Publications/Preprints

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Orthogonal Möbius Inversion and Grassmannian Persistence Diagrams

Preprint, 2023

We introduce the notion of Orthogonal Möbius Inversion, a custom-made analog to Möbius inversion on the poset of intervals of a linear poset $P$. This notion is applicable to functions whose target space is the Grassmannian of a given inner product space $V$. When this notion of inversion is applied to such a function, we obtain another function, called the Grassmannian persistence diagram. Read more

Recommended citation: Gülen, A.B., Mémoli, F., Wan, Z. (2023). Orthogonal Möbius Inversion and Grassmannian Persistence Diagrams. arXiv preprint. arXiv:2311.06870.

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A Generalization of the Persistent Laplacian to Simplicial Maps

Published in Proceedings of the 39th International Symposium on Computational Geometry (SoCG)., 2023

The (combinatorial) graph Laplacian is a fundamental object in the analysis of, and optimization on, graphs. Via a topological view, this operator can be extended to a simplicial complex $K$ and therefore offers a way to perform “signal processing” on $p$-(co)chains of $K$. Recently, the concept of persistent Laplacian was proposed and studied for a pair of simplicial complexes $K\hookrightarrow L$ connected by an inclusion relation, further broadening the use of Laplace-based operators. In this paper, we significantly expand the scope of the persistent Laplacian by generalizing it to a pair of weighted simplicial complexes connected by a weight preserving simplicial map $f: K \to L$. Such a simplicial map setting arises frequently, e.g., when relating a coarsened simplicial representation with an original representation, or the case when the two simplicial complexes are spanned by different point sets, i.e. cases in which it does not hold that $K\subset L$. However, the simplicial map setting is much more challenging than the inclusion setting since the underlying algebraic structure is much more complicated. Read more

Recommended citation: Gülen, A.B., Mémoli, F., Wan, Z., Wang, Y. (2023). A Generalization of the Persistent Laplacian to Simplicial Maps. 39th International Symposium on Computational Geometry (SoCG 2023).

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Galois Connections in Persistent Homology

Preprint, 2022

High-dimensional data sets are typically very difficult to understand. Statistics provides a wealth of quantitative tools for tackling this problem. Topological data analysis (TDA) on the other hand offers qualitative invariants for understanding high-dimensional data sets. Persistent homology is the main tool used in TDA. It takes as input a nested sequence of spaces and outputs an invariant that captures where holes were born and died in the sequence of spaces. This invariant is called the persistence diagram or barcode. We provide a new language for studying persistent homology. We show that this language unifies central concepts in persistent homology. And it also provides access to Rota’s Galois connection theorem. Read more

Recommended citation: Gülen, A.B., McCleary, A. (2022). Galois Connections is Persistent Homology. arXiv preprint. arXiv:2201.06650.

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