论文标题
使用QIBO通过参数偏移规则的量子分析亚当下降
A quantum analytical Adam descent through parameter shift rule using Qibo
论文作者
论文摘要
在此程序中，我们使用与参数移位规则算法的随机梯度下降提出了量子机学习优化实验。我们首先描述了使用QIBO框架实施的梯度评估算法及其优化过程。在使用经典硬件上使用量子模拟对实现进行数值测试之后，我们使用由QIBO控制的单个超导量子芯片成功执行了完整的量子硬件优化练习。我们通过将仿真与实际硬件优化进行比较来显示量子回归模型的结果。
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.
