{"title":"Self‐avoiding walk on the hypercube","authors":"G. Slade","doi":"10.1002/rsa.21117","DOIUrl":null,"url":null,"abstract":"We study the number cn(N)$$ {c}_n^{(N)} $$ of n$$ n $$ ‐step self‐avoiding walks on the N$$ N $$ ‐dimensional hypercube, and identify an N$$ N $$ ‐dependent connective constant μN$$ {\\mu}_N $$ and amplitude AN$$ {A}_N $$ such that cn(N)$$ {c}_n^{(N)} $$ is O(μNn)$$ O\\left({\\mu}_N^n\\right) $$ for all n$$ n $$ and N$$ N $$ , and is asymptotically ANμNn$$ {A}_N{\\mu}_N^n $$ as long as n≤2pN$$ n\\le {2}^{pN} $$ for any fixed p<12$$ p<\\frac{1}{2} $$ . We refer to the regime n≪2N/2$$ n\\ll {2}^{N/2} $$ as the dilute phase. We discuss conjectures concerning different behaviors of cn(N)$$ {c}_n^{(N)} $$ when n$$ n $$ reaches and exceeds 2N/2$$ {2}^{N/2} $$ , corresponding to a critical window and a dense phase. In addition, we prove that the connective constant has an asymptotic expansion to all orders in N−1$$ {N}^{-1} $$ , with integer coefficients, and we compute the first five coefficients μN=N−1−N−1−4N−2−26N−3+O(N−4)$$ {\\mu}_N=N-1-{N}^{-1}-4{N}^{-2}-26{N}^{-3}+O\\left({N}^{-4}\\right) $$ . The proofs are based on generating function and Tauberian methods implemented via the lace expansion, for which an introductory account is provided.","PeriodicalId":54523,"journal":{"name":"Random Structures & Algorithms","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2021-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Random Structures & Algorithms","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1002/rsa.21117","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 3
Abstract
We study the number cn(N)$$ {c}_n^{(N)} $$ of n$$ n $$ ‐step self‐avoiding walks on the N$$ N $$ ‐dimensional hypercube, and identify an N$$ N $$ ‐dependent connective constant μN$$ {\mu}_N $$ and amplitude AN$$ {A}_N $$ such that cn(N)$$ {c}_n^{(N)} $$ is O(μNn)$$ O\left({\mu}_N^n\right) $$ for all n$$ n $$ and N$$ N $$ , and is asymptotically ANμNn$$ {A}_N{\mu}_N^n $$ as long as n≤2pN$$ n\le {2}^{pN} $$ for any fixed p<12$$ p<\frac{1}{2} $$ . We refer to the regime n≪2N/2$$ n\ll {2}^{N/2} $$ as the dilute phase. We discuss conjectures concerning different behaviors of cn(N)$$ {c}_n^{(N)} $$ when n$$ n $$ reaches and exceeds 2N/2$$ {2}^{N/2} $$ , corresponding to a critical window and a dense phase. In addition, we prove that the connective constant has an asymptotic expansion to all orders in N−1$$ {N}^{-1} $$ , with integer coefficients, and we compute the first five coefficients μN=N−1−N−1−4N−2−26N−3+O(N−4)$$ {\mu}_N=N-1-{N}^{-1}-4{N}^{-2}-26{N}^{-3}+O\left({N}^{-4}\right) $$ . The proofs are based on generating function and Tauberian methods implemented via the lace expansion, for which an introductory account is provided.
期刊介绍:
It is the aim of this journal to meet two main objectives: to cover the latest research on discrete random structures, and to present applications of such research to problems in combinatorics and computer science. The goal is to provide a natural home for a significant body of current research, and a useful forum for ideas on future studies in randomness.
Results concerning random graphs, hypergraphs, matroids, trees, mappings, permutations, matrices, sets and orders, as well as stochastic graph processes and networks are presented with particular emphasis on the use of probabilistic methods in combinatorics as developed by Paul Erdõs. The journal focuses on probabilistic algorithms, average case analysis of deterministic algorithms, and applications of probabilistic methods to cryptography, data structures, searching and sorting. The journal also devotes space to such areas of probability theory as percolation, random walks and combinatorial aspects of probability.