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Random walks are frequently used as a model for very diverse physical phenomena. The Monte Carlo method is a versatile tool for the study of the properties of systems modelled as random walks. Often, each walker is associated with a…

Statistical Mechanics · Physics 2021-07-21 Hunter Belanger , Davide Mancusi , Andrea Zoia

We introduce a Monte-Carlo algorithm for the simulation of charged particles moving in the continuum. Electrostatic interactions are not instantaneous as in conventional approaches, but are mediated by a constrained, diffusing electric…

Soft Condensed Matter · Physics 2009-11-10 Joerg Rottler , A. C. Maggs

We propose a novel computational strategy to study the glass transition of molecular fluids. Our approach combines the construction of simple yet realistic models with the development of Monte Carlo algorithms to accelerate equilibration…

Statistical Mechanics · Physics 2026-03-31 Romain Simon , Jean-Louis Barrat , Ludovic Berthier

Self-avoiding walks (SAWs) were introduced in chemistry to model the real-life behavior of chain-like entities such as solvents and polymers, whose physical volume prohibits multiple occupation of the same spatial point. In mathematics, a…

Data Structures and Algorithms · Computer Science 2013-10-01 Franc Brglez

Legged robots have the ability to adapt their walking posture to navigate confined spaces due to their high degrees of freedom. However, this has not been exploited in most common multilegged platforms. This paper presents a deformable…

An efficient implementation of the self-consistent GW method in the FlapwMBPT code (https://www.bnl.gov/cmpmsd/flapwmbpt/) is presented. It features the evaluation of polarizability and self-energy which scales linearly with respect to the…

Materials Science · Physics 2020-08-05 Andrey L. Kutepov

We investigate neighbor-avoiding walks on the simple cubic lattice in the presence of an adsorbing surface. This class of lattice paths has been less studied using Monte Carlo simulations. Our investigation follows on from our previous…

Statistical Mechanics · Physics 2019-01-02 C. J. Bradly , A. L. Owczarek , T. Prellberg

Optimizing or sampling complex cost functions of combinatorial optimization problems is a longstanding challenge across disciplines and applications. When employing family of conventional algorithms based on Markov Chain Monte Carlo (MCMC)…

Machine Learning · Computer Science 2025-08-15 Dmitrii Dobrynin , Masoud Mohseni , John Paul Strachan

This paper discusses some convergence properties in the entropic sampling Monte Carlo methods with multiple random walkers, particularly in the Wang-Landau (WL) and $1/t$ algorithms. The classical algorithms are modified by the use of $m$…

Statistical Mechanics · Physics 2016-06-22 R. E. Belardinelli , V. D. Pereyra

We study a restricted class of self-avoiding walks (SAW) which start at the origin (0, 0), end at $(L, L)$, and are entirely contained in the square $[0, L] \times [0, L]$ on the square lattice ${\mathbb Z}^2$. The number of distinct walks…

Statistical Mechanics · Physics 2016-08-31 M. Bousquet-Mélou , A. J. Guttmann , I. Jensen

We study a lattice model of a magnetic polymer where the XY spin variables are located on a self-avoiding walk (SAW) on a regular lattice in two and three dimensions. We consider the regime where both spins and conformations are dynamic,…

Statistical Mechanics · Physics 2024-05-14 Kamilla Faizullina , Evgeni Burovski

Integer linear programming (ILP) remains computationally challenging due to its NP-complete nature despite its central role in scheduling, logistics, and design optimization. We introduce a fully quantum Metropolis-Hastings algorithm for…

Quantum Physics · Physics 2026-02-16 Gabriel Escrig , Roberto Campos , M. A. Martin-Delgado

The Metropolis-Hastings algorithm has been extensively studied in the estimation and simulation literature, with most prior work focusing on convergence behavior and asymptotic theory. However, its covariance structure-an important…

Computation · Statistics 2026-03-03 Jingyi Zhang , James C. Spall

The work introduces a 3D cellular automaton model for the spatial and crystallographic prediction of spherulite growth phenomena in polymers at the mesoscopic scale. The automaton is discrete in time, real space, and orientation space. The…

Soft Condensed Matter · Physics 2008-11-11 D. Raabe

The phase diagram and surface critical behaviour of the vertex-interacting self-avoiding walk are examined using transfer matrix methods extended using DMRG and coupled with finite-size scaling. Particular attention is paid to the critical…

Statistical Mechanics · Physics 2015-06-12 Damien P. Foster , Claire Pinettes

For random-walk Metropolis (RWM) and parallel tempering (PT) algorithms, an asymptotic acceptance rate of around 0.234 is known to be optimal in certain high-dimensional limits. However, its practical relevance is uncertain due to…

Computation · Statistics 2025-08-05 Aidan Li , Liyan Wang , Tianye Dou , Jeffrey S. Rosenthal

The effect of the correlations in the diluteness pattern in the systems with non-integral dimensionality, on $\nu=\frac{4}{5}$ superdiffusion process is considered in this paper. These spatial correlations have proved to be very effective…

Statistical Mechanics · Physics 2019-09-04 J. Cheraghalizadeh , M. N. Najafi

We calculate the connective constant for self-avoiding walks on the simple cubic lattice to unprecedented accuracy, using a novel application of the pivot algorithm. We estimate that \mu = 4.684 039 931(27). Our method also provides…

Statistical Mechanics · Physics 2015-04-09 Nathan Clisby

Random walks on dynamic graphs have received increasingly more attention from different academic communities over the last decade. Despite the relatively large literature, little is known about random walks that construct the graph where…

Developing a robust algorithm for automatic individual tree crown (ITC) detection from laser scanning datasets is important for tracking the responses of trees to anthropogenic change. Such approaches allow the size, growth and mortality of…

Computer Vision and Pattern Recognition · Computer Science 2019-10-04 Jonathan Williams , Carola-Bibiane Schönlieb , Tom Swinfield , Juheon Lee , Xiaohao Cai , Lan Qie , David A. Coomes
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