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Normalizing flows have recently demonstrated the ability to learn the Boltzmann distribution of the Hubbard model, opening new avenues for generative modeling in condensed matter physics. In this work, we investigate the steps required to…

Strongly Correlated Electrons · Physics 2026-01-27 Janik Kreit , Andrea Bulgarelli , Lena Funcke , Thomas Luu , Dominic Schuh , Simran Singh , Lorenzo Verzichelli

Riemannian diffusion models draw inspiration from standard Euclidean space diffusion models to learn distributions on general manifolds. Unfortunately, the additional geometric complexity renders the diffusion transition term inexpressible…

Machine Learning · Computer Science 2023-11-01 Aaron Lou , Minkai Xu , Stefano Ermon

We construct lattice gauge theories in which the elements of the link matrices are represented by non-commuting operators acting in a Hilbert space. These quantum link models are related to ordinary lattice gauge theories in the same way as…

High Energy Physics - Lattice · Physics 2015-06-25 S. Chandrasekharan , U. -J. Wiese

Gauge theories form the foundation of modern physics, with applications ranging from elementary particle physics and early-universe cosmology to condensed matter systems. We perform quantum simulations of the unitary dynamics of a U(1)…

Point processes model the distribution of random point sets in mathematical spaces, such as spatial and temporal domains, with applications in fields like seismology, neuroscience, and economics. Existing statistical and machine learning…

Machine Learning · Computer Science 2024-10-31 David Lüdke , Enric Rabasseda Raventós , Marcel Kollovieh , Stephan Günnemann

Score-based diffusion models have demonstrated outstanding empirical performance in machine learning and artificial intelligence, particularly in generating high-quality new samples from complex probability distributions. Improving the…

Machine Learning · Statistics 2025-05-30 Yuchen Jiao , Gen Li

In this paper we study a 3D lattice spin model of CP$^1$ Schwinger-bosons coupled with dynamical compact U(1) gauge bosons. The model contains two parameters; the gauge coupling and the hopping parameter of CP$^1$ bosons. At large (weak)…

Strongly Correlated Electrons · Physics 2009-11-11 Shunsuke Takashima , Ikuo Ichinose , Tetsuo Matsui

We show that the partition function of many classical models with continuous degrees of freedom, e.g. abelian lattice gauge theories and statistical mechanical models, can be written as the partition function of an (enlarged)…

Gauge theories are fundamental to our understanding of interactions between the elementary constituents of matter as mediated by gauge bosons. However, computing the real-time dynamics in gauge theories is a notorious challenge for…

Quantum Physics · Physics 2016-06-28 E. A. Martinez , C. A. Muschik , P. Schindler , D. Nigg , A. Erhard , M. Heyl , P. Hauke , M. Dalmonte , T. Monz , P. Zoller , R. Blatt

We propose an explicit formulation of the physical subspace for a (1+1)-dimensional SU(2) lattice gauge theory, where the gauge degrees of freedom are integrated out. Our formulation is completely general, and might be potentially suited…

High Energy Physics - Lattice · Physics 2018-01-25 Mari Carmen Bañuls , Krzysztof Cichy , J. Ignacio Cirac , Karl Jansen , Stefan Kühn

We propose a minimal model to study the real-time dynamics of a $\mathbb{Z}_2$ lattice gauge theory coupled to fermionic matter in a cold atom quantum simulator setup. We show that dynamical correlators of the gauge fields can be measured…

Quantum Gases · Physics 2018-08-29 Adam Smith , Dmitry L. Kovrizhin , Roderich Moessner , Johannes Knolle

We survey continuous-time generative modeling methods based on transporting a simple reference distribution to a data distribution via stochastic or deterministic dynamics. We present a unified framework in which diffusion models,…

Machine Learning · Computer Science 2026-05-11 Aditya Ranganath , Mukesh Singhal

Quantum computers have the potential to explore the vast Hilbert space of entangled states that play an important role in the behavior of strongly interacting matter. This opportunity motivates reconsidering the Hamiltonian formulation of…

High Energy Physics - Lattice · Physics 2021-01-08 David B. Kaplan , Jesse R. Stryker

We present an algorithm for Monte Carlo simulations which is able to overcome the suppression of transitions between the phases in compact U(1) lattice gauge theory in 4 dimensions.

High Energy Physics - Lattice · Physics 2009-10-28 W. Kerler , C. Rebbi , A. Weber

Applications of normalizing flows to the sampling of field configurations in lattice gauge theory have so far been explored almost exclusively in two space-time dimensions. We report new algorithmic developments of gauge-equivariant flow…

We study U(1) gauge theory on a 4d non-commutative torus, where two directions are non-commutative. Monte Carlo simulations are performed after mapping the regularized theory onto a U(N) lattice gauge theory in d=2. At intermediate coupling…

High Energy Physics - Theory · Physics 2009-11-13 J. Nishimura , W. Bietenholz , Y. Susaki , J. Volkholz

We investigate the advantages of machine learning techniques to recognize the dynamics of topological objects in quantum field theories. We consider the compact U(1) gauge theory in three spacetime dimensions as the simplest example of a…

High Energy Physics - Lattice · Physics 2020-10-27 M. N. Chernodub , Harold Erbin , V. A. Goy , A. V. Molochkov

We have studied the scalar $\phi^4$-model in the symmetric phase and the non--compact $U(1)$ gauge theory on a momentum lattice using the Langevin equation for generating configurations. In the $\phi^4$-model we have analyzed the…

High Energy Physics - Lattice · Physics 2015-06-25 H. Kröger , S. Lantagne , K. J. M. Moriarty

A model has two main aims: predicting the behavior of a physical system and understanding its nature, that is how it works, at some desired level of abstraction. A promising recent approach to model building consists in deriving a…

Statistical Mechanics · Physics 2019-02-26 Marco Baldovin , Andrea Puglisi , Angelo Vulpiani

We consider the problem of sampling lattice field configurations on a lattice from the Boltzmann distribution corresponding to some action. Since such densities arise as approximationw of an underlying functional density, we frame the task…

Machine Learning · Computer Science 2024-11-27 Bálint Máté , François Fleuret