This presentation discusses new ways of designing nanophotonic devices using deep learning. I will present our efforts in developing generalized artificial neural network (ANN) approaches for evaluating 3D nanostructures in free space and integrated photonic circuits, taking into account complex interactions. New results on highly multi-objective, ANN-driven inverse design of complex scattering matrices in multimode silicon photonic waveguides is presented, which enable ultracompact routers and programmable switches for photonic AI and quantum chips.
Materials with switchable optical characteristics can enable new types of optical technology that can be tuned or reprogrammed after fabrication. Here, I will present recent results on controlling light on a chip using tunable and programmable materials. New perturbative concepts for altering the flow of light in silicon integrated photonic circuits were initially developed in our lab through ultrafast photomodulation of the silicon waveguide itself. Implementation of reprogrammable photonics using the perturbation approach are now made possible by integrating phase change materials onto the silicon photonics platform. In particular I will be presenting the first results on a new family of new low-loss phase change materials for reconfigurable nanophotonic devices.
A CMOS compatible three-dimensional (3D) integrated photonics circuit for multilayer silicon photonics is reported. Slopes with angles between 10o and 15° were created in the oxide layer using single step wet etching to connect the two Si waveguide layers. Amorphous Si (a-Si) deposited using hot wire chemical vapor deposition (HWCVD) at a temperature of 230°C was used to fabricate the device. Losses of 0.5 dB/slope were measured in the slope waveguides at 1310 nm wavelength. As a demonstration, we propose a 4x4 network switch using a-Si based vertical directional coupler.
Defining elements with reconfigurable input-output characteristics is of importance to achieve flexible circuitry where light can be manipulated and routed using external control signals. We have developed an experimental approach for shaping of the transmission function of multimode silicon photonic waveguides by projecting a pattern of local nonlinear perturbations induced by an ultrafast laser pulse. Making use of the degrees of freedom offered by a spatial light modulator, the technique offers a new approach for studying light transport, for controlling its flow on ultrafast time scale, and for programming functions on a photonic chip.
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