Skip to main content

NOTICE: Due to a lapse in annual appropriations, most of this website is not being updated. Learn more.

Form submissions will still be accepted but will not receive responses at this time. Sections of this site for programs using non-appropriated funds (such as NVLAP) or those that are excepted from the shutdown (such as CHIPS and NVD) will continue to be updated.

U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

SuperMind: A survey of the potential of superconducting electronics for neuromorphic computing

Published

Author(s)

Michael Schneider, Emily Toomey, Graham Rowlands, Jeff Shainline, Paul Tschirhart, Ken Segall

Abstract

Neuromorphic computing is a broad eld that uses biological inspiration to address computing design. It is being pursued in many hardware technologies both novel and conventional. Here we discuss the use of superconductive electronics for neuromorphic computing and several reasons why superconducting electronics is an interesting technology within which to design a neuromorphic computing system. For example, the natural spiking behavior in Josephson junctions and the ability to transmit short voltage spikes without the resistive capacitive time constants that typically hinder spike based computing. We will review the work that has been done on biologically inspired superconductive devices, circuits and architectures and also discuss the scaling potential of these demonstrations.
Citation
Superconductor Science and Technology
Volume
35
Issue
5

Keywords

Neuromorphic computing, superconducting electronics, Josephson junctions

Citation

Schneider, M. , Toomey, E. , Rowlands, G. , Shainline, J. , Tschirhart, P. and Segall, K. (2022), SuperMind: A survey of the potential of superconducting electronics for neuromorphic computing, Superconductor Science and Technology, [online], https://doi.org/10.1088/1361-6668/ac4cd2, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=932644 (Accessed October 20, 2025)

Issues

If you have any questions about this publication or are having problems accessing it, please contact [email protected].

Created March 30, 2022, Updated June 8, 2023
Was this page helpful?