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Related papers: Exact enumeration of self-avoiding walks

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We give an algorithm for counting self-avoiding walks or self-avoiding polygons that runs in time $\exp(C\sqrt{n\log n})$ on 2-dimensional lattices and time $\exp(C_dn^{(d-1)/d}\log n)$ on $d$-dimensional lattices for $d>2$.

Data Structures and Algorithms · Computer Science 2019-11-27 Samuel Zbarsky

We have extended the enumeration of self-avoiding walks on the Manhattan lattice from 28 to 53 steps and for self-avoiding polygons from 48 to 84 steps. Analysis of this data suggests that the walk generating function exponent gamma =…

Statistical Mechanics · Physics 2009-10-31 D. Bennett-Wood , J. L. Cardy , I. G. Enting , A. J. Guttmann , A. L. Owczarek

Motivated by recent claims of a proof that the length scale exponent for the end-to-end distance scaling of self-avoiding walks is precisely $7/12=0.5833...$, we present results of large-scale simulations of self-avoiding walks and…

Statistical Mechanics · Physics 2009-11-07 T. Prellberg

This article presents SAWdoubler, a package for counting the total number Z(N) of self-avoiding walks (SAWs) on a regular lattice by the length-doubling method, of which the basic concept has been published previously by us. We discuss an…

Statistical Mechanics · Physics 2015-06-11 Raoul D. Schram , Gerard T. Barkema , Rob H. Bisseling

We present an algorithm, based on the iteration of conformal maps, that produces independent samples of self-avoiding paths in the plane. It is a discrete process approximating radial Schramm-Loewner evolution growing to infinity. We focus…

Statistical Mechanics · Physics 2010-10-29 Marco Gherardi

We present an algorithm for enumerating exactly the number of Hamiltonian chains on regular lattices in low dimensions. By definition, these are sets of k disjoint paths whose union visits each lattice vertex exactly once. The well-known…

Statistical Mechanics · Physics 2009-11-13 Jesper Lykke Jacobsen

We develop statistical enumeration methods for self-avoiding walks using a powerful sampling technique called the multicanonical Monte Carlo method. Using these methods, we estimate the numbers of the two dimensional N-step self-avoiding…

Statistical Mechanics · Physics 2013-10-04 Nobu C. Shirai , Macoto Kikuchi

We present simulation results for long ($N\leq 4000$) self-avoiding walks in four dimensions. We find definite indications of logarithmic corrections, but the data are poorly described by the asymptotically leading terms. Detailed…

Condensed Matter · Physics 2009-10-22 Peter Grassberger , Rainer Hegger , Lothar Schaefer

This article is a pedagogical review of Monte Carlo methods for the self-avoiding walk, with emphasis on the extraordinarily efficient algorithms developed over the past decade. Many more details can be found in hep-lat/9405016.

High Energy Physics - Lattice · Physics 2009-10-28 Alan D. Sokal

Enumeration of planar lattice walks is a classical topic in combinatorics, at the cross-roads of several domains (e.g., probability, statistical physics, computer science). The aim of this paper is to propose a new approach to obtain some…

Probability · Mathematics 2013-01-15 Guy Fayolle , Kilian Raschel

We study self-avoiding walks on the four-dimensional hypercubic lattice via Monte Carlo simulations of walks with up to one billion steps. We study the expected logarithmic corrections to scaling, and find convincing evidence in support the…

Statistical Mechanics · Physics 2018-08-01 Nathan Clisby

The statistics of self-avoiding random walks have been used to model polymer physics for decades. A self-avoiding walk that grows one step at a time on a lattice will eventually trap itself, which occurs after an average of 71 steps on a…

Statistical Mechanics · Physics 2020-09-23 Wyatt Hooper , Alexander R. Klotz

We study the correction-to-scaling exponents for the two-dimensional self-avoiding walk, using a combination of series-extrapolation and Monte Carlo methods. We enumerate all self-avoiding walks up to 59 steps on the square lattice, and up…

This article is a pedagogical review of Monte Carlo methods for the self-avoiding walk, with emphasis on the extraordinarily efficient algorithms developed over the past decade.

High Energy Physics - Lattice · Physics 2007-05-23 Alan D. Sokal

Many recent papers deal with the enumeration of 2-dimensional walks with prescribed steps confined to the positive quadrant. The classification is now complete for walks with steps in $\{0, \pm 1\}^2$: the generating function is D-finite if…

Combinatorics · Mathematics 2025-04-11 Alin Bostan , Mireille Bousquet-Mélou , Manuel Kauers , Stephen Melczer

We have developed a parallel algorithm that allows us to enumerate the number of self-avoiding polygons on the square lattice to perimeter length 110. We have also extended the series for the first 10 area-weighted moments and the radius of…

Statistical Mechanics · Physics 2009-11-10 Iwan Jensen

The decay of directional correlations in self-avoiding random walks on the square lattice is investigated. Analysis of exact enumerations and Monte Carlo data suggest that the correlation between the directions of the first step and the…

Statistical Mechanics · Physics 2009-11-07 E. Eisenberg , A. Baram

We introduce a self-avoiding walk model for which end-effects are completely eliminated. We enumerate the number of these walks for various lattices in dimensions two and three, and use these enumerations to study the properties of this…

Statistical Mechanics · Physics 2015-04-09 Nathan Clisby

There is an extensive literature concerning self-avoiding walk on infinite graphs, but the subject is relatively undeveloped on finite graphs. The purpose of this paper is to elucidate the phase transition for self-avoiding walk on the…

Probability · Mathematics 2019-09-19 Gordon Slade

We study terminally attached self-avoiding walks and bridges on the simple cubic lattice, both by series analysis and Monte Carlo methods. We provide strong numerical evidence supporting a scaling relation between self-avoiding walks,…

Statistical Mechanics · Physics 2016-10-06 Nathan Clisby , Andrew R. Conway , Anthony J. Guttmann