerically calculate Rényi entanglement entropies in lattice quantum field theory using generative models. We describe how flow-based approaches…
Numerical determination of the width and shape of the effective string using Stochastic Normalizing Flows
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 eff…
Sampling the lattice Nambu-Goto string using Continuous Normalizing Flows
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 s…
Stochastic normalizing flows for lattice field theory
Michele Caselle, Elia Cellini, Alessandro Nada +1
Stochastic normalizing flows are a class of deep generative models that combine normalizing flows with Monte Carlo updates and can be used in lattice field theory to sample from Bo…
Stochastic normalizing flows as non-equilibrium transformations
Michele Caselle, Elia Cellini, Alessandro Nada +1
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.…