16 citations · 27 across the 17 of their papers we have counts for
17 papers
Diffusion Models for Sampling Near Criticality in Lattice Field Theories
Yang-yang Tan, Gert Aarts, Diaa E. Habibi +2
We investigate generative diffusion models as denoising samplers for two- and three-dimensional lattice theory across the symmetric, near-critical, and broken phases. Validat…
Spectral phase transitions and trainability in neural network learning dynamics
Chanju Park, Dario Bocchi, Francesco D'Amico +2
The emergence of low-dimensional structures in the spectra of neural network weight matrices is a common empirical feature of trained models, but the dynamical origin of this pheno…
Finite-temperature Yang-Mills theories with the density of states method: towards the continuum limit
Ed Bennett, Biagio Lucini, David Mason +4
A first-order, confinement/deconfinement phase transition appears in the finite temperature behavior of many non-Abelian gauge theories. These theories play an important role in pr…
Phase diagram and eigenvalue dynamics of stochastic gradient descent in multilayer neural networks
Chanju Park, Biagio Lucini, Gert Aarts
Hyperparameter tuning is one of the essential steps to guarantee the convergence of machine learning models. We argue that intuition about the optimal choice of hyperparameters for…
Chimera baryons and mesons on the lattice: a spectral density analysis
Ed Bennett, Luigi Del Debbio, Niccolò Forzano +10
We develop and test a spectral-density analysis method, based on the introduction of smeared energy kernels, to extract physical information from two-point correlation functions co…
Exploring Generative Networks for Manifolds with Non-Trivial Topology
Shiyang Chen, Gert Aarts, Biagio Lucini
The expressive power of neural networks in modelling non-trivial distributions can in principle be exploited to bypass topological freezing and critical slowing down in simulations…
Topological Data Analysis of Abelian Magnetic Monopoles in Gauge Theories
Xavier Crean, Jeffrey Giansiracusa, Biagio Lucini
Motivated by recent literature on the possible existence of a second higher-temperature phase transition in Quantum Chromodynamics, we revisit the proposal that colour confinement…
Random Matrix Theory for Stochastic Gradient Descent
Chanju Park, Matteo Favoni, Biagio Lucini +1
Investigating the dynamics of learning in machine learning algorithms is of paramount importance for understanding how and why an approach may be successful. The tools of physics a…
Dyson Brownian motion and random matrix dynamics of weight matrices during learning
Gert Aarts, Ouraman Hajizadeh, Biagio Lucini +1
During training, weight matrices in machine learning architectures are updated using stochastic gradient descent or variations thereof. In this contribution we employ concepts of r…
Updates on the density of states method in finite temperature symplectic gauge theories
David Mason, Ed Bennett, Biagio Lucini +4
First-order phase transitions in the early universe have rich phenomenological implications, such as the production of a potentially detectable signal of stochastic relic backgroun…
Stochastic weight matrix dynamics during learning and Dyson Brownian motion
Gert Aarts, Biagio Lucini, Chanju Park
We demonstrate that the update of weight matrices in learning algorithms can be described in the framework of Dyson Brownian motion, thereby inheriting many features of random matr…
Topological Data Analysis of Monopole Current Networks in Lattice Gauge Theory
Xavier Crean, Jeffrey Giansiracusa, Biagio Lucini
In -dimensional pure compact lattice gauge theory, we analyse topological aspects of the dynamics of monopoles across the deconfinement phase transition. We do this using…
Scalar field Restricted Boltzmann Machine as an ultraviolet regulator
Gert Aarts, Biagio Lucini, Chanju Park
Restricted Boltzmann Machines (RBMs) are well-known tools used in Machine Learning to learn probability distribution functions from data. We analyse RBMs with scalar fields on the…
Interface tension of the 3d 4-state Potts model using the Wang-Landau algorithm
A. Hietanen, B. Lucini
We study the interface tension of the 4-state Potts model in three dimensions using the Wang- Landau algorithm. The interface tension is given by the ratio of the partition functio…
A numerical method for determining the interface free energy
A. Hietanen, B. Lucini
We propose a general method (based on the Wang-Landau algorithm) to compute numerically free energies that are obtained from the logarithm of the ratio of suitable partition functi…
Is Confinement a Phase of Broken Dual Gauge Symmetry?
J. Greensite, B. Lucini
We study whether broken dual gauge symmetry, as detected by a monopole order parameter introduced by the Pisa group, is necessarily associated with the confinement phase of a latti…
Searching for diquarks in hadrons
C. Alexandrou, Ph de Forcrand, B. Lucini
Since the early days of QCD, it has been argued that inside hadrons quarks organise into substructures. Among those, popular pictures of various phenomena (including exotica and co…