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Superconducting optoelectronic networks I: general principles



Jeffrey M. Shainline, Sonia M. Buckley, Adam N. McCaughan, Jeffrey T. Chiles, Richard P. Mirin, Sae Woo Nam


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 power law spatial and temporal distributions advantageous for cognitive processing and we consider physical scaling limits based on light-speed communication. We introduce the superconducting optoelectronic neurons and networks which are the subject of the subsequent papers in this series.
Physical Review Applied


neural computing, superconductors, integrated photonics, cognition
Created April 6, 2018, Updated February 25, 2020