Cryogenic system for the exploration of low-temperature neuromorphic photonic systems

点击翻译按钮获取中文摘要

This NSERC-RTI proposal will support the building of a cryogenic neuromorphic photonics platform-perhaps the first in Canada-through the purchase of a cryogenic system. Our work on neuromorphic photonics (Shastri et al. Nature Photonics 15, 2021) uses principles of optical physics to mimic neurons and synapses (neuron-to neuron connections) in the brain to create photonic neural networks (i.e., chips powered by light) that are orders of magnitude faster than electronic processors. We have been extending this work to build low-temperature photonic neural networks interfaced with quantum technologies to enable applications in quantum photonic machine learning and real-time quantum state tomography. The physical hybridization of machine learning and quantum information stands to advance in both fields-quantum for machine learning, and machine learning for quantum. This proposal requests funding for the purchase of a cryogenic system that includes a cryostat, a sorption fridge, temperature controllers and sensors, a water-cooled helium compressor, and a vacuum pumping system. This cryosystem will allow us to interface our silicon photonic neural networks with single-photon quantum gates with single photon sources and superconducting nanowire single-photon detectors (SNSPDs). We are investigating quantum information processing to improve machine learning algorithms implemented with photonic neural networks by designing a hardware interface between neuromorphic processors and quantum gates enabling hybrid quantum-classical neural network on a single silicon photonic chip. Conversely, we are investigating machine learning with photonic neural networks for the real-time control of quantum devices. In collaboration with Rotenberg Group (Queen's), we are hardwiring an interface between a photonic neural circuit and single photon sources, that will enable processing and control of the fragile quantum optical states, that underlie all quantum photonic technologies, in real-time. The cryosystem will support the experimental work of 15 HQP/year across nanophotonics, machine learning, and quantum information processing. In 2019, the global AI and quantum computing markets were valued at $39.9B and $507.1M, respectively. If these fields merge, their overall market value could be greater than the sum of their parts. HQP working at the intersection of this field will be uniquely positioned to tap into the combined technology market by creating start-ups or become leading academics in this field.