Artificial Neural Network based on SQUIDs: demonstration of network training and operation

Abstract

We propose a scheme for the realization of artificial neural networks based on Superconducting Quantum Interference Devices (SQUIDs). In order to demonstrate the operation of this scheme we designed and successfully tested a small network that implements a XOR gate and is trained by means of examples. The proposed scheme can be particularly convenient as support for superconducting applications such as detectors for astrophysics, high energy experiments, medicine imaging and so on.

10 pages, 6 figures

References in corpus (3)

• Demonstration of Two-Qubit Algorithms with a Superconducting Quantum Processor
• Realization of Three-Qubit Quantum Error Correction with Superconducting Circuits
• Catastrophe observation in a Josephson junction system

Cited by in corpus (7)

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• Deep Neuromorphic Networks with Superconducting Single Flux Quanta