Computing Generalized Rank Invariant for 2-Parameter Persistence Modules via Zigzag Persistence and its Applications
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Abstract (arXiv)
The notion of generalized rank invariant in the context of multiparameter persistence has become an important ingredient for defining interesting homological structures such as generalized persistence diagrams. Naturally, computing these rank invariants efficiently is a prelude to computing any of these derived structures efficiently. We show that the generalized rank over a finite interval I of a mathbbZ2-indexed persistence module M is equal to the generalized rank of the zigzag module that is induced on a certain path in I tracing mostly its boundary. Hence, we can compute the generalized rank over I by computing the barcode of the zigzag module obtained by restricting the bifiltration inducing M to that path. If the bifiltration and I have at most t simplices and points respectively, this computation takes O(tω) time where ω∈[2,2.373) is the exponent of matrix multiplication. Among others, we apply this result to obtain an improved algorithm for the following problem. Given a bifiltration inducing a module M, determine whether M is interval decomposable and, if so, compute all intervals supporting its summands.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 30 Nov 2021.
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Citing papers per year: 2023: 1; 2024: 2; 2025: 1.
4 papers.
- 2023GRIL: A 2-parameter Persistence Based Vectorization for Machine Learningcited by 13
- 2024Persistent Topological Features in Large Language Modelscited by 12
- 2024D-GRIL: End-to-End Topological Learning with 2-parameter Persistencecited by 5
- 2025Quasi Zigzag Persistence: A Topological Framework for Analyzing Time-Varying Datacited by 1
- 2025Quasi Zigzag Persistence: A Topological Framework for Analyzing Time-Varying Data22 Feb 2025
- 2024Persistent Topological Features in Large Language Models14 Oct 2024
- 2024D-GRIL: End-to-End Topological Learning with 2-parameter Persistence11 Jun 2024
- 2023GRIL: A 2-parameter Persistence Based Vectorization for Machine Learning11 Apr 2023