Persistent Dirac of Path and Hypergraph

TL;DR

This paper develops persistent path and hypergraph Dirac operators that analyze topological features and spectra in complex structures, with applications in molecular science and topological data analysis.

Contribution

It introduces novel persistent Dirac operators for paths and hypergraphs, demonstrating their ability to distinguish spectra and adapt to topological changes in data.

Findings

Operators differentiate harmonic and non-harmonic spectra.

Effective in analyzing molecular structures via topological methods.

Showcase adaptability to filtration and topological changes.

Abstract

This work introduces the development of path Dirac and hypergraph Dirac operators, along with an exploration of their persistence. These operators excel in distinguishing between harmonic and non-harmonic spectra, offering valuable insights into the subcomplexes within these structures. The paper showcases the functionality of these operators through a series of examples in various contexts. An important facet of this research involves examining the operators' sensitivity to filtration, emphasizing their capacity to adapt to topological changes. The paper also explores a significant application of persistent path Dirac and persistent hypergraph Dirac in the field of molecular science, specifically in the analysis of molecular structures. The study introduces strict preorders derived from molecular structures, which generate graphs and digraphs with intricate path structures. The depth of information within these path complexes reflects the complexity of different preorder classes influenced by molecular structures. This characteristic underscores the effectiveness of these tools in the realm of topological data analysis.