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A Monte Carlo method for simulating a multi-dimensional diffusion process conditioned on hitting a fixed point at a fixed future time is developed. Proposals for such diffusion bridges are obtained by superimposing an additional guiding…

Probability · Mathematics 2017-05-30 Moritz Schauer , Frank van der Meulen , Harry van Zanten

We propose a new time quantifiable Monte Carlo (MC) method to simulate the thermally induced magnetization reversal for an isolated single domain particle system. The MC method involves the determination of density of states, and the use of…

Statistical Mechanics · Physics 2009-11-11 X. Z. Cheng , M. B. A. Jalil , H. K. Lee , Y. Okabe

We propose an efficient method for Monte Carlo simulation of quantum lattice models. Unlike most other quantum Monte Carlo methods, a single run of the proposed method yields the free energy and the entropy with high precision for the whole…

Statistical Mechanics · Physics 2009-11-10 Chiaki Yamaguchi , Naoki Kawashima , Yutaka Okabe

We present results from a study of light meson spectra and structure obtained within the framework of light-front QCD formulated on a transverse lattice. We discuss how imposing Lorentz covariance conditions on meson dispersion relations…

High Energy Physics - Phenomenology · Physics 2009-11-07 M. Burkardt , S. K. Seal

We show how lattice Quantum Monte Carlo can be applied to the electronic properties of carbon nanotubes in the presence of strong electron-electron correlations. We employ the path-integral formalism and use methods developed within the…

Strongly Correlated Electrons · Physics 2016-06-10 Thomas Luu , Timo A. Lähde

We establish $L_q$ convergence for Hamiltonian Monte Carlo algorithms. More specifically, under mild conditions for the associated Hamiltonian motion, we show that the outputs of the algorithms converge (strongly for $2\le q<\infty$ and…

Classical Analysis and ODEs · Mathematics 2022-06-07 Soumyadip Ghosh , Yingdong Lu , Tomasz Nowicki

Using the Wang-Landau flat histogram Monte Carlo (FHMC) simulation technique, we were able to study two types of triangulated spherical surface models in which the two-dimensional extrinsic curvature energy is assumed in the Hamiltonian.…

Statistical Mechanics · Physics 2010-09-30 Hiroshi Koibuchi

We demonstrate that substantial progress can be achieved in the study of the phase structure of 4-dimensional compact QED by a joint use of hybrid Monte Carlo and multicanonical algorithms, through an efficient parallel implementation. This…

High Energy Physics - Lattice · Physics 2016-08-25 G. Arnold , Th. Lippert , K. Schilling

We propose a method for the numerical computation of microcanonical expectation values--i.e. averages over energy eigenstates with the same eigenvalue-without any prior knowledge about the spectrum of the Hamiltonian. This is accomplished…

High Energy Physics - Theory · Physics 2007-05-23 Jani Lukkarinen

Hamiltonian Monte Carlo (HMC) is a state-of-the-art Markov chain Monte Carlo sampling algorithm for drawing samples from smooth probability densities over continuous spaces. We study the variant most widely used in practice, Metropolized…

Machine Learning · Statistics 2021-01-12 Yuansi Chen , Raaz Dwivedi , Martin J. Wainwright , Bin Yu

The auxiliary field diffusion Monte Carlo method uses imaginary-time projection techniques to accurately solve the ground-state wave function of atomic nuclei and infinite nuclear matter. In this work, we present a novel representation of…

Nuclear Theory · Physics 2024-07-23 Jordan M. R. Fox , Alessandro Lovato , Alessandro Roggero , Ermal Rrapaj

We adapt the compression algorithm of Weinstein, Auerbach, and Chandra from eigenvectors of spin lattice Hamiltonians to eigenvectors of light-front field-theoretic Hamiltonians. The latter are approximated by the standard discrete…

High Energy Physics - Phenomenology · Physics 2013-12-16 Xiao Pu , Sophia S. Chabysheva , John R. Hiller

We have simulated the three-dimensional Heisenberg model on simple cubic lattices, using the single-cluster Monte Carlo update algorithm. The expected pronounced reduction of critical slowing down at the phase transition is verified. This…

High Energy Physics - Lattice · Physics 2009-10-22 Christian Holm , Wolfhard Janke

In lattice QCD, the trace of the inverse of the discretized Dirac operator appears in the disconnected fermion loop contribution to an observable. As simulation methods get more and more precise, these contributions become increasingly…

High Energy Physics - Lattice · Physics 2022-11-29 Andreas Frommer , Gustavo Ramirez-Hidalgo

We introduce a general Monte Carlo scheme for achieving atomistic simulations with monoelectronic Hamiltonians including the thermalization of both nuclear and electronic degrees of freedom. The kinetic Monte Carlo algorithm is used to…

Materials Science · Physics 2009-11-07 F. Calvo , F. Spiegelman

This paper presents a novel event camera simulation system fully based on physically based Monte Carlo path tracing with adaptive path sampling. The adaptive sampling performed in the proposed method is based on a statistical technique,…

Computer Vision and Pattern Recognition · Computer Science 2024-08-16 Yuichiro Manabe , Tatsuya Yatagawa , Shigeo Morishima , Hiroyuki Kubo

The Hybrid Monte Carlo algorithm for the simulation of QCD with dynamical staggered fermions is compared with Kramers equation algorithm. We find substantially different autocorrelation times for local and nonlocal observables. The…

High Energy Physics - Lattice · Physics 2009-10-28 M. E. Berbenni-Bitsch , A. P. Gottlob , S. Meyer , M. Puetz

The new light-front coupled-cluster (LFCC) method for the nonperturbative solution of Hamiltonian eigenvalue problems is described and then illustrated in an application to quantum electrodynamics. The method eliminates any necessity for a…

High Energy Physics - Phenomenology · Physics 2012-03-02 S. S. Chabysheva , J. R. Hiller

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…

Machine Learning · Statistics 2016-09-15 Xiaoyu Lu , Valerio Perrone , Leonard Hasenclever , Yee Whye Teh , Sebastian J. Vollmer

Based on the scheme of variational Monte Carlo sampling, we develop an accurate and efficient two-dimensional tensor-network algorithm to simulate quantum lattice models. We find that Monte Carlo sampling shows huge advantages in dealing…

Strongly Correlated Electrons · Physics 2021-06-28 Wen-Yuan Liu , Yi-Zhen Huang , Shou-Shu Gong , Zheng-Cheng Gu
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