论文标题
机器学习辅助操作和分子旋转量子的读数
Machine Learning-Assisted Manipulation and Readout of Molecular Spin Qubits
论文作者
论文摘要
机器学习在量子控制和读数中找到应用程序。在这项工作中，我们应用人工神经网络来协助对旨在测试幅度和相位识别的两个实验中的原型分子旋转量子置量置量和读数。我们首先成功使用人工网络来分析具有四个输入脉冲的存储/检索协议的输出，以识别回声位置，并在结果上进行进一步的选择，以推断初始输入脉冲序列。然后，我们应用人工神经网络来确定实验测量的Hahn Echo的相位，表明可以正确检测其相位并识别操作过程中添加的其他单脉冲相移。
Machine Learning finds application in the quantum control and readout of qubits. In this work we apply Artificial Neural Networks to assist the manipulation and the readout of a prototypical molecular spin qubit - an Oxovanadium(IV) moiety - in two experiments designed to test the amplitude and the phase recognition, respectively. We first successfully use an artificial network to analyze the output of a Storage/Retrieval protocol with four input pulses to recognize the echo positions and, with further post selection on the results, to infer the initial input pulse sequence. We then apply an Artificial Neural Network to ascertain the phase of the experimentally measured Hahn echo, showing that it is possible to correctly detect its phase and to recognize additional single-pulse phase shifts added during manipulation.
