基于神经网络的金刚石色心自动识别算法实现

Realization of automatic recognition algorithm of diamond color center based on neural network

文章研究了金刚石氮-空位(nitrogen-vacancy,NV)色心量子调控平台中的NV色心位置识别和检测。在目前的实验平台上,对于NV色心位置的辨别主要依赖实验人员以往的经验,再借助光探测磁共振(optically detected magnetic resonance,ODMR)实验来确认是否为NV色心。为了更精准地检测色心,文章把辨别金刚石NV色心作为目标检测问题来处理,对已有的基于神经网络的目标检测框架进行研究,并针对NV色心的识别问题进行改进,提出了基于卷积神经网络的金刚石NV色心自动识别框架。与人工识别相比,该框架具有识别准确率高、识别速度快、抗噪能力强等优势。

The recognition and detection of nitrogen-vacancy(NV)color center in the quantum control platform based on diamond NV color center are studied.On the current experimental platform,the identification of NV color center mainly depends on the previous experience of the experimenters,and then the optically detected magnetic resonance(ODMR)experiment is used to confirm whether it is NV color center.In order to detect color centers more accurately,this paper treats the identification of diamond NV color centers as the problem of target detection,studies the existing framework of target detection based on neural network,and improves the recognition of NV color centers.Then,a framework of automatic recognition of diamond NV color centers based on convolutional neural network is proposed.Compared with artificial recognition,the framework has the advantages of high recognition accuracy,fast recognition speed and strong anti-noise ability.