Dendritic Learning in Superconducting Optoelectronic Networks - Elastic Weight Collision at Dynamical Boundaries and Intermittent Validation for Early Convergence

Published

August 28, 2023

Author(s)

Ryan O'Loughlin, Bryce Primavera, Jeff Shainline

Abstract

Superconducting Optoelectronic Networks (SOENs) combine pho- tonics and superconductors to instantiate computing systems that approach the fundamental limits of information processing in terms of speed and scalability. Overcoming the engineering challenges of integrating these technologies into one system has consistently been aided by using neuro-inspired architectures. SOENs are na- tively Spiking Neural Networks (SNNs) of loop neurons, which themselves are comprised of many subsequent dendrites organized into intricate morphologies. Therefore, SOENs at scale may em- body highly complex superstructures that demand commensurate learning methods. To that end, we here propose a simple activity- based update rule (the arbor-update) for dendritic learning that is found to successfully classify nine-pixel images with a single neuron. We test two amendments to the arbor-update on a winner- take-all (WTA) mutually inhibitory three-neuron network. Both elastic weight collision with dynamical boundaries and intermittent validation are found to improve convergence time and conditions. The arbor-update and its variants are scalable with SOENs and may even map to other systems. Importantly, all proposed learn- ing methods are expected to be entirely implementable for on-chip learning in SOENs.

Proceedings Title

ICONS '23: Proceedings of the International Conference on Neuromorphic Systems 2023

Conference Dates

August 1-3, 2023

Conference Location

Santa Fe, NM, US

Conference Title

International Conference for Neuromorphic Systems

Pub Type

Conferences

Keywords

Neuromorphic, Neuro-Inspired, Hardware, Algorithms, Dendritic Processing, Plasticity, Superconducting Optoelectronic Networks

Citation

O'Loughlin, R. , Primavera, B. and Shainline, J. (2023), Dendritic Learning in Superconducting Optoelectronic Networks - Elastic Weight Collision at Dynamical Boundaries and Intermittent Validation for Early Convergence, ICONS '23: Proceedings of the International Conference on Neuromorphic Systems 2023, Santa Fe, NM, US (Accessed October 7, 2025)