XXVIII International Symposium ''Nanophysics and Nanoelectronics'', Nizhny Novgorod, March 11-15, 2024
Metals

Numerical simulation of the superconducting sigma neuron design

A. S. Ionin^abc, S. V. Egorov^a, M. S. Sidelnikov^a, L. N. Karelina^a, N. S. Shuravin^a, M. M. Khapaev^ad, V. V. Bol'ginov<sup>a

a</sup> Osipyan Institute of Solid State Physics, Russian Academy of Sciences, Chernogolovka, Russia
^b Moscow Institute of Physics and Technology (National Research University), Dolgoprudny, Moscow Region
^c OOO SP Kvant, Moscow, Russia
^d Lomonosov Moscow State University

Abstract: The results of numerical simulation of the distribution of superconducting currents in the prototype of an adiabatic sigma neuron, implemented in 2023 in the form of a multilayer thin-film structure over a thick superconducting screen, are presented. The calculation was carried out in the 3D-MLSI program, which allows taking into account the three-dimensional design of the experimental sample. A good agreement was obtained between the values of the intrinsic inductances of the sigma neuron parts and the previously obtained numerical estimates. It is shown that the superconducting screen does not provide sufficient independence of the neuron elements, which is expressed in non-zero values of the corresponding components of the inductance matrix. This corresponds to the available experimental data and requires generalization of previously proposed models of the stationary state of a superconducting sigma neuron. A method is proposed to compensate for the parasitic coupling of the input and readout elements of the neuron by changing the shape of the control line.

Keywords: superconductivity, Josephson effect, neuromorphic computing, thin-film structures, numerical modeling.

Received: 18.04.2024
Revised: 18.04.2024
Accepted: 08.05.2024

DOI: 10.61011/FTT.2024.07.58366.25HH

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