A parameterized quantum circuit with a penalty Hamiltonian is claimed to make quantum neural networks noise-resistant, with 98% classification accuracy under amplitude damping noise in simulation.
Quantum advantage in learning from experiments,
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Noise-resistant adaptive Hamiltonian learning
A parameterized quantum circuit with a penalty Hamiltonian is claimed to make quantum neural networks noise-resistant, with 98% classification accuracy under amplitude damping noise in simulation.