Superconducting Optoelectronic Neurons I: General Principles
This work addresses the problem of designing efficient neural hardware for cognitive systems, but it is incremental as it builds on existing principles without presenting new experimental results.
The paper tackles the design of neural hardware by proposing superconducting optoelectronic neurons that use optical signals for communication and superconducting detectors for energy efficiency, aiming to achieve spatial and temporal integration beneficial for cognitive processing.
The design of neural hardware is informed by the prominence of differentiated processing and information integration in cognitive systems. The central role of communication leads to the principal assumption of the hardware platform: signals between neurons should be optical to enable fanout and communication with minimal delay. The requirement of energy efficiency leads to the utilization of superconducting detectors to receive single-photon signals. We discuss the potential of superconducting optoelectronic hardware to achieve the spatial and temporal information integration advantageous for cognitive processing, and we consider physical scaling limits based on light-speed communication. We introduce the superconducting optoelectronic neurons and networks that are the subject of the subsequent papers in this series.