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arXiv · 2512.20311

Algorithm for Interpretable Graph Features via Motivic Persistent Cohomology

Yoshihiro Maruyama
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Abstract

We present the Chromatic Persistence Algorithm (CPA), an event-driven method for computing persistent cohomological features of weighted graphs via graphic arrangements, a classical object in computational geometry. We establish rigorous complexity results: CPA is exponential in the worst case, fixed-parameter tractable in treewidth, and nearly linear for common graph families such as trees, cycles, and series-parallel graphs. Finally, we demonstrate its practical applicability through a controlled experiment on molecular-like graph structures.

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Yoshihiro Maruyama. 2025-12-23. Algorithm for Interpretable Graph Features via Motivic Persistent Cohomology. https://arxiv.org/abs/2512.20311

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