Quantum algorithms for topological and geometric analysis of data

Abstract

Persistent homology allows identification of topological features in data sets, allowing the efficient extraction of useful information. Here, the authors propose a quantum machine learning algorithm that provides an exponential speed up over known algorithms for topological data analysis.