Mathematical Sciences: General Frameworks for Classification Theory

数学科学：分类理论的一般框架

• 批准号: 9704541
• 负责人: Steven Buechler
• 金额: $ 9.9万
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-07-01 至 2001-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9704541&HistoricalAwards=false
• 关键词: Mathematical; Sciences; General; Frameworks; Classification

Professor Buechler's proposed research is in stability-theoretic classification theory, a subfield of model theory. In recent years, methods developed in the context of stability theory have been used to analyze structures such as pseudo-finite fields, pseudo-algebraically closed fields, difference fields, and quadratic forms over finite fields. This research has yielded applications to arithmetic number theory (due largely to Hrushovski). Model-theorists now have a good understanding of how these dependence relations fit in a general framework. Buechler proposes to generalize techniques from the geometrical stability theory of superstable theories to this broader class. This research is likely to give insight into the model-theoretic properties of bilinear forms and groups definable in structures such as those mentioned above. Buechler also intends to set a more general framework for arguments based on ranks and dependence relations. Much of mathematics involves the classification of an abstract collection of objects in terms of concrete, well-understood objects. The classification of finite simple groups is one instance of this principle. Model theorists study classification results in an abstract setting, addressing questions such as: When can we prove that a classification theorem exists, even when the particular theorem is unknown? How can we tell when a particular classification theorem is the best possible result for a given collection of objects? When are two classification theorems special cases of a more general result? In the past twenty years model theorists have gone a long way towards answering these questions for collections of objects axiomatized in a relatively simple manner. While this research is carried out in abstract setting, it has spawned concrete results in differential algebra and arithmetic number theory. Buechler proposes to expand the mathematical context in which these results apply. He will also find a more abstract notion of classification theorem which encompasses several existing examples. This may lead to a greater understanding of results related to Fermat's Last Theorem.

Buechler教授建议的研究是在稳定性理论分类理论中，这是模型理论的一个子领域。近年来，在稳定性理论的背景下发展起来的方法被用来分析有限域上的伪有限场、伪代数闭场、差场和二次型等结构。这项研究已经在算术数论中得到了应用(主要归功于赫鲁晓夫斯基)。模型理论家现在已经很好地理解了这些依赖关系是如何在一般框架中适用的。比克勒建议将技术从超稳理论的几何稳定性理论推广到这一更广泛的类别。这项研究可能会深入了解双线性形式和群的模型理论性质，这些双线性形式和群可定义在上述结构中。比切勒还打算为基于等级和依赖关系的论点设定一个更一般的框架。许多数学涉及到将抽象的对象集合归类为具体的、容易理解的对象。有限单群的分类就是这一原理的一个例子。模型理论家在抽象的环境中研究分类结果，解决这样的问题：我们何时才能证明分类定理的存在，即使特定的定理是未知的？对于给定的对象集合，我们如何判断特定的分类定理何时是最佳可能结果呢？什么时候两个分类定理是更一般结果的特例？在过去的二十年里，模型理论家们在以一种相对简单的方式公理化的对象集合方面为回答这些问题付出了很大的努力。虽然这项研究是在抽象的背景下进行的，但它在微分代数和算术数论方面已经产生了具体的结果。比克勒建议扩大这些结果适用的数学背景。他还将发现分类定理的一个更抽象的概念，它包含了几个现有的例子。这可能会使我们更好地理解与费马大定理有关的结果。