This study explores the implementation of the Quantum Approximate Optimisation Algorithm (QAOA) in its analog form using a neutral atom quantum processing unit to solve the Maximum Independent Set problem. Our QAOA protocol leverages the natural encoding of problem Hamiltonians by Rydberg atom interactions, while employing Bayesian Optimisation to navigate the quantum-classical parameter space effectively under the constraints of hardware noise and resource limitations. We evaluate the approach through a combination of numerical simulations and experimental runs on Pasqal's first commercial quantum processing unit, Orion Alpha, demonstrating effective parameter optimisation and noise mitigation strategies, such as selective bitstring discarding and detection error corrections. Results show that a limited number of measurements still allows for a quick convergence to a solution, making it a viable solution for resource-efficient scenarios.

Tibaldi, S., Leclerc, L., Vodola, D., Tignone, E., Ercolessi, E. (2026). Analog QAOA with Bayesian optimisation on a neutral atom QPU. EPJ QUANTUM TECHNOLOGY, 13(1), 1-18 [10.1140/epjqt/s40507-025-00437-z].

Analog QAOA with Bayesian optimisation on a neutral atom QPU

Tibaldi S.
;
Ercolessi E.
2026

Abstract

This study explores the implementation of the Quantum Approximate Optimisation Algorithm (QAOA) in its analog form using a neutral atom quantum processing unit to solve the Maximum Independent Set problem. Our QAOA protocol leverages the natural encoding of problem Hamiltonians by Rydberg atom interactions, while employing Bayesian Optimisation to navigate the quantum-classical parameter space effectively under the constraints of hardware noise and resource limitations. We evaluate the approach through a combination of numerical simulations and experimental runs on Pasqal's first commercial quantum processing unit, Orion Alpha, demonstrating effective parameter optimisation and noise mitigation strategies, such as selective bitstring discarding and detection error corrections. Results show that a limited number of measurements still allows for a quick convergence to a solution, making it a viable solution for resource-efficient scenarios.
2026
Tibaldi, S., Leclerc, L., Vodola, D., Tignone, E., Ercolessi, E. (2026). Analog QAOA with Bayesian optimisation on a neutral atom QPU. EPJ QUANTUM TECHNOLOGY, 13(1), 1-18 [10.1140/epjqt/s40507-025-00437-z].
Tibaldi, S.; Leclerc, L.; Vodola, D.; Tignone, E.; Ercolessi, E.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/1047773
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