A quantum analytical Adam descent through parameter shift rule using Qibo
Proceedings of 41st International Conference on High Energy physics — PoS(ICHEP2022)(2022)
摘要
In this proceedings we present quantum machine learning optimization experiments using stochastic gradient descent with the parameter shift rule algorithm. We first describe the gradient evaluation algorithm and its optimization procedure implemented using the Qibo framework. After numerically testing the implementation using quantum simulation on classical hardware, we perform successfully a full quantum hardware optimization exercise using a single superconducting qubit chip controlled by Qibo. We show results for a quantum regression model by comparing simulation to real hardware optimization.
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关键词
analytical adam descent,quantum,parameter shift rule
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