Quantum topological data analysis with continuous variables

Abstract

I introduce a continuous-variable quantum topological data algorithm. The goal of the quantum algorithm is to calculate the Betti numbers in persistent homology which are the dimensions of the kernel of the combinatorial Laplacian. I accomplish this task with the use of qRAM to create an oracle which organizes sets of data. I then perform a continuous-variable phase estimation on a Dirac operator to get a probability distribution with eigenvalue peaks. The results also leverage an implementation of continuous-variable conditional swap gate.

7 pages, 5 figures

Cited by in corpus (4)

• Quantum Imaginary Time Evolution Algorithm for Quantum Field Theories with Continuous Variables
• Computing Wasserstein Distance for Persistence Diagrams on a Quantum Computer
• Quantum Persistent Homology for Time Series
• Quantum-Enhanced Topological Data Analysis: A Peep from an Implementation Perspective