A GNN policy trained on spin-chain simulations learns to select operators for ADAPT-VQE and functions as an effective shortlist generator on small molecular benchmarks.
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Noise in present quantum hardware prevents reliable VQE molecular energy estimation for benzene despite Hamiltonian simplifications and optimizer tweaks, requiring substantially lower noise for future utility.
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Graph Neural Networks for Fast Operator Selection in Adaptive VQE
A GNN policy trained on spin-chain simulations learns to select operators for ADAPT-VQE and functions as an effective shortlist generator on small molecular benchmarks.
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Limitations of Quantum Hardware for Molecular Energy Estimation Using VQE
Noise in present quantum hardware prevents reliable VQE molecular energy estimation for benzene despite Hamiltonian simplifications and optimizer tweaks, requiring substantially lower noise for future utility.