The Royal Institution for the Advancement of Learning/McGill University

Published purpose

The HTSN program aims to develop innovative technologies to deliver extreme broadband services across Canada. Photonics for core network and satellite communications are among the main themes to be addressed. With the advent of 5G and IoT, the data capacity demands are expected to increase dramatically. New system architectures and components supporting them are required. Increasing data capacity while reducing component footprint and reducing power consumption are among the critical challenges. The key high-level objective of this project is to leverage artificial intelligence (AI) and machine learning (ML) techniques to develop silicon photonics components for signal multiplexing. The McGill team will apply and further develop the new ML design strategy of dimensionality reduction pioneered at NRC to tackle the complexity of high-dimensional design optimization and inverse design approach. This will enable efficient exploitation of the unique properties of subwavelength-structured dielectric metamaterials and complex device geometries required for next generation photonic datacom devices. The team will then demonstrate the novel designs at the components and the system level.