DocumentCode :
1409531
Title :
Superconducting Neural Network for Solving a Combinatorial Optimization Problem
Author :
Onomi, Takeshi ; Maenami, Yusuke ; Nakajima, Koji
Author_Institution :
Lab. for Brainware Syst./Nanoelectronis & Spintronics, Tohoku Univ., Sendai, Japan
Volume :
21
Issue :
3
fYear :
2011
fDate :
6/1/2011 12:00:00 AM
Firstpage :
701
Lastpage :
704
Abstract :
We propose a neural network using coupled-SQUIDs to solve the N-Queens problem, a combinatorial optimization problem. The N-Queen problem consists of placing N queens on an N × N chess board such that none of the queens are able to capture any other using standard chess moves for a queen. We run a numerical simulation to show that a network consisting of a combination of coupled-SQUIDs can arrive at the solution. However, conditions of the network may be trapped in incorrect answers due to the existence of local minima on the energy function of the network. The Josephson voltage oscillation effect is effective for escaping from such conditions due to the existence of local minima. We investigate network dynamics and discuss the performance of the network on the basis of the parameters of the Nb integration circuit.
Keywords :
Josephson effect; SQUIDs; combinatorial mathematics; neural nets; numerical analysis; optimisation; superconducting integrated circuits; Josephson voltage oscillation effect; N-queens problem; combinatorial optimization problem; coupled-SQUIDs; network dynamics; numerical simulation; superconducting integrated circuits; superconducting neural network; Artificial neural networks; Neurons; Noise; Oscillators; SQUIDs; Superconducting integrated circuits; Thermal noise; Combinatorial optimization; N-Queens problem; neural networks; superconducting integrated circuits;
fLanguage :
English
Journal_Title :
Applied Superconductivity, IEEE Transactions on
Publisher :
ieee
ISSN :
1051-8223
Type :
jour
DOI :
10.1109/TASC.2010.2092397
Filename :
5672805
Link To Document :
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