Computing a connection matrix and persistence efficiently from a morse decomposition

Dey TK, Haas A, Lipiński M. 2026. Computing a connection matrix and persistence efficiently from a morse decomposition. SIAM Journal on Applied Dynamical Systems. 25(1), 108–130.

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Author
Dey, Tamal K.; Haas, Andrew; Lipiński, MichałISTA
Department
Abstract
Morse decompositions partition the flows in a vector field into equivalent structures. Given such a decomposition, one can define a further summary of its flow structure by what is called a connection matrix. These matrices, a generalization of Morse boundary operators from classical Morse theory, capture the connections made by the flows among the critical structures—such as attractors, repellers, and orbits—in a vector field. Recently, in the context of combinatorial dynamics, an efficient persistence-like algorithm to compute connection matrices has been proposed in Dey, Lipiński, Mrozek, and Slechta [SIAM J. Appl. Dyn. Syst., 23 (2024), pp. 81–97]. We show that, actually, the classical persistence algorithm with exhaustive reduction retrieves connection matrices, both simplifying the algorithm of Dey et al. and bringing the theory of persistence closer to combinatorial dynamical systems. We supplement this main result with an observation: the concept of persistence as defined for scalar fields naturally adapts to Morse decompositions whose Morse sets are filtered with a Lyapunov function. We conclude by presenting preliminary experimental results.
Publishing Year
Date Published
2026-01-01
Journal Title
SIAM Journal on Applied Dynamical Systems
Publisher
Society for Industrial & Applied Mathematics
Acknowledgement
This research was supported by NSF grants DMS-2301360 and CCF-2437030 as well as from the European Union's Horizon 2020 research and innovation programme under Marie Sk\lodowska-Curie grant 101034413.
Volume
25
Issue
1
Page
108-130
ISSN
IST-REx-ID

Cite this

Dey TK, Haas A, Lipiński M. Computing a connection matrix and persistence efficiently from a morse decomposition. SIAM Journal on Applied Dynamical Systems. 2026;25(1):108-130. doi:10.1137/25m1739406
Dey, T. K., Haas, A., & Lipiński, M. (2026). Computing a connection matrix and persistence efficiently from a morse decomposition. SIAM Journal on Applied Dynamical Systems. Society for Industrial & Applied Mathematics. https://doi.org/10.1137/25m1739406
Dey, Tamal K., Andrew Haas, and Michał Lipiński. “Computing a Connection Matrix and Persistence Efficiently from a Morse Decomposition.” SIAM Journal on Applied Dynamical Systems. Society for Industrial & Applied Mathematics, 2026. https://doi.org/10.1137/25m1739406.
T. K. Dey, A. Haas, and M. Lipiński, “Computing a connection matrix and persistence efficiently from a morse decomposition,” SIAM Journal on Applied Dynamical Systems, vol. 25, no. 1. Society for Industrial & Applied Mathematics, pp. 108–130, 2026.
Dey TK, Haas A, Lipiński M. 2026. Computing a connection matrix and persistence efficiently from a morse decomposition. SIAM Journal on Applied Dynamical Systems. 25(1), 108–130.
Dey, Tamal K., et al. “Computing a Connection Matrix and Persistence Efficiently from a Morse Decomposition.” SIAM Journal on Applied Dynamical Systems, vol. 25, no. 1, Society for Industrial & Applied Mathematics, 2026, pp. 108–30, doi:10.1137/25m1739406.
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