COVID-19 and QAOA

Abstract

We used a quantum annealer to to determine how to safely reopen college campuses via quarantining students. We also implemented the quantum approximate optimization algorithm on Qiskit and TensorFlow Quantum, and showed numerically that for level 1 QAOA similar parameters are optimal on Erdos-Reyni and regular graphs.

Result Presentation

https://qcb.berkeley.edu/pdf/covid.pdf

Optimization

A collection of iPython notebooks investigating quantum optimization. Related papers include:

• Solving the Graph Isomorphism Problem with a Quantum Annealer
• For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances