Design of superconducting optoelectronic networks for neuromorphic computing

Published: November 07, 2018


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


We have previously proposed a novel hardware platform for neuromorphic computing based on superconducting optoelectronics that presents many of the features necessary for information processing in the brain. Here we discuss the design and training of networks of neurons and synapses based on this technology. We present circuit models for the simplest neurons and synapses that we can use to build networks. We discuss the further abstracted integrate and fire model that we use for evolutionary optimization of small networks of these neurons. We show that we can use the TENNLab evolutionary optimization programming framework to design small networks for logic, control and classification tasks. We plan to use the results to feedback and inform our neuron design.
Proceedings Title: 2018 IEEE International Conference on Rebooting Computing
Conference Dates: November 7-9, 2018
Conference Location: Tysons, VA
Pub Type: Conferences


neuromorphic computing, integrated photonics, superconducting electronics
Created November 07, 2018, Updated July 09, 2019