New parameterized quantum gates design and efficient gradient solving based on variational quantum classification algorithm
Currently, variational quantum classification algorithms (VQCAs) generally rely on traditional optimization techniques such as Powell and SLSQP in the parameter optimization session.However, the performance of these methods shows limitations in practical applications.Although the parameter-shift rule can efficiently compute the parameter gradient w