Iterated magnitude homology
Emily Roff
TL;DR
This work develops iterated magnitude homology to capture higher-order enrichment structures in categories, linking magnitude homology to bicategorical classifying spaces via the double magnitude nerve. It proves an Eilenberg–Zilber-type theorem and Künneth formulas for magnitude chain complexes, enabling computations for product and metric-space settings. For strict 2-categories, the iterated theory recovers the classical homology of the classifying space, and the framework is applied to enriched groups (strict 2-groups, partially ordered groups, and normed groups) to extract both topological and geometric invariants. The results illuminate how higher-order enrichment governs homological behavior and extend naturally to strict n-categories, offering a unified tool for probing algebraic and geometric structure in enriched categorical contexts.
Abstract
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 $n > 2$.
