Sampling frequency thresholds for the quantum advantage of the quantum approximate optimization algorithm

Sampling frequency thresholds for the quantum advantage of the quantum approximate optimization algorithm

Abstract We compare the performance of the Quantum Approximate Optimization Algorithm (QAOA) with state-of-the-art classical solvers Gurobi and MQLib to solve the MaxCut problem on 3-regular graphs. We identify the minimum noiseless sampling frequency and depth p required for a quantum device to out...

Full description

Bibliographic Details
Main Authors: Danylo Lykov, Jonathan Wurtz, Cody Poole, Mark Saffman, Tom Noel, Yuri Alexeev
Format: Article
Language:English
Published: Nature Portfolio 2023-07-01
Series:npj Quantum Information
Online Access:https://doi.org/10.1038/s41534-023-00718-4

Internet

https://doi.org/10.1038/s41534-023-00718-4

Similar Items