Title:  Random Persistence Diagram Generator
Abstract:  We will present a random persistence diagram generator (RPDG) method that generates a sequence of random persistence diagrams from the ones produced by the data. RPDG is underpinned by a model based on pairwise interacting point processes and a reversible jump Markov chain Monte Carlo (RJ-MCMC) algorithm. A first example, which is based on a synthetic dataset, will demonstrate the efficacy of RPDG and provides a comparison with another method for sampling PDs. A second example will demonstrate the utility of RPDG to solve a materials science problem given a real dataset of small sample size.