Selecting a customized Hermitian observable enables training of QNNs up to 10 qubits under noise for global cost functions, outperforming Pauli observables, while PauliZ works best for local cost functions up to 10 qubits.
Next- generation quantum neural networks: Enhancing efficiency, security, and privacy,
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HQNET: Harnessing Quantum Noise for Effective Training of Quantum Neural Networks in NISQ Era
Selecting a customized Hermitian observable enables training of QNNs up to 10 qubits under noise for global cost functions, outperforming Pauli observables, while PauliZ works best for local cost functions up to 10 qubits.