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quant-ph2023
Random coordinate descent: a simple alternative for optimizing parameterized quantum circuits
Zhiyan Ding, Taehee Ko, Jiahao Yao +2
Variational quantum algorithms rely on the optimization of parameterized quantum circuits in noisy settings. The commonly used back-propagation procedure in classical machine learn…
quant-ph2020
Reinforcement Learning for Many-Body Ground-State Preparation Inspired by Counterdiabatic Driving
Jiahao Yao, Lin Lin, Marin Bukov
The quantum alternating operator ansatz (QAOA) is a prominent example of variational quantum algorithms. We propose a generalized QAOA called CD-QAOA, which is inspired by the coun…
quant-ph2020
Policy Gradient based Quantum Approximate Optimization Algorithm
Jiahao Yao, Marin Bukov, Lin Lin
The quantum approximate optimization algorithm (QAOA), as a hybrid quantum/classical algorithm, has received much interest recently. QAOA can also be viewed as a variational ansatz…