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原文連結
論文資訊
- 類型：已發表論文
- 日期：2025-03-01
摘要
Forman-Ricci curvature (FRC) is a potent and powerful tool for analyzing empirical 網絡s, as the distribution of the curvature values can identify structural 資訊 that is not readily detected by other geometrical methods. Crucially, FRC captures higher-order structural 資訊 of clique complexes of a graph or Vietoris-Rips complexes, which is not readily accessible to alternative methods. However, existing FRC platforms are prohibitively 計算ly expensive. Therefore, we develop an efficient set-theoretic formulation for computing such high-order FRC in simplicial complexes. Significantly, our set theory representation reveals previous 計算 bottlenecks and also accelerates the computation of FRC. Finally, we provide a pseudocode, a software implementation coined FastForman, as well as a benchmark compar
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