Quantum ansatz design is cast as a four-player potential game optimizing trainability, non-stabilizerness, performance, and cost, with Nash search outperforming baselines on 4-qubit MaxCut and LiH tasks.
Kandalaet al., Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets, Nature549, 242 (2017)
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Graph neural networks that incorporate local hardware noise parameters as graph features enable quantum error mitigation with better scalability and lower error than traditional global regression methods on 10-16 qubit circuits.
citing papers explorer
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A four-player potential game for barren-plateau-aware quantum ansatz design
Quantum ansatz design is cast as a four-player potential game optimizing trainability, non-stabilizerness, performance, and cost, with Nash search outperforming baselines on 4-qubit MaxCut and LiH tasks.
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Scalable Quantum Error Mitigation with Physically Informed Graph Neural Networks
Graph neural networks that incorporate local hardware noise parameters as graph features enable quantum error mitigation with better scalability and lower error than traditional global regression methods on 10-16 qubit circuits.