Benchmarking the recursive quantum approximate optimization algorithm

Paige Frederick; Rich Rines; F. T. Chong; Pranav Gokhale

doi:10.1117/12.2648434

8 March 2023 Benchmarking the recursive quantum approximate optimization algorithm

Paige Frederick, Rich Rines, F. T. Chong, Pranav Gokhale

Proceedings Volume 12446, Quantum Computing, Communication, and Simulation III; 1244609 (2023) https://doi.org/10.1117/12.2648434
Event: SPIE Quantum West, 2023, San Francisco, California, United States

Abstract

Recent results on the Quantum Approximate Optimization Algorithm (QAOA) have cast pessimism on its potential to exhibit practical quantum speedups. For instance, QAOA’s locality limits its performance on tasks such as coloring bipartite graphs—which is easy for classical methods. Motivated by these limitations, the Recursive QAOA was introduced to overcome the locality and symmetry of QAOA. Despite being more powerful than QAOA, RQAOA is fully classically simulable at level-1 depth (p = 1). We report results on RQAOA in this classically simulable regime, benchmarked on random Quantum Unconstrainted Binary Optimization (QUBO) problems with up to 100 variables. We find that RQAOA generally matches the performance of classical simulated annealing and significantly outperforms ordinary QAOA.

Conference Presentation

Citation Download Citation

Paige Frederick, Rich Rines, F. T. Chong, and Pranav Gokhale "Benchmarking the recursive quantum approximate optimization algorithm", Proc. SPIE 12446, Quantum Computing, Communication, and Simulation III, 1244609 (8 March 2023); https://doi.org/10.1117/12.2648434

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available