New parameterized quantum gates design and efficient gradient solving based on variational quantum classification algorithm

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 r...

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Bibliographic Details
Main Authors: Xiaodong Ding, FuDong Liu, Weilong Wang, Yu Zhu, Yifan Hou, Yizhen Huang, Jinchen Xu, Zheng Shan
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Machine Learning: Science and Technology
Subjects:
VQCAs
parameters optimization
PQGs
quantum–classical hybrid algorithms
Online Access:https://doi.org/10.1088/2632-2153/ada0a4
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https://doi.org/10.1088/2632-2153/ada0a4

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