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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 examine self-avoiding walks in dimensions 4 to 8 using high-precision Monte-Carlo simulations up to length N=16384, providing the first such results in dimensions $d > 4$ on which we concentrate our analysis. We analyse the scaling…

Statistical Mechanics · Physics 2009-11-07 Aleksander L. Owczarek , Thomas Prellberg

We study the asymptotic behavior of ``true" self-avoiding random walks on general infinite locally finite trees. In this model, the walk starts at the root and, at each step, from its current vertex chooses a neighboring edge to traverse…

Probability · Mathematics 2026-05-04 Tuan-Minh Nguyen

The Sliced-Wasserstein distance (SW) is a computationally efficient and theoretically grounded alternative to the Wasserstein distance. Yet, the literature on its statistical properties -- or, more accurately, its generalization properties…

Machine Learning · Statistics 2023-06-01 Ruben Ohana , Kimia Nadjahi , Alain Rakotomamonjy , Liva Ralaivola

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

It has been recently argued that interacting self-avoiding walks (ISAW) of length $ \ell , $ in their low temperature phase (i.e. below the $ \Theta $-point) should have a partition function of the form: $$ Q_{\ell} \sim \mu^{ \ell}_ 0\mu^{…

Condensed Matter · Physics 2009-10-22 Bertrand Duplantier

We present improved simulations of three-dimensional self avoiding walks with one end attached to an impenetrable surface on the simple cubic lattice. This surface can either be a-thermal, having thus only an entropic effect, or attractive.…

Soft Condensed Matter · Physics 2009-11-10 Peter Grassberger

Optimal Transport has received much attention in Machine Learning as it allows to compare probability distributions by exploiting the geometry of the underlying space. However, in its original formulation, solving this problem suffers from…

Machine Learning · Computer Science 2023-11-27 Clément Bonet

While completely self-avoiding quantum walks have the distinct property of leading to a trivial unidirectional transport of a quantum state, an interesting and non-trivial dynamics can be constructed by restricting the self-avoidance to a…

Quantum Physics · Physics 2015-12-22 Takuya Machida , C. M. Chandrashekar , Norio Konno , Thomas Busch

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

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

The connective constant $\mu(G)$ of a quasi-transitive graph $G$ is the asymptotic growth rate of the number of self-avoiding walks (SAWs) on $G$ from a given starting vertex. We survey several aspects of the relationship between the…

Combinatorics · Mathematics 2019-07-15 Geoffrey R. Grimmett , Zhongyang Li

We investigate a model of continuous-time simple random walk paths in $\mathbb{Z}^d$ undergoing two competing interactions: an attractive one towards the large values of a random potential, and a self-repellent one in the spirit of the…

We give exact relations for a number of amplitude combinations that occur in the study of self-avoiding walks, polygons and lattice trails. In particular, we elucidate the lattice-dependent factors which occur in those combinations which…

Condensed Matter · Physics 2009-10-22 John L. Cardy , Anthony J. Guttmann

The exact solution of directed self-avoiding walks confined to a slit of finite width and interacting with the walls of the slit via an attractive potential has been calculated recently. The walks can be considered to model the…

Statistical Mechanics · Physics 2009-11-13 A. L. Owczarek , T. Prellberg , A. Rechnitzer

Although the title seems self-contradictory, it does not contain a misprint. The model we study is a seemingly minor modification of the "true self-avoiding walk" (TSAW) model of Amit, Parisi, and Peliti in two dimensions. The walks in it…

Statistical Mechanics · Physics 2017-10-11 Peter Grassberger

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

CSAW (conditioned self-avoiding walk) is a model of protein folding that combines SAW (self-avoiding walk) with Monte-Carlo. It simulates the Brownian motion of a chain molecule in the presence of interactions, both among chain residues,…

Statistical Mechanics · Physics 2007-05-23 Kerson Huang

The goal is to show that an edge-reinforced random walk on a graph of bounded degree, with reinforcement weight function $W$ taken from a general class of reciprocally summable reinforcement weight functions, traverses a random attracting…

Probability · Mathematics 2009-09-29 Vlada Limic , Pierre Tarrès

We consider one-dimensional discrete-time random walks (RWs) with arbitrary symmetric and continuous jump distributions $f(\eta)$, including the case of L\'evy flights. We study the expected maximum ${\mathbb E}[M_n]$ of bridge RWs, i.e.,…

Statistical Mechanics · Physics 2021-08-30 Benjamin De Bruyne , Satya N. Majumdar , Gregory Schehr
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