{"title":"On the largest part size of low‐rank combinatorial assemblies","authors":"R. Arratia, S. Desalvo","doi":"10.1002/rsa.21132","DOIUrl":null,"url":null,"abstract":"We give a general framework for approximations to decomposable combinatorial structures suitable to the situation where the size n$$ n $$ and the number of components k$$ k $$ are specified. In particular for assemblies, this involves a Poisson process, which, with the appropriate choice of parameter, may be viewed as an extension of saddlepoint approximation. We illustrate the use of the Poisson process description for assemblies by analyzing the component structure when the rank, defined as r:=n−k$$ r:= n-k $$ , is small relative to the size n$$ n $$ . There is near‐universal behavior, in the sense that, apart from degenerate cases where the exponential generating function has radius of convergence zero, we have for t∈(0,∞)$$ t\\in \\left(0,\\infty \\right) $$ and ℓ=1,2,…$$ \\ell =1,2,\\dots $$ : when r≍nα$$ r\\asymp {n}^{\\alpha } $$ for fixed α∈(ℓℓ+1,ℓ+1ℓ+2)$$ \\alpha \\in \\left(\\frac{\\ell }{\\ell +1},\\frac{\\ell +1}{\\ell +2}\\right) $$ , the size L1$$ {L}_1 $$ of the largest component converges in probability to ℓ+2$$ \\ell +2 $$ ; when r∼tnℓ/(ℓ+1)$$ r\\sim t\\kern0.3em {n}^{\\ell /\\left(\\ell +1\\right)} $$ , we have ℙ(L1∈{ℓ+1,ℓ+2})→1$$ \\mathbb{P}\\left({L}_1\\in \\left\\{\\ell +1,\\ell +2\\right\\}\\right)\\to 1 $$ , with the choice governed by a Poisson limit distribution for the number of components of size ℓ+2$$ \\ell +2 $$ . This was recently observed, for the case ℓ=1$$ \\ell =1 $$ and the special cases of permutations and set partitions, using Chen–Stein approximations for the indicators of attacks and alignments in rook placements.","PeriodicalId":54523,"journal":{"name":"Random Structures & Algorithms","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Random Structures & Algorithms","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1002/rsa.21132","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: 1
Abstract
We give a general framework for approximations to decomposable combinatorial structures suitable to the situation where the size n$$ n $$ and the number of components k$$ k $$ are specified. In particular for assemblies, this involves a Poisson process, which, with the appropriate choice of parameter, may be viewed as an extension of saddlepoint approximation. We illustrate the use of the Poisson process description for assemblies by analyzing the component structure when the rank, defined as r:=n−k$$ r:= n-k $$ , is small relative to the size n$$ n $$ . There is near‐universal behavior, in the sense that, apart from degenerate cases where the exponential generating function has radius of convergence zero, we have for t∈(0,∞)$$ t\in \left(0,\infty \right) $$ and ℓ=1,2,…$$ \ell =1,2,\dots $$ : when r≍nα$$ r\asymp {n}^{\alpha } $$ for fixed α∈(ℓℓ+1,ℓ+1ℓ+2)$$ \alpha \in \left(\frac{\ell }{\ell +1},\frac{\ell +1}{\ell +2}\right) $$ , the size L1$$ {L}_1 $$ of the largest component converges in probability to ℓ+2$$ \ell +2 $$ ; when r∼tnℓ/(ℓ+1)$$ r\sim t\kern0.3em {n}^{\ell /\left(\ell +1\right)} $$ , we have ℙ(L1∈{ℓ+1,ℓ+2})→1$$ \mathbb{P}\left({L}_1\in \left\{\ell +1,\ell +2\right\}\right)\to 1 $$ , with the choice governed by a Poisson limit distribution for the number of components of size ℓ+2$$ \ell +2 $$ . This was recently observed, for the case ℓ=1$$ \ell =1 $$ and the special cases of permutations and set partitions, using Chen–Stein approximations for the indicators of attacks and alignments in rook placements.
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.