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Evolving hardware-efficient grover circuits with grammatical evolution
Date
2026-07-10
Abstract
Canonical quantum algorithms often achieve low execution fidelities on current Noisy Intermediate-Scale Quantum (NISQ) hardware. The standard implementation of Grover's search algorithm, designed for theoretical generality, produces deep, gate-heavy circuits that are susceptible to noise. This paper challenges the "one-size-fits-all" design paradigm by using Grammatical Evolution (GE) to automatically discover hardware-efficient, state-specific quantum circuits. We demonstrate this approach by evolving bespoke circuits for all eight 3-qubit computational basis states and executing them on a 133-qubit IBM Heron quantum processor. To our knowledge, this is the first hardware-validated application of GE for this task. The results indicate significant performance gains: evolved circuits achieve hardware-executed fidelities up to 96.9% (vs. 66.3% baseline) while reducing circuit depth by 82.5–96.6% and gate count by 77.4–94.6% compared to canonical implementations. These findings suggest that automated symbolic search is a viable approach to designing algorithms that can execute on today's NISQ devices.
Supervisor
Description
Peer-reviewed
Publisher
Association for Computing Machinery
Citation
GECCO '26: Proceedings of the Genetic and Evolutionary Computation Conference
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Funding Information
Sustainable Development Goals
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License
Attribution 4.0 International