论文标题
基于Resnet 152体系结构的机器学习模型对非线性光学衍射模式的研究
Study of nonlinear optical diffraction patterns using machine learning models based on ResNet 152 architecture
论文作者
论文摘要
随着人工智能和非线性光学领域的进步继续使用新方法来更好地描述和确定非线性光学现象。在这项研究中，我们旨在分析有机材料的衍射模式，并通过利用RESNET 152在激光功率区域的卷积神经网络结构来确定所讨论材料的非线性折射指数，即衍射环无法明确区分。这种方法可以在不适用传统方法的情况下为光学材料表征打开新的景点。
As the advancements in the field of artificial intelligence and nonlinear optics continues new methods can be used to better describe and determine nonlinear optical phenomena. In this research we aimed to analyze the diffraction patterns of an organic material and determine the nonlinear refraction index of the material in question by utilizing ResNet 152 convolutional neural network architecture in the regions of laser power that the diffraction rings are not clearly distinguishable. This approach can open new sights for optical material characterization in situations where the conventional methods do not apply.
