Implementation of new superconducting neural circuits using coupled SQUIDs

Yoshinao Mizugaki; Koji Nakajima; Yasuji Sawada; Tsutomu Yamashita

doi:10.1109/77.273058

Implementation of new superconducting neural circuits using coupled SQUIDs

Yoshinao Mizugaki, Koji Nakajima, Yasuji Sawada, Tsutomu Yamashita

Tohoku University

Research output: Contribution to journal › Article › peer-review

29 Citations (Scopus)

Abstract

A novel superconducting neuron circuit and two types of variable synapses, which are based on superconducting quantum interferometer devices (SQUIDs), are presented. A neuron circuit with good input-output isolation and steep threshold characteristics is accomplished using a combination of a single-junction SQUID coupled to a double-junction SQUID. The quantum state of the single-junction SQUID represents the neuron state, and the output voltage of the double-junction SQUID, which is operated in a nonlatching mode with shunt resistors, is a sigmoid-shaped function of the input. Both variable synapse circuits are composed of multiple shunted double-junction SQUIDs. The first type changes its conductance value by using both superconducting and voltage states. The second variable synapse circuit changes its output current digitally by switching its bias currents. Besides numerical simulations of the circuit characteristics, we have fabricated superconducting neural chips in a Nb/AlO_x/Nb Josephson junction technology. The fundamental operation of each element and a 2-bit neural-based A/D converter have been successfully tested. A learning system with a variable synapse is also discussed.

Original language	English
Pages (from-to)	1-8
Number of pages	8
Journal	IEEE Transactions on Applied Superconductivity
Volume	4
Issue number	1
DOIs	https://doi.org/10.1109/77.273058
Publication status	Published - 1994 Mar

ASJC Scopus subject areas

Electrical and Electronic Engineering
Physics and Astronomy (miscellaneous)

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title = "Implementation of new superconducting neural circuits using coupled SQUIDs",

abstract = "A novel superconducting neuron circuit and two types of variable synapses, which are based on superconducting quantum interferometer devices (SQUIDs), are presented. A neuron circuit with good input-output isolation and steep threshold characteristics is accomplished using a combination of a single-junction SQUID coupled to a double-junction SQUID. The quantum state of the single-junction SQUID represents the neuron state, and the output voltage of the double-junction SQUID, which is operated in a nonlatching mode with shunt resistors, is a sigmoid-shaped function of the input. Both variable synapse circuits are composed of multiple shunted double-junction SQUIDs. The first type changes its conductance value by using both superconducting and voltage states. The second variable synapse circuit changes its output current digitally by switching its bias currents. Besides numerical simulations of the circuit characteristics, we have fabricated superconducting neural chips in a Nb/AlOx/Nb Josephson junction technology. The fundamental operation of each element and a 2-bit neural-based A/D converter have been successfully tested. A learning system with a variable synapse is also discussed.",

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N2 - A novel superconducting neuron circuit and two types of variable synapses, which are based on superconducting quantum interferometer devices (SQUIDs), are presented. A neuron circuit with good input-output isolation and steep threshold characteristics is accomplished using a combination of a single-junction SQUID coupled to a double-junction SQUID. The quantum state of the single-junction SQUID represents the neuron state, and the output voltage of the double-junction SQUID, which is operated in a nonlatching mode with shunt resistors, is a sigmoid-shaped function of the input. Both variable synapse circuits are composed of multiple shunted double-junction SQUIDs. The first type changes its conductance value by using both superconducting and voltage states. The second variable synapse circuit changes its output current digitally by switching its bias currents. Besides numerical simulations of the circuit characteristics, we have fabricated superconducting neural chips in a Nb/AlOx/Nb Josephson junction technology. The fundamental operation of each element and a 2-bit neural-based A/D converter have been successfully tested. A learning system with a variable synapse is also discussed.

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Implementation of new superconducting neural circuits using coupled SQUIDs

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