Experimental Study of a Prototype of a Superconducting Sigma Neuron for Adiabatic Neural Networks

Abstract

The artificial neuron proposed earlier for use in superconducting neural networks is experimentally studied. The fabricated sample is a single-junction interferometer, part of the circuit of which is shunted by an additional inductance, which is also used to generate an output signal. A technological process has been developed and tested to fabricate a neuron in the form of a multilayer thin-film structure over a thick superconducting screen. The transfer function of the fabricated sample, which contains sigmoid and linear components, is experimentally measured. A theoretical model is developed to describe the relation between input and output signals in a practical superconducting neuron. The derived equations are shown to approximate experimental curves at a high level of accuracy. The linear component of the transfer function is shown to be related to the direct transmission of an input signal to a measuring circuit. Possible ways for improving the design of the sigma neuron are considered.