We propose an alternative approach to compensation of intermodal interactions in few-mode optical fibers by means of digital backpropagation.Instead of solving the inverse generalized multimode nonlinear Schr?dinger e...We propose an alternative approach to compensation of intermodal interactions in few-mode optical fibers by means of digital backpropagation.Instead of solving the inverse generalized multimode nonlinear Schr?dinger equation,we accomplish backpropagation of the multimode signals with help of their near-field intensity distributions captured by a camera.We demonstrate that this task can successfully be handled by a deep neural network and provide a proof of concept by training an autoencoder for backpropagation of six linearly polarized[LP]modes of a step-index fiber.展开更多
文摘We propose an alternative approach to compensation of intermodal interactions in few-mode optical fibers by means of digital backpropagation.Instead of solving the inverse generalized multimode nonlinear Schr?dinger equation,we accomplish backpropagation of the multimode signals with help of their near-field intensity distributions captured by a camera.We demonstrate that this task can successfully be handled by a deep neural network and provide a proof of concept by training an autoencoder for backpropagation of six linearly polarized[LP]modes of a step-index fiber.
