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arXiv 2309.00577math.ATmath.CTmath.GRmath.MG
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迭代量级同调

Iterated magnitude homology

Emily Roff

AI总结:

本文提出迭代量级同调,融合量级同调与几何神经,适用于高阶丰富范畴,在严格2-范畴中恢复分类空间同调,并探讨偏序群、赋范群等情形。

摘要:

量级同调是丰富范畴的一个不变量,它推广了普通范畴同调——即小范畴的分类空间的同调。分类空间还可以沿另一方向推广:它从范畴扩展到双范畴,作为几何神经的几何实现。本文引入了这两种思想的混合:一种针对具有二阶或更高阶丰富的范畴的迭代量级同调理论。这涵盖例如带有额外结构(如偏序或双不变度量)的群。在严格2-范畴的情形下,迭代量级同调恢复了分类空间的同调;我们研究了它在偏序群、赋范群以及$n>2$的严格$n$-范畴中的内容和行为。

英文摘要:

Magnitude homology is an invariant of enriched categories which generalizes ordinary categorical homology -- the homology of the classifying space of a small category. The classifying space can also be generalized in a different direction: it extends from categories to bicategories as the geometric realization of the geometric nerve. This paper introduces a hybrid of the two ideas: an iterated magnitude homology theory for categories with a second- or higher-order enrichment. This encompasses, for example, groups equipped with extra structure such as a partial ordering or a bi-invariant metric. In the case of a strict 2-category, iterated magnitude homology recovers the homology of the classifying space; we investigate its content and behaviour when interpreted for partially ordered groups, normed groups, and strict $n$-categories for $n > 2$.

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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