On the asymptotic normality of persistent Betti numbers
Persistent Betti numbers are a major tool in persistent homology, a subfield of topological data analysis. Many tools in persistent homology rely on the properties of persistent Betti numbers considered as a two dimensional stochastic process (r,s) \mapsto n^ 1/2} \beta^{r,s}_q \mathcal{K}(n^{1/d} S_n) \mathbb{E}\beta^{r,s}_q \mathcal{K} n^{1/d} S_n) So far, pointwise limit theorems have been established in different set ups. In particular, the pointwise asymptotic normality of (persistent) Betti numbers has been established for stationary Poisson processes and binomial processes with constant intensity function in the so called critical (or thermodynamic) regime, see Yogeshwaran et al. [2017] and Hiraoka et al. [2018] In this contribution, we derive a strong stabilizing property (in the spirit of Penrose and Yukich [2001] of persistent Betti numbers and generalize the existing results on the asymptotic normality to the multivariate case and to a broader class of underlying Poisson and binomial processes. Most importantly, we show that the multivariate asymptotic normality holds for all pairs (r,s) $0\le r\le s<\infty$ and that it is not affected by percolation effects in the underlying random geometric graph.