Simulating QAOA with Spin-Boson Systems
ORAL
Abstract
The Quantum Approximate Optimization Algorithm (QAOA) is a leading quantum heuristic for combinatorial optimization, with potential for quantum advantage on intermediate-term hardware. While QAOA guarantees optimal solutions at infinite depth, its behavior at large but finite depths pp is not well understood. We develop a mapping between evaluating average QAOA energies for spin-glass systems in the thermodynamic limit and simulating a related spin-boson system. Using this mapping, we provide evidence that QAOA efficiently solves the Sherrington-Kirkpatrick model in the average case, with simulations reaching depths up to p=160s. This approach generalizes to higher-order and mixed-order spin-glass models, enabling exploration of QAOA’s performance on challenging instances. Our results advance the understanding of QAOA in regimes relevant to intermediate-term quantum devices and offer a new framework for benchmarking QAOA on well-studied problems.
*This material is based upon work supported by the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers. This research used resources of the Argonne Leadership Computing Facility, a U.S. Department of Energy (DOE) Office of Science user facility at Argonne National Laboratory and is based on research supported by the U.S. DOE Office of Science-Advanced Scientific Computing Research Program, under Contract No. DE-AC02-06CH11357. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a Department of Energy Office of Science User Facility using NERSC award DDR-ERCAP0034098.
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Publication: https://arxiv.org/abs/2505.07929
Presenters
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Abid A Khan
- JPMorgan Chase