Refined Large Deviation Principle for Branching Brownian Motion Conditioned to Have a Low Maximum

Pub Date : 2021-02-18 DOI:10.30757/alea.v19-34
Yanjia Bai, Lisa Hartung
{"title":"Refined Large Deviation Principle for Branching Brownian Motion Conditioned to Have a Low Maximum","authors":"Yanjia Bai, Lisa Hartung","doi":"10.30757/alea.v19-34","DOIUrl":null,"url":null,"abstract":"A BSTRACT . Conditioning a branching Brownian motion to have an atypically low maximum leads to a suppression of the branching mechanism. In this note, we consider a branching Brownian motion conditioned to have a maximum below √ 2 α t ( α < 1). We study the precise effects of an early/late first branching time and a low/high first branching location under this condition. We do so by imposing additional constraints on the first branching time and location. We obtain large deviation estimates, as well as the optimal first branching time and location given the additional constraints.","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.30757/alea.v19-34","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

A BSTRACT . Conditioning a branching Brownian motion to have an atypically low maximum leads to a suppression of the branching mechanism. In this note, we consider a branching Brownian motion conditioned to have a maximum below √ 2 α t ( α < 1). We study the precise effects of an early/late first branching time and a low/high first branching location under this condition. We do so by imposing additional constraints on the first branching time and location. We obtain large deviation estimates, as well as the optimal first branching time and location given the additional constraints.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
具有低极大值条件下分支布朗运动的精细大偏差原理
摘要。将分支布朗运动调节为具有异常低的最大值会导致分支机制的抑制。在本文中,我们考虑一个分支布朗运动,条件是其最大值低于√2αt(α<1)。我们研究了在这种情况下第一次分支时间早/晚和第一次分支位置低/高的精确影响。我们通过对第一个分支的时间和位置施加额外的限制来做到这一点。我们获得了大偏差估计,以及在附加约束条件下的最佳第一分支时间和位置。
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
×
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