We present three different approaches to apply deep learning to inverse design for nanophotonic devices. The forward models use device parameters as inputs and device responses as outputs. This model works as a fast approximation method which can be integrated in the optimization loop, and can accelerate the optimization. The network is updated as we obtain more simulation data on the fly for better approximation. The inverse modeling uses a network trained with the device responses as inputs, and the device parameters as outputs. This way the network outputs the device structure given the target optical response. This network can also be updated as we obtain more data during the optimization and validation. The generative model we use is a variant of a conditional variational autoencoder, and the network learns the statistical characteristics of the device structure, and it generates a series of improved designs given the target device responses. By using these three models, we demonstrate how to design nanophotonic power splitters with multiple splitting ratios.
We present the design strategy of shallow-angle grating couplers for vertical emission from InP devices, and then discuss the focusing effect of a 2D grating. Measured beam shapes from prototyped devices agree well with the simulation results.
We review the recent advancement in the system and device technologies for coherent optical communications. One major topic is high-dimensional modulation, and in particular the nonlinearity-tolerant modulation format family, based on four-dimensional 2A8PSK. This family, covering 5, 6, 7 bits/4D symbol, outperforms most known corresponding modulation formats in the linear and nonlinear region. We also review our recent progress on forward error correction including polar codes, and monolithic narrow linewidth semiconductor lasers.
Recent research in multidimensional modulation has shown great promise in long reach applications. In this work, we will investigate the origins of this gain, the different approaches to multidimensional constellation design, and different performance metrics for coded modulation. We will also discuss the reason that such coded modulation schemes seem to have limited application at shorter distances, and the potential for other coded modulation schemes in future transmission systems.