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Berkeley Conference in Inner Model Theory

伯克利内模型理论会议

基本信息

批准号：
1919537
负责人：
John Steel
金额：
$ 0.8万
依托单位：
University of California-Berkeley
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-05-01 至 2021-04-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1919537&HistoricalAwards=false
关键词：
Berkeley Conference Inner Model Theory

项目摘要

The Berkeley Conference on Inner Model Theory will be held July 8-19, 2019 at the Department of Mathematics, University of California, Berkeley. It will be devoted to significant recent progress in inner model theory. The new work includes advances in iteration tree combinatorics, leading to a general comparison theorem for the iteration strategies of mice having no long extenders, and from there to a new theory of the hereditarily ordinal definable sets in models of the Axiom of Determinacy. The Berkeley conference will gather experts in inner model theory from around the world, as well as students and postdocs with a serious interest in the field, in order to communicate and pursue the new ideas.Large cardinal hypotheses play a central role in the set-theoretic foundations of mathematics. The inner model program attempts toassociate to each large cardinal hypothesis a canonical minimal universe of sets in which that hypothesis is true. Some of our deepest understanding of large cardinal hypotheses come from this program. The core model induction method is our most powerful method for constructing such canonical inner models, and this conference will be devoted to recent work that strengthens the method in important ways. The website for the conference is https://ivv5hpp.uni-muenster.de/u/rds/berkeley_meeting_2019.html.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

伯克利会议内部模型理论将于2019年7月8日至19日在数学系，加州大学伯克利分校举行。它将致力于内模理论的重大进展。新的工作包括进步迭代树组合，导致一般比较定理的迭代策略的小鼠没有长的扩展，并从那里到一个新的理论的遗传有序可定义集模型的公理的决定性。伯克利会议将聚集来自世界各地的内模型理论专家，以及对该领域有浓厚兴趣的学生和博士后，以交流和追求新的想法。大基数假设在数学的集合论基础中发挥着核心作用。内部模型程序试图将每个大的基数假设与一个规范的最小集合论域联系起来，在这个集合论域中，这个假设是正确的。我们对大基数假设的一些最深刻的理解来自这个程序。核心模型归纳法是我们构造这种正则内部模型的最有力的方法，这次会议将致力于在重要方面加强该方法的最新工作。会议的网站是https://ivv5hpp.uni-muenster.de/u/rds/berkeley_meeting_2019.html.This奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。