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相关论文: An Exact Local Hybrid Monte Carlo Algorithm for Ga…

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The past few years have seen considerable progress in algorithmic development for the generation of gauge fields including the effects of dynamical fermions. The Rational Hybrid Monte Carlo (RHMC) algorithm, where Hybrid Monte Carlo is…

高能物理 - 格点 · 物理学 2008-11-26 M. A. Clark

We investigate the performance of the hybrid Monte Carlo algorithm, the standard algorithm used for lattice QCD simulations involving fermions, in updating non-trivial global topological structures. We find that the hybrid Monte Carlo…

高能物理 - 格点 · 物理学 2016-08-15 B. Allés , G. Boyd , M. D'Elia , A. Di Giacomo , E. Vicari

We report on a study of the autocorrelation times of the local version of the Hybrid Monte Carlo (LHMC) algorithm for pure gauge $SU(3)$. We compare LHMC to standard multi-hit Metropolis and to the global version of the same HMC. For every…

高能物理 - 格点 · 物理学 2009-10-22 P. Marenzoni , L. Pugnetti , P. Rossi

We develop an extended framework for the hybrid Monte Carlo (HMC) algorithm in lattice gauge theory by embedding the $SU(N)$ group into the space of general complex matrices,$M_N(\mathbb{C})$. Auxiliary directions will be completely…

高能物理 - 格点 · 物理学 2025-08-18 Norman H. Christ , Lu-Chang Jin , Christoph Lehner , Erik Lundstrum , Nobuyuki Matsumoto

Reverse Monte Carlo (RMC) is an algorithm that incorporates stochastic modification of the action as part of the process that updates the fields in a Monte Carlo simulation. Such update moves have the potential of lowering or eliminating…

高能物理 - 格点 · 物理学 2015-06-22 Arjun Singh Gambhir , Kostas Orginos

We generalize the Hamiltonian Monte Carlo algorithm with a stack of neural network layers and evaluate its ability to sample from different topologies in a two dimensional lattice gauge theory. We demonstrate that our model is able to…

高能物理 - 格点 · 物理学 2021-05-10 Sam Foreman , Xiao-Yong Jin , James C. Osborn

This review gives an overview on the research of algorithms for dynamical fermions used in large scale lattice QCD simulations. First a short overview on the state-of-the-art of ensemble generation at the physical point is given. Followed…

高能物理 - 格点 · 物理学 2024-02-20 Jacob Finkenrath

The numerical sign problem remains one of the central challenges in computational physics. The Worldvolume Hybrid Monte Carlo (WV-HMC) method has recently been proposed as a reliable and computationally efficient algorithm that crucially…

高能物理 - 格点 · 物理学 2026-03-31 Masafumi Fukuma

Large N gauge theories with adjoint matter can be numerically studied using lattice techniques. Eguchi-Kawai reductions holds for this theory and one can reduce the lattice model to a single site. Hybrid Monte Carlo algorithm can be used to…

高能物理 - 格点 · 物理学 2015-03-19 R. Narayanan

An overview is given over the recently developed and now widely used Monte Carlo algorithms with reduced or eliminated critical slowing down. The basic techniques are overrelaxation, cluster algorithms and multigrid methods. With these…

高能物理 - 格点 · 物理学 2011-04-15 Ulli Wolff

We propose a new algorithm which works effectively in global updates in Monte Carlo study. We apply it to the quantum spin chain with next-nearest-neighbor interactions. We observe that Monte Carlo results are in excellent agreement with…

凝聚态物理 · 物理学 2017-02-01 Tomo Munehisa , Yasuko Munehisa

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…

高能物理 - 格点 · 物理学 2011-07-28 S. Catterall , S. Karamov

The Hybrid Monte Carlo algorithm is adapted to the simulation of a system of classical degrees of freedom coupled to non self-interacting lattices fermions. The diagonalization of the Hamiltonian matrix is avoided by introducing a…

强关联电子 · 物理学 2009-10-31 J. L. Alonso , L. A. Fernandez , F. Guinea , V. Laliena , V. Martin-Mayor

Hamiltonian Monte Carlo (HMC) is a popular Markov chain Monte Carlo (MCMC) algorithm that generates proposals for a Metropolis-Hastings algorithm by simulating the dynamics of a Hamiltonian system. However, HMC is sensitive to large time…

机器学习 · 统计学 2016-09-15 Xiaoyu Lu , Valerio Perrone , Leonard Hasenclever , Yee Whye Teh , Sebastian J. Vollmer

Monte Carlo techniques with importance sampling have been extensively applied to lattice gauge theory in the Lagrangian formulation. Unfortunately, it is extremely difficult to compute the excited states using the conventional Monte Carlo…

高能物理 - 格点 · 物理学 2017-08-23 Xiang-Qian Luo , H. Jirari , H. Kroger , K. Moriarty

We present a trainable framework for efficiently generating gauge configurations, and discuss ongoing work in this direction. In particular, we consider the problem of sampling configurations from a 4D $SU(3)$ lattice gauge theory, and…

高能物理 - 格点 · 物理学 2023-12-19 Sam Foreman , Xiao-Yong Jin , James C. Osborn

We introduce a new algorithm which we call the {Rational Hybrid Monte Carlo} Algorithm (RHMC). This method uses a rational approximation to the fermionic kernel together with a noisy Kennedy-Kuti acceptance step to give an efficient…

高能物理 - 格点 · 物理学 2009-10-31 Ivan Horvath , A. D. Kennedy , Stefan Sint

We describe a new Hybrid Monte Carlo (HMC) algorithm for dynamical overlap fermions, which improves the rate of topological index changes by adding an additional (intensive) term to the action for the molecular dynamics part of the…

高能物理 - 格点 · 物理学 2012-02-28 Nigel Cundy , Weonjong Lee

In this article we present our implementation of a Hybrid Monte Carlo algorithm for Lattice Gauge Theory using two degenerate flavours of Wilson-Dirac fermions on a Fermi GPU. We find that using registers instead of global memory speeds up…

高能物理 - 格点 · 物理学 2012-07-11 Abhijit Chakrabarty , Pushan Majumdar

We consider recent progress in algorithms for generating gauge field configurations that include the dynamical effects of light fermions. We survey what has been achieved in recent state-of-the-art computations, and examine the trade-offs…

高能物理 - 格点 · 物理学 2009-11-10 A. D. Kennedy
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