David L. Millman

Brittany Terese Fasy, Samuel Micka, David L. Millman et al.

The persistent homology transform (PHT) represents a shape with a multiset of persistence diagrams parameterized by the sphere of directions in the ambient space. In this work, we describe a finite set of diagrams that discretize the PHT such that it faithfully represents the underlying shape. We provide a discretization that is exponential in the dimension of the shape. Moreover, we show that this discretization is stable with respect to various perturbations and we provide an algorithm for computing the discretization. Our approach relies only on knowing the heights and dimensions of topological events, which means that it can be adapted to provide discretizations of other dimension-returning topological transforms, including the Betti function transform. With mild alterations, we also adapt our methods to faithfully discretize the Euler characteristic function transform.

Brittany Terese Fasy, David L. Millman, Anna Schenfisch

Recent developments in shape reconstruction and comparison call for the use of many different (topological) descriptor types, such as persistence diagrams and Euler characteristic functions. We establish a framework to quantitatively compare the strength of different descriptor types, setting up a theory that allows for future comparisons and analysis of descriptor types and that can inform choices made in applications. We use this framework to partially order a set of six common descriptor types. We then give lower bounds on the size of sets of descriptors that uniquely correspond to simplicial complexes, giving insight into the advantages of using verbose rather than concise topological descriptors.

Jacob Sriraman, Eli Barton, Brittany Terese Fasy et al.

We consider the parametric shortest paths problem in a linearly interpolated graph. Given two positively-weighted directed graphs $G_0=(V,E,ω_0)$ and $G_1=(V,E,ω_1),$ the linearly interpolated graph is the family of graphs $(1-λ)G_0+λG_1$, parameterized by $λ\in [0,1]$. The problem is to compute all distinct parametric shortest paths. We compute a data structure in $Θ(k|E|\log |V|)$ time, where~$k$ is the number of distinct parametric shortest paths over all~$λ\in [0,1]$ that exist for a nontrivial interval of parameters, each corresponding to a linear function in a maximal sub-interval of $[0,1]$. Using this data structure, a shortest path query takes~$Θ(\log k)$ time.