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February 28, 2026Extremes0 citationsOpen Access

Poisson approximation of large-lifetime cycles

CHChristian HirschAarhus UniversityNLNikolaj Nyvold LundbyeAarhus UniversityMOMoritz OttoLeiden University

Key Points

  • The aim is to analyze large-lifetime cycles in point clouds represented as Poisson point processes.
  • Investigated cycles without upper limits on deathtime.
  • Established Poisson convergence on a 2-dimensional flat torus.
  • Imposed bounds on deathtime to study sparse connectivity.
  • Proved joint Poisson convergence in dimensions greater than or equal to 2.
  • Demonstrated Poisson convergence of cycle centers when deathtime is unbounded.
  • Observed joint Poisson convergence of centers, lifetimes, and deathtimes under sparsity conditions.

Abstract

In topological data analysis, the notions of persistent homology, birthtime, lifetime, and deathtime are used to assign and capture relevant cycles (i. e. , topological features) of a point cloud, such as loops and cavities. In particular, cycles with a large lifetime are of special interest. In this paper, we study such large-lifetime cycles when the point cloud is modeled as a Poisson point process. First, we consider the case with no bound on the deathtime, where we establish Poisson convergence of the centers of large-lifetime cycles on the 2-dimensional flat torus. Afterwards, by imposing a bound on the deathtime, we enter a sparse connectivity regime, and we prove joint Poisson convergence of the centers, lifetimes, and deathtimes in dimensions d 2 under suitable model conditions.

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Cite This Study

Hirsch et al. (2026) studied this question.

synapsesocial.com/papers/69a286490a974eb0d3c011f5https://doi.org/10.1007/s10687-026-00526-x
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