A Distributed Learning Scheme for Variational Quantum Algorithms

A Distributed Learning Scheme for Variational Quantum Algorithms

Variational quantum algorithms (VQAs) are prime contenders to gain computational advantages over classical algorithms using near-term quantum machines. As such, many endeavors have been made to accelerate the optimization of modern VQAs in past years. To further improve the capability of VQAs, here,...

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Bibliographic Details
Main Authors: Yuxuan Du, Yang Qian, Xingyao Wu, Dacheng Tao
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Transactions on Quantum Engineering
Subjects:
Distributed optimization
quantum computing
quantum Hamiltonians
quantum machine learning
Online Access:https://ieeexplore.ieee.org/document/9775600/

Internet

https://ieeexplore.ieee.org/document/9775600/

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