Persistent homology (PH) is an operation which, loosely speaking, describes the different holes in a point cloud via a collection of intervals called a barcode. The two most frequently used variants of persistent homology for point clouds are called Čech PH and Vietoris-Rips PH. How much information is lost when we apply these kinds of PH to a point cloud? We investigate this question by studying the subspace of point clouds with the same barcodes under these operations. We establish upper and lower bounds on the dimension of this space, and find that the question of when the persistence map is identifiable has close ties to rigidity theory. For example, we show that a generic point cloud being locally identifiable under Vietoris-Rips persistence is equivalent to a certain graph being rigid on the same point cloud.
