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.
Adaptive pruning-based optimization of parameterized quantum circuits,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
extension 1
citation-polarity summary
fields
quant-ph 1years
2025 1verdicts
REJECT 1roles
extension 1polarities
extend 1representative citing papers
citing papers explorer
-
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.