Application-level Benchmarking of Quantum Computers using Nonlocal Game Strategies

Journal Article · Thu Jul 31 04:00:00 EDT 2025 · Quantum Science and Technology

DOI:https://doi.org/10.1088/2058-9565/adf1c0· OSTI ID:2587042

Furches, James C.; Chehade, Sarah; Hamilton, Kathleen E.; Wiebe, Nathan O.; Ortiz Marrero, Carlos M.

In a nonlocal game, two noncommunicating players cooperate to convince a referee that they possess a strategy that does not violate the rules of the game. Quantum strategies allow players to optimally win some games by performing joint measurements on a shared entangled state, but computing these strategies can be challenging. We present a variational quantum algorithm to compute quantum strategies for nonlocal games by encoding the rules of a nonlocal game into a Hamiltonian. We show how this algorithm can generate a short-depth optimal quantum strategy for a graph coloring game with a quantum advantage. This quantum strategy is then evaluated on fourteen different quantum hardware platforms to demonstrate its utility as a benchmark. Finally, we discuss potential sources of errors that can explain the observed decreased performance of the executed task and derive an expression for the number of samples required to accurately estimate the win rate in the presence of noise.

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 2587042
• Report Number(s): PNNL-SA-208588
• Journal Information: Quantum Science and Technology, Journal Name: Quantum Science and Technology Journal Issue: 4 Vol. 10
• Country of Publication: United States
• Language: English

Related Subjects

quantum benchmarking
quantum computing
quantum machine learning
quantum algorithms