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About this paper
Rubén Darío Guerrero
A new framework leverages a four-player potential game to design parameterized quantum circuits, balancing trainability, classical simulation hardness, task performance, and hardware cost. This approach identifies Pareto-optimal circuit architectures, navigating the inherent trade-offs in variational quantum algorithms.
Key insights
- Modeling PQC design as a multi-player potential game allows explicit, fine-grained control over conflicting objectives such as trainability (via quantum Fisher information), non-stabilizerness (via stabilizer Rényi entropy), task performance, and hardware cost.
- The introduction of an ε-Nash certificate provides a robust stopping criterion, ensuring that the chosen PQC architecture represents a balanced equilibrium where no single objective can be significantly improved without detriment to others.
- The framework effectively navigates the "structural tension" between VQA trainability and classical simulability, enabling the discovery of Pareto-optimal circuits that reside in the desirable "interior" of this trade-off space.
Summary by alphaXiv.
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