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We briefly review the principles, mathematical bases, numerical shortcuts and applications of fast random walk (FRW) algorithms. This Monte Carlo technique allows one to simulate individual trajectories of diffusing particles in order to…

Computational Physics · Physics 2013-05-01 Denis Grebenkov

The basic idea of fast Monte Carlo (MC) simulations is to perform particle-based MC simulations with the excluded-volume interactions modeled by "soft" repulsive potentials that allow particle overlapping. This gives much faster system…

Soft Condensed Matter · Physics 2012-01-24 Qiang Wang

Finding the ground state of Ising spin glasses is notoriously difficult due to disorder and frustration. Often, this challenge is framed as a combinatorial optimization problem, for which a common strategy employs simulated annealing, a…

We present results from Monte Carlo simulations to test for ultrametricity and clustering properties in spin-glass models. By using a one-dimensional Ising spin glass with random power-law interactions where the universality class of the…

Disordered Systems and Neural Networks · Physics 2009-01-26 Helmut G. Katzgraber , Alexander K. Hartmann

When utilizing a cluster decomposible relativistic scattering formalism, it is most convenient that the covariant field equations take on a linear form with respect to the energy and momentum dispersion on the fields in the manner given by…

Mathematical Physics · Physics 2007-05-23 James Lindesay

We consider dynamically constrained Monte-Carlo dynamics and show that this leads to the generation of long ranged effective interactions. This allows us to construct a local algorithm for the simulation of charged systems without ever…

Statistical Mechanics · Physics 2009-11-10 L. Levrel , F. Alet , J. Rottler , A. C. Maggs

We discuss a rejectionless global optimization technique which, while being technically similar to the recently introduced method of Extremal Optimization, still relies on a physical analogy with a thermalizing system. Our waiting time…

Statistical Mechanics · Physics 2009-11-07 Jesper Dall , Paolo Sibani

Monte Carlo algorithms are frequently used in atomistic simulations, including for computation of magnetic parameter temperature dependences in multiscale simulations. Even though parallelization strategies for Monte Carlo simulations of…

Mesoscale and Nanoscale Physics · Physics 2021-09-15 Serban Lepadatu , George McKenzie , Tim Mercer , Callum Robert MacKinnon , Philip Raymond Bissell

Generalized Ising models, also known as cluster expansions, are an important tool in many areas of condensed-matter physics and materials science, as they are often used in the study of lattice thermodynamics, solid-solid phase transitions,…

Statistical Mechanics · Physics 2016-06-27 Wenxuan Huang , Daniil Kitchaev , Stephen Dacek , Ziqin Rong , Zhiwei Ding , Gerbrand Ceder

A new representation is found for the action of the recently suggested ghost-free nonlocal gravity models generating de Sitter or Anti-de Sitter background with an arbitrary value of the effective cosmological constant. This representation…

High Energy Physics - Theory · Physics 2015-06-11 A. O. Barvinsky , Yu. V. Gusev

Flat-histogram Monte Carlo simulations are well-established, robust methods to perform random walks in a physical observable or parameter space, making them suitable for finding ground states or studying phase transitions in complex systems…

Statistical Mechanics · Physics 2026-01-28 Thomas Vogel , Ying Wai Li

We propose a framework for simulating the real-time dynamics of quantum field theories (QFTs) using continuous-variable quantum computing (CVQC). Focusing on ($1+1$)-dimensional $\varphi^4$ scalar field theory, the approach employs the…

Quantum Physics · Physics 2025-09-03 Steven Abel , Michael Spannowsky , Simon Williams

The Ising model is a simple statistical model for ferromagnetism. There are analytic solutions for low dimensions and very efficient Monte Carlo methods, such as cluster algorithms, for simulating this model in special cases. However most…

Computational Physics · Physics 2021-08-25 Johann Ostmeyer , Evan Berkowitz , Thomas Luu , Marcus Petschlies , Ferenc Pittler

A cluster mean-field method is introduced and the applications to the Ising and Heisenberg models are demonstrated. We divide the lattice sites into clusters whose size and shape are selected so that the equivalence of all sites in a…

Strongly Correlated Electrons · Physics 2013-05-29 Daisuke Yamamoto

Mean field-like approximations (including naive mean field, Bethe and Kikuchi and more general Cluster Variational Methods) are known to stabilize ordered phases at temperatures higher than the thermodynamical transition. For example, in…

Disordered Systems and Neural Networks · Physics 2015-06-22 A. Lage-Castellanos , R. Mulet , F. Ricci-Tersenghi

We describe a novel switching algorithm based on a ``reverse'' Monte Carlo method, in which the potential is stochastically modified before the system configuration is moved. This new algorithm facilitates a generalized formulation of…

Soft Condensed Matter · Physics 2009-11-13 C. H. Mak , Arun K. Sharma

We present a detailed discussion of our novel diagrammatic coupled cluster Monte Carlo (diagCCMC) [Scott et al. J. Phys. Chem. Lett. 2019, 10, 925]. The diagCCMC algorithm performs an imaginary-time propagation of the similarity-transformed…

Chemical Physics · Physics 2020-10-28 Charles J. C. Scott , Roberto Di Remigio , T. Daniel Crawford , Alex J. W. Thom

The principle and the efficiency of the Monte Carlo transfer-matrix algorithm are discussed. Enhancements of this algorithm are illustrated by applications to several phase transitions in lattice spin models. We demonstrate how the…

Condensed Matter · Physics 2009-10-28 M. P. Nightingale , H. W. J. Bloete

Close to the chiral limit, many calculations in numerical lattice QCD can potentially be accelerated using low-mode deflation techniques. In this paper it is shown that the recently introduced domain-decomposed deflation subspaces can be…

High Energy Physics - Lattice · Physics 2008-11-26 Martin Lüscher

In this work we have calculated the dynamic critical exponent $z$ for 2-, 3- and 4-dimensional Ising models using the Wolff's algorithm through dynamic finite size scaling. We have studied time evolution of the average cluster size, the…

Statistical Mechanics · Physics 2007-05-23 Mehmet Dílaver , Semra Gündüç , Meral Aydın , Yiğit Gündüç