Artificial Intelligence (AI) Mode-Space Optical/Quantum Processor Design for Energy-Autonomous AI Applications

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Over the last six years, Dr. Liboiron-Ladouceur discovered and demonstrated how optical modes lead to higher throughput systems, thanks to technology advancements in silicon photonics (SiPh) integrated circuits. Recently, Dr. Liboiron-Ladouceur uncovered powerful design approaches referred as inverse design by developing AI-based algorithms towards more performing and compact devices. The research outcomes reveal how we can surpass conventional design methodology currently relying on human experience and intuition. In parallel, Dr. Liboiron-Ladouceur has recently developed an optical processor for computation enabling mathematical transformation of vectors and matrices. This research outcome reveals the inherent properties of photons for processing and computing data beyond their transmission capabilities in low-loss optical channels. Optical computation can lead to better energy efficiency and be accelerators in modern computer architectures. The initial work demonstrates good prediction accuracy in a practical framework accounting for fabrication and energy usage. However, increasing the optical processor size to the required vector dimensions remains an important challenge. Indeed, the processor sizes needed, such as in autonomous AI applications, are greater by one to two orders of magnitude than what is achievable through conventionally designed photonic integrated circuits. The research objectives of the proposed discovery program investigate optical modes to increase the size of optical processors exploiting recent design methodology in photonic integrated circuits. Mode division multiplexing view modes as orthogonal data channels mainly for transmission purpose. In the discovery program, scaling the vector size from tens to hundreds of elements leverages Dr. Liboiron-Ladouceur's significant contributions in SiPh mode-based device development. Her research methodology exploits machine learning algorithms in new inverse design techniques to develop the required devices manipulating photons for computation. These techniques will allow to reduce the device area from tens of microns to a few microns while maintaining the required performance in terms of insertion loss, crosstalk, and robustness to process variations. The benefits of the proposed research program are excellent with important impact from inverse design techniques leading to a paradigm shift in photonic integrated circuits. The feasibility of a mode-space optical processor will lead to energy-efficient computing platforms for AI applications in autonomous vehicles. The proposed discovery program allows for a multidisciplinary, inclusive, and diverse HQP training platform. Students will gain valuable research skills through industry-approved simulation tools and experimental methodologies, while developing their creative and critical mindset as future world leaders.