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Related papers: Self-attracting self-avoiding walk

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Two closely related models of oriented self-avoiding walks (OSAWs) on a square lattice are studied. We use the pruned-enriched Rosenbluth method to determine numerically the phase diagram. Both models have three phases: a tight-spiral phase…

Condensed Matter · Physics 2007-05-23 G. T. Barkema , U. Bastolla , P. Grassberger

Quantum walks exhibit many unique characteristics compared to classical random walks. In the classical setting, self-avoiding random walks have been studied as a variation on the usual classical random walk. Classical self-avoiding random…

Quantum Physics · Physics 2015-01-08 Elizabeth Camilleri , Peter P. Rohde , Jason Twamley

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

Given a connected graph $G$ with some subset of its vertices excited and a fixed target vertex, in the geodesic-biased random walk on $G$, a random walker moves as follows: from an unexcited vertex, she moves to a uniformly random…

Probability · Mathematics 2019-09-13 Mikhail Beliayeu , Petr Chmel , Bhargav Narayanan , Jan Petr

Counting the number of N-step self-avoiding walks (SAWs) on a lattice is one of the most difficult problems of enumerative combinatorics. Once we give up calculating the exact number of them, however, we have a chance to apply powerful…

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

We consider a discrete time biased random walk conditioned to avoid Bernoulli obstacles on ${\mathbb Z}^d$ ($d\geq 2$) up to time $N$. This model is known to undergo a phase transition: for a large bias, the walk is ballistic whereas for a…

Probability · Mathematics 2020-09-17 Jian Ding , Ryoki Fukushima , Rongfeng Sun , Changji Xu

We study a scenario under which variable step random walks give anomalous statistics. We begin by analyzing the Martingale Central Limit Theorem to find a sufficient condition for the limit distribution to be non-Gaussian. We note that the…

Data Analysis, Statistics and Probability · Physics 2009-11-10 Gemunu H. Gunaratne , Joseph L. McCauley , Matthew Nicol , Andrei Torok

The connective constant $\mu(G)$ of a graph $G$ is the asymptotic growth rate of the number of self-avoiding walks on $G$ from a given starting vertex. We survey three aspects of the dependence of the connective constant on the underlying…

Combinatorics · Mathematics 2015-03-29 Geoffrey R. Grimmett , Zhongyang Li

We study a self-attractive random walk such that each trajectory of length $N$ is penalised by a factor proportional to $\exp ( - |R_N|)$, where $R_N$ is the set of sites visited by the walk. We show that the range of such a walk is close…

Probability · Mathematics 2020-03-04 Nathanael Berestycki , Raphael Cerf

The Hammersley-Welsh bound (1962) states that the number $c_n$ of length $n$ self-avoiding walks on $\mathbb{Z}^d$ satisfies \[ c_n \leq \exp \left[ O(n^{1/2}) \right] \mu_c^n, \] where $\mu_c=\mu_c(d)$ is the connective constant of…

Probability · Mathematics 2017-11-23 Tom Hutchcroft

This paper proves the formula \nu(d) =1 for d=1 and \nu(d) = max(1/4 +1/d, 1/2) for d > 1 for the root mean square displacement exponent \nu(d) of the self-avoiding walk (SAW) in Z^d, and thus, resolves some major long-standing open…

Probability · Mathematics 2007-05-23 Irene Hueter

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…

We consider a self-attracting random walk in dimension d=1, in presence of a field of strength s, which biases the walker toward a target site. We focus on the dynamic case (true reinforced random walk), where memory effects are implemented…

Statistical Mechanics · Physics 2015-06-05 Elena Agliari , Raffaella Burioni , Guido Uguzzoni

Kinetically-grown self-avoiding walks have been studied on Watts-Strogatz small-world networks, rewired from a two-dimensional square lattice. The maximum length L of this kind of walks is limited in regular lattices by an attrition effect,…

Disordered Systems and Neural Networks · Physics 2009-11-13 Carlos P. Herrero

We consider spread-out models of self-avoiding walk, bond percolation, lattice trees and bond lattice animals on the d-dimensional hyper cubic lattice having long finite-range connections, above their upper critical dimensions d=4…

Mathematical Physics · Physics 2007-05-23 Takashi Hara , Remco van der Hofstad , Gordon Slade

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 study a continuous time random walk on the $d$-dimensional lattice, subject to a drift and an attraction to large clusters of a subcritical Bernoulli site percolation. We find two distinct regimes: a ballistic one, and a subballistic one…

Probability · Mathematics 2007-10-12 Francis Comets , Francois Simenhaus

We define a new ensemble for self-avoiding walks in the upper half-plane, the fixed irredicible bridge ensemble, by considering self-avoiding walks in the upper half-plane up to their $n$-th bridge height, $Y_n$, and scaling the walk by…

Mathematical Physics · Physics 2015-06-23 Michael James Gilbert

For d at least two and integer n, let c_n = c_n(d) denote the number of length n self-avoiding walks beginning at the origin in the integer lattice Z^d, and, for even n, let p_n = p_n(d) denote the number of length n self-avoiding polygons…

Probability · Mathematics 2017-02-09 Alan Hammond

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