3-Port beam splitter of arbitrary power ratio enabled by deep learning on a multimode waveguide

A 3-port beam splitter with arbitrary power ratio is developed on a multimode waveguide by effectively manipulating the multimode interference through 4 locally placed microheaters. For matched interference, different light powers are coupled to the three output waveguides but the sum does not undergo extra loss, whereas the splitter integrates also the variable attenuation function, from zero to maximum, to any of the outputs. Different from the conventional design approach using extensive simulations, an equivalent neural network is established to represent such a multimode waveguide system based on experimental data only. From this neural network, an optimization program is developed to inverse the output and input. For a target power splitting ratio, the required heater currents can be readily calculated on a computer and then loaded onto the waveguide chip. The experimental results match well with the targets. This work demonstrates that the nonlinear activation is inherently integrated in the thermally controlled multimode waveguide though the optical material itself is linear. This feature can be used to construct complex deep learning networks. It may lead to the development of advanced integrated optical switches and computing networks.