Continuation of Point Clouds via Persistence Diagrams
For researchers in topological data analysis, this provides a novel method to generate point clouds with desired topological features, addressing a previously unsolved inverse problem.
This paper introduces a differentiable persistence map enabling Newton-Raphson continuation to transform a point cloud so that its persistence diagram matches a target diagram, solving the inverse problem from persistence diagrams to point clouds.
In this paper, we present a mathematical and algorithmic framework for the continuation of point clouds by persistence diagrams. A key property used in the method is that the persistence map, which assigns a persistence diagram to a point cloud, is differentiable. This allows us to apply the Newton-Raphson continuation method in this setting. Given an original point cloud $P$, its persistence diagram $D$, and a target persistence diagram $D'$, we gradually move from $D$ to $D'$, by successively computing intermediate point clouds until we finally find a point cloud $P'$ having $D'$ as its persistence diagram. Our method can be applied to a wide variety of situations in topological data analysis where it is necessary to solve an inverse problem, from persistence diagrams to point cloud data.