AI 中文总结
针对共封装光学应用中混合间距光栅耦合器设计复杂的问题，开发集成DNN模型的软件，依据用户给定参数自动设计，经训练测试，在波长和半高宽误差控制上效果良好，还开发GUI方便使用。
AI 中文摘要
在共封装光学（CPO）应用中，需要一种能耦合宽波长范围的混合间距光栅耦合器。然而，这种光栅耦合器的设计和优化很复杂。本文开发了集成深度神经网络（DNN）模型的软件，根据用户指定的峰值波长和半高宽（FWHM）值自动设计混合间距光栅耦合器。首先用10000行光栅参数-功率谱数据集训练DNN模型，功率谱用有限时域差分（FDTD）技术模拟。训练后用约1000种不同的峰值波长和FWHM值组合测试模型，在与用户指定和FDTD验证的光谱比较中，822次尝试误差<15%，351次尝试误差<5%；在比较用户指定和FDTD验证的峰值波长时，844次尝试的峰值波长绝对误差（AE）<2nm；对于FWHM，738次尝试的FWHM值AE<10nm。还开发了图形用户界面（GUI）方便软件使用。
英文摘要
A mixed-pitch grating coupler which can couple a wide range of wavelengths is preferred in its application in co-packaged optics (CPO). However, the design and optimization of such grating coupler is complex. In this work, we developed software with integrated deep neural network (DNN) model to automatically design the mixed-pitch grating coupler from user-specified peak wavelengths and full-width half-maximum (FWHM) values. We first trained the DNN model with 10,000 rows of grating parameters-power spectrum datasets, where the power spectrum was simulated using finite-difference time domain (FDTD) technique. Upon training, we tested the model using ~1,000 different combinations of peak wavelengths and FWHM values. Among the combinations, 822 attempts have <15% error, while 351 attempts have <5% error when comparing the user-specified and FDTD-verified spectrum. Meanwhile, comparing the user-specified and FDTD-verified peak wavelengths, 844 attempts have peak wavelengths with absolute error (AE) < 2 nm. For FWHMs, 738 attempts have FWHM values with AE < 10 nm. We have also developed a graphical-user interface (GUI) to ease the usage of this software.
