Superconducting artificial neural networks and quantum circuits

• Anatolie S. Sidorenko

Beilstein J. Nanotechnol. 2026, 17, 744–747, doi:10.3762/bjnano.17.51

• Anatolie S. Sidorenko Technical University of Moldova, Chisinau 2004, Republic of Moldova 10.3762/bjnano.17.51 Keywords: artificial neural networks; high-performance computing; Josephson junctions; superconducting digital technologies; superconducting quantum circuits; ultra-low energy

• superconducting quantum circuits and superconducting digital technologies based on Josephson junctions. The energy consumption of a basic element of superconducting digital technology is on the order of 10−19 J, corresponding to up to seven orders of magnitude lower energy dissipation than that of semiconductor

Modeling magnetic properties of cobalt nanofilms used as a component of spin hybrid superconductor–ferromagnetic structures

• Aleksey Fedotov,
• Olesya Severyukhina,
• Anastasia Salomatina and
• Anatolie Sidorenko

Beilstein J. Nanotechnol. 2025, 16, 1557–1566, doi:10.3762/bjnano.16.110

• are currently used, as well as fundamental features of the thin film formation processes with new composition and coatings of various types. These types of nanomaterials are very promising (in terms of computational performance and energy dissipation efficiency) for use in superconducting digital

• technologies [5][6][7] based on Josephson junctions. It is well established that the properties of nanostructures can significantly differ from those of bulk samples. Currently, close attention is paid to thin-film magnetic structures, which include cobalt and iron [8][9][10]. Thus, in [1], the crystal