A variational formula for large deviations in first-passage percolation under tail estimates

IF 1.4 2区 数学 Q2 STATISTICS & PROBABILITY Annals of Applied Probability Pub Date : 2021-01-20 DOI:10.1214/22-aap1861
Clément Cosco, S. Nakajima
{"title":"A variational formula for large deviations in first-passage percolation under tail estimates","authors":"Clément Cosco, S. Nakajima","doi":"10.1214/22-aap1861","DOIUrl":null,"url":null,"abstract":"Consider first passage percolation with identical and independent weight distributions and first passage time ${\\rm T}$. In this paper, we study the upper tail large deviations $\\mathbb{P}({\\rm T}(0,nx)>n(\\mu+\\xi))$, for $\\xi>0$ and $x\\neq 0$ with a time constant $\\mu$ and a dimension $d$, for weights that satisfy a tail assumption $ \\beta_1\\exp{(-\\alpha t^r)}\\leq \\mathbb P(\\tau_e>t)\\leq \\beta_2\\exp{(-\\alpha t^r)}.$ When $r\\leq 1$ (this includes the well-known Eden growth model), we show that the upper tail large deviation decays as $\\exp{(-(2d\\xi +o(1))n)}$. When $1<r\\leq d$, we find that the rate function can be naturally described by a variational formula, called the discrete p-Capacity, and we study its asymptotics. For $r<d$, we show that the large deviation event ${\\rm T}(0,nx)>n(\\mu+\\xi)$ is described by a localization of high weights around the origin. The picture changes for $r\\geq d$ where the configuration is not anymore localized.","PeriodicalId":50979,"journal":{"name":"Annals of Applied Probability","volume":null,"pages":null},"PeriodicalIF":1.4000,"publicationDate":"2021-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Applied Probability","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1214/22-aap1861","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 4

Abstract

Consider first passage percolation with identical and independent weight distributions and first passage time ${\rm T}$. In this paper, we study the upper tail large deviations $\mathbb{P}({\rm T}(0,nx)>n(\mu+\xi))$, for $\xi>0$ and $x\neq 0$ with a time constant $\mu$ and a dimension $d$, for weights that satisfy a tail assumption $ \beta_1\exp{(-\alpha t^r)}\leq \mathbb P(\tau_e>t)\leq \beta_2\exp{(-\alpha t^r)}.$ When $r\leq 1$ (this includes the well-known Eden growth model), we show that the upper tail large deviation decays as $\exp{(-(2d\xi +o(1))n)}$. When $1n(\mu+\xi)$ is described by a localization of high weights around the origin. The picture changes for $r\geq d$ where the configuration is not anymore localized.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
尾估计下一次渗流大偏差的变分公式
考虑具有相同和独立的权重分布和第一次通过时间${\rmT}$的第一次通过渗流。在本文中,我们研究了满足尾部假设$\beta\exp{(-\alpha T^r)}\leq\mathbb P(\tau_e>T)\leq\beta_2\exp(-\\alpha T^r)}的权重的上尾部大偏差$\mathbb{P}({\rm T}(0,nx)>n(\mu+\neneneba xi))$,对于时间常数$\mu$和维度$x\neq 0$当$r\leq1$(这包括众所周知的Eden增长模型)时,我们表明上尾大偏差衰减为$\exp{(-(2d\neneneba xi+o(1))n)}$。当$1n(\mu+\neneneba xi)$通过在原点周围定位高权重来描述时。$r\geq d$的图片发生了更改,其中配置不再本地化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Annals of Applied Probability
Annals of Applied Probability 数学-统计学与概率论
CiteScore
2.70
自引率
5.60%
发文量
108
审稿时长
6-12 weeks
期刊介绍: The Annals of Applied Probability aims to publish research of the highest quality reflecting the varied facets of contemporary Applied Probability. Primary emphasis is placed on importance and originality.
期刊最新文献
Well-posedness and wave-breaking for the stochastic rotation-two-component Camassa–Holm system A sample-path large deviation principle for dynamic Erdős–Rényi random graphs Quenched and averaged large deviations for random walks in random environments: The impact of disorder The bi-dimensional Directed IDLA forest A Kesten–Stigum type theorem for a supercritical multitype branching process in a random environment
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1