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arXiv 2103.01339math.FAmath.GN
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网收敛结构及其在向量格上的应用

Net convergence structures with applications to vector lattices

M. O'Brien, V. G. Troitsky, J. H. van der Walt

摘要:

收敛是分析中的一个基本主题,通常使用拓扑建模。然而,有许多自然收敛不是由任何拓扑给出的;例如,可测函数序列的几乎处处收敛和向量格网的序收敛。收敛结构理论为研究更一般的收敛模式提供了一个框架。它还有一个特别显著的功能:是使用过滤器语言形式化的。本文发展了一个关于网的收敛性的一般理论。我们表明,它是等效的过滤器为基础的理论,并提出了两个领域之间的一些翻译。特别是,我们提供了一个表征的预拓扑收敛结构的网。我们还使用我们的结果统一某些议题的向量格与一般收敛理论。

英文摘要:

Convergence is a fundamental topic in analysis that is most commonly modelled using topology. However, there are many natural convergences that are not given by any topology; e.g., convergence almost everywhere of a sequence of measurable functions and order convergence of nets in vector lattices. The theory of convergence structures provides a framework for studying more general modes of convergence. It also has one particularly striking feature: it is formalized using the language of filters. This paper develops a general theory of convergence in terms of nets. We show that it is equivalent to the filter-based theory and present some translations between the two areas. In particular, we provide a characterization of pretopological convergence structures in terms of nets. We also use our results to unify certain topics in vector lattices with general convergence theory.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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