Design of a low-crosstalk half-wavelength pitch nano-structured silicon waveguide array.

An ultra-compact half-wavelength pitch silicon waveguide array with very low crosstalk is proposed and analyzed in this work. We first show the design of a pair of low-crosstalk silicon waveguides with only half-wavelength spacing, where the placement of two thin silicon strips asymmetrically in between the waveguides is key to having very low crosstalk. We next extend this nano-structured two-waveguide design to form a low-crosstalk half-wavelength pitch silicon waveguide array.

High performance ultra-compact SOI waveguide crossing.

Waveguide crossing is an important integrated photonic component that will be routinely used for high-density and large-scale photonic integrated circuits, such as optical switches and routers. Several techniques have been reported in achieving high performance waveguide crossings on a silicon-on-insulator photonic platform, i.e.

Analyzing modal power in multi-mode waveguide via machine learning.

A machine learning assisted modal power analyzing scheme designed for optical modes in integrated multi-mode waveguides is proposed and studied in this work. Convolutional neural networks (CNNs) are successfully trained to correlate the far-field diffraction intensity patterns of a superposition of multiple waveguide modes with its modal power distribution. In particular, a specialized CNN is trained to analyze thin optical waveguides, which are single-moded along one axis and multi-moded along the other axis.