Transfer function of an asymmetric superconducting Gauss neuron

• Fedor A. Razorenov,
• Aleksander S. Ionin,
• Nikita S. Shuravin,
• Liubov N. Karelina,
• Mikhail S. Sidel’nikov,
• Sergey V. Egorov and
• Vitaly V. Bol’ginov

Beilstein J. Nanotechnol. 2025, 16, 1160–1170, doi:10.3762/bjnano.16.85

• a previously conducted experiment. Keywords: Josephson interferometers; superconducting neural network; superconductivity; Introduction Over the past decade, artificial neural networks have demonstrated their effectiveness and versatility in tasks related to processing large volumes of data

Tunable superconducting neurons for networks based on radial basis functions

• Andrey E. Schegolev,
• Nikolay V. Klenov,
• Sergey V. Bakurskiy,
• Igor I. Soloviev,
• Mikhail Yu. Kupriyanov,
• Maxim V. Tereshonok and
• Anatoli S. Sidorenko

Beilstein J. Nanotechnol. 2022, 13, 444–454, doi:10.3762/bjnano.13.37

• , ferromagnetic, and normal layers. Keywords: networks on radial basis functions; Josephson circuits; radial basis functions (RBFs); spintronics; superconducting electronics; superconducting neural network; Introduction For modern telecommunications, probabilistic identification of various sources in a

Controlling the proximity effect in a Co/Nb multilayer: the properties of electronic transport

• Sergey Bakurskiy,
• Mikhail Kupriyanov,
• Nikolay V. Klenov,
• Igor Soloviev,
• Andrey Schegolev,
• Roman Morari,
• Yury Khaydukov and
• Anatoli S. Sidorenko

Beilstein J. Nanotechnol. 2020, 11, 1336–1345, doi:10.3762/bjnano.11.118

• superlattices can be used as tunable kinetic inductors designed for artificial neural networks representing the information in a “current domain”. Keywords: cryogenic computing; spin-valve; superconducting neural network; superconducting spintronics; Introduction Multilayer superconductor/ferromagnetic (S/F