Department of Computer, Control and Management Engineering

This work reports the design of a 1x2 photonic digital switch controlled by an electrically induced metasurface, configurated by a rectangular array of points where the refractive index is locally changed through the application of an external bias. The device is simulated using the Beam Propagation Method (BPM) and Finite Difference Time Domain (FDTD) algorithms and the structure under evaluation is an amorphous silicon 1x2 multimode interference (MMI), joined to an arrayed Metal Oxide Semiconductor (MOS) structure Al/SiNx/a-Si:H/ITO to be used in active-matrix pixel fashion to control the output of the switch. MMI couplers, based on self-imaging multimode waveguides, are very compact integrated optical components that can perform many different splitting and recombining functions. The input–output model has been defined using a machine learning approach; a high number of images have been generated through simulations, based on the beam propagation algorithm, obtaining a large dataset for an MMI structure under different activation maps of the MOS pixels. This dataset has been used for training and testing of a machine learning algorithm for the classification of the MMI configuration in terms of binary digital output for a 1x2 switch. Also, a statistical analysis has been produced, targeting the definition of the most incident-activated pixel for each switch operation. An optimal configuration is proposed and applied to demonstrate the operation of a digital cascaded switch. This proof of concept paves the way to a more complex device class, supporting the recent advances in programmable photonic integrated circuits.