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We describe a Fourier Accelerated Hybrid Monte Carlo algorithm suitable for dynamical fermion simulations of non-gauge models. We test the algorithm in supersymmetric quantum mechanics viewed as a one-dimensional Euclidean lattice field…

High Energy Physics - Lattice · Physics 2011-07-28 S. Catterall , S. Karamov

Metastability is a formidable challenge to Markov chain Monte Carlo methods. In this paper we present methods for algorithm design to meet this challenge. The design problem we consider is temperature selection for the infinite swapping…

Probability · Mathematics 2020-11-12 Paul Dupuis , Guo-Jhen Wu

We present a novel implementation of the parallel tempering Monte Carlo method in a multicanonical ensemble. Multicanonical weights are derived by a self-consistent iterative process using a Boltzmann inversion of global energy histograms.…

Soft Condensed Matter · Physics 2009-11-07 Roland Faller , Qiliang Yan , Juan J. de Pablo

We introduce a new Monte Carlo method for pure gauge theories. It is not intended for use with dynamical fermions. It belongs to the class of Local Hybrid Monte Carlo (LHMC) algorithms, which make use of the locality of the action by…

High Energy Physics - Lattice · Physics 2009-10-22 A. D. Kennedy , K. M. Bitar

We present the results of a large-scale numerical study of the equilibrium three-dimensional Edwards-Anderson Ising spin glass with Gaussian disorder. Using parallel tempering (replica exchange) Monte Carlo we measure various static, as…

Disordered Systems and Neural Networks · Physics 2013-01-07 Burcu Yucesoy , Jonathan Machta , Helmut G. Katzgraber

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 present results from our study of the Parallel Tempering algorithm. We examine the swapping acceptance rate of a twin subensemble PT system. We use action matching technology in an attempt to maximise the swap acceptance rate. We model…

High Energy Physics - Lattice · Physics 2009-10-31 Balint Joo , UKQCD Collaboration

The simulation of lattice gauge theories on quantum computers necessitates digitizing gauge fields. One approach involves substituting the continuous gauge group with a discrete subgroup, but the implications of this approximation still…

High Energy Physics - Lattice · Physics 2024-05-29 Benoît Assi , Henry Lamm

Understanding the non-equilibrium dynamics of gauge theories remains a fundamental challenge in high-energy physics. Indeed, most large scale experiments on gauge theories intrinsically rely on very far-from equilibrium dynamics, from…

We present computer simulations of a dynamic Monte Carlo algorithm for polymer chains on the FCC lattice which takes explicitly into account the possibility to overcome topological constraints by controlling the rate at which nearby polymer…

Soft Condensed Matter · Physics 2021-12-01 Mattia Alberto Ubertini , Angelo Rosa

We investigate simulations for gauge theories on a Minkowskian space-time lattice. We employ stochastic quantization with optimized updating using stochastic reweighting or gauge fixing, respectively. These procedures do not affect the…

High Energy Physics - Lattice · Physics 2008-11-26 J. Berges , D. Sexty

Despite the enormous success of Hamiltonian Monte Carlo and related Markov Chain Monte Carlo (MCMC) methods, sampling often still represents the computational bottleneck in scientific applications. Availability of parallel resources can…

Computation · Statistics 2026-01-26 Jakob Robnik , Uroš Seljak

The simulation of real-time dynamics in lattice gauge theories is particularly hard for classical computing due to the exponential scaling of the required resources. On the other hand, quantum algorithms can potentially perform the same…

Quantum Physics · Physics 2020-11-11 Simon V. Mathis , Guglielmo Mazzola , Ivano Tavernelli

Markov Chain Monte Carlo (MCMC) underlies both statistical physics and combinatorial optimization, but mixes slowly near critical points and in rough landscapes. Parallel Tempering (PT) improves mixing by swapping replicas across…

Machine Learning · Computer Science 2025-09-30 Saleh Bunaiyan , Corentin Delacour , Shuvro Chowdhury , Kyle Lee , Kerem Y. Camsari

In this review I summarize how machine learning can be used in lattice gauge theory simulations and what ap\-proaches are currently available to improve the sampling of gauge field configurations, with a focus on applications in…

High Energy Physics - Lattice · Physics 2026-04-15 Urs Wenger

In the field of sampling algorithms, MCMC (Markov Chain Monte Carlo) methods are widely used when direct sampling is not possible. However, multimodality of target distributions often leads to slow convergence and mixing. One common…

Machine Learning · Computer Science 2023-04-05 Holden Lee , Zeyu Shen

We investigate the critical slowing down of the topological modes using local updating algorithms in lattice 2-d CP^(N-1) models. We show that the topological modes experience a critical slowing down that is much more severe than the one of…

High Energy Physics - Lattice · Physics 2009-11-10 Luigi Del Debbio , Gian Mario Manca , Ettore Vicari

We consider the possibility of gauge coupling unification within the simplest realizations of the $\mathrm{SU(3)_c \times SU(3)_L \times SU(3)_R \times U(1)_{X}}$ gauge theory. We present a first exploration of the renormalization group…

High Energy Physics - Phenomenology · Physics 2017-07-12 Chandan Hati , Sudhanwa Patra , Mario Reig , José W. F. Valle , C. A. Vaquera-Araujo

Monte Carlo (MC) simulations of lattice models are a widely used way to compute thermodynamic properties of substitutional alloys. A limitation to their more widespread use is the difficulty of driving a MC simulation in order to obtain the…

Statistical Mechanics · Physics 2009-11-07 A. van de Walle , M. Asta

Metadynamics, a member of the `flat histogram' class of advanced sampling algorithms, has been widely used in molecular simulations to drive the exploration of states separated by high free energy barriers and promote comprehensive sampling…

Computational Physics · Physics 2021-09-13 Shanghui Huang , Michael J. Quevillon , Ernesto C. Cortés-Morales , Jonathan K. Whitmer
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