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Hamiltonian Flow Monte Carlo(HFMC) methods have been implemented in engineering, biology and chemistry. HFMC makes large gradient based steps to rapidly explore the state space. The application of the Hamiltonian dynamics allows to estimate…

Computation · Statistics 2017-09-06 Raphael Douady , Shohruh Miryusupov

Detector response to a high-energy physics process is often estimated by Monte Carlo simulation. For purposes of data analysis, the results of this simulation are typically stored in large multi-dimensional histograms, which can quickly…

Data Analysis, Statistics and Probability · Physics 2013-06-14 Nathan Whitehorn , Jakob van Santen , Sven Lafebre

There has been much recent progress in the understanding and reduction of the computational cost of the Hybrid Monte Carlo algorithm for Lattice QCD as the quark mass parameter is reduced. In this letter we present a new solution to this…

High Energy Physics - Lattice · Physics 2008-11-26 M. A. Clark , A. D. Kennedy

We enable the automatic construction of Hybrid Monte Carlo (HMC) forces in lattice gauge theory by performing reverse-mode automatic differentiation at the level of optimized LLVM intermediate representation, making the approach applicable…

High Energy Physics - Lattice · Physics 2026-02-25 Yuki Nagai , Akio Tomiya , Hiroshi Ohno

We propose a splitting Hamiltonian Monte Carlo (SHMC) algorithm, which can be computationally efficient when combined with the random mini-batch strategy. By splitting the potential energy into numerically nonstiff and stiff parts, one…

Numerical Analysis · Mathematics 2022-06-23 Lei Li , Lin Liu , Yuzhou Peng

Hamiltonian Monte Carlo (HMC) and related algorithms have become routinely used in Bayesian computation. In this article, we present a simple and provably accurate method to improve the efficiency of HMC and related algorithms with…

Computation · Statistics 2020-03-10 Akihiko Nishimura , David Dunson

Brute-force simulations for dynamics on very large networks are quite expensive. While phenomenological treatments may capture some macroscopic properties, they often ignore important microscopic details. Fortunately, one may be only…

Physics and Society · Physics 2016-05-17 Chuansheng Shen , Hanshuang Chen , Zhonghuai Hou , Jürgen Kurths

We propose a method for Monte Carlo simulations of systems with a complex action. The method has the advantages of being in principle applicable to any such system and provides a solution to the overlap problem. We apply it in random matrix…

High Energy Physics - Lattice · Physics 2017-08-23 Jan Ambjorn , Konstantinos N. Anagnostopoulos , Jun Nishimura , Jacobus J. M. Verbaarschot

We develop a classical Monte Carlo algorithm based on a quasi-classical approximation for a pseudospin S=1 Hamiltonian in real space to construct a phase diagram of a model cuprate with a high Tc. A model description takes into account both…

Strongly Correlated Electrons · Physics 2021-10-25 Yu. D. Panov , A. S. Moskvin , A. A. Chikov , V. A. Ulitko

We present the preliminary tests on two modifications of the Hybrid Monte Carlo (HMC) algorithm. Both algorithms are designed to travel much farther in the Hamiltonian phase space for each trajectory and reduce the autocorrelations among…

High Energy Physics - Lattice · Physics 2018-04-18 Guido Cossu , Peter Boyle , Norman Christ , Chulwoo Jung , Andreas Jüttner , Francesco Sanfilippo

The use of APE smearing or other blocking techniques in lattice fermion actions can provide many advantages. There are many variants of these fat link actions in lattice QCD currently, such as FLIC fermions. The FLIC fermion formalism makes…

High Energy Physics - Lattice · Physics 2010-03-04 Waseem Kamleh , Derek B. Leinweber , Anthony G. Williams

By precisely writing down the matrix element of the local Boltzmann operator, we have proposed a new path integral formulation for quantum field theory and developed a corresponding Monte Carlo algorithm. With current formula, the…

Strongly Correlated Electrons · Physics 2022-03-08 J. Wang , W. Pan , D. Y. Sun

We propose an algorithm for accurate, systematic and scalable computation of interatomic forces within the auxiliary-field Quantum Monte Carlo (AFQMC) method. The algorithm relies on the Hellman-Fenyman theorem, and incorporates Pulay…

Computational Physics · Physics 2018-05-30 Mario Motta , Shiwei Zhang

We consider a hybrid Monte Carlo algorithm which is applicable to lattice theories defined on Lefschetz thimbles. In the algorithm, any point (field configuration) on a thimble is parametrized uniquely by the flow-direction and the…

High Energy Physics - Lattice · Physics 2015-06-17 H. Fujii , D. Honda , M. Kato , Y. Kikukawa , S. Komatsu , T. Sano

We present an exact Monte Carlo algorithm designed to sample theories where the energy is a sum of many couplings of decreasing strength. The algorithm avoids the computation of almost all non-leading terms. Its use is illustrated by…

High Energy Physics - Lattice · Physics 2009-10-31 T. Bakeyev , Ph. de Forcrand

Hamiltonian Monte Carlo (HMC) has emerged as a powerful Markov Chain Monte Carlo (MCMC) method to sample from complex continuous distributions. However, a fundamental limitation of HMC is that it can not be applied to distributions with…

Computation · Statistics 2021-12-10 Guangyao Zhou

This paper surveys in detail the relations between numerical integration and the Hamiltonian (or hybrid) Monte Carlo method (HMC). Since the computational cost of HMC mainly lies in the numerical integrations, these should be performed as…

Probability · Mathematics 2020-07-21 Nawaf Bou-Rabee , Jesús María Sanz-Serna

It is well established that lattice artifacts can be suppressed substantially by the use of SU(3)-projected smeared links in the fermion action. An example is the Highly Improved Staggered Quark action where the ASQ-like effective links are…

High Energy Physics - Lattice · Physics 2008-11-26 K. Y. Wong , R. M. Woloshyn

The Worldvolume Hybrid Monte Carlo (WV-HMC) method [arXiv:2012.08468] is an efficient algorithm for addressing the numerical sign problem at moderate computational cost. It mitigates the sign problem while avoiding the ergodicity issues…

Strongly Correlated Electrons · Physics 2026-05-15 Masafumi Fukuma , Yusuke Namekawa

We present an efficient algorithm for the inference of stochastic block models in large networks. The algorithm can be used as an optimized Markov chain Monte Carlo (MCMC) method, with a fast mixing time and a much reduced susceptibility to…

Data Analysis, Statistics and Probability · Physics 2014-01-14 Tiago P. Peixoto
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