Zobrazeno 1 - 10
of 44
pro vyhledávání: '"I. A. Iakovlev"'
Autor:
O. M. Sotnikov, I. A. Iakovlev, A. A. Iliasov, M. I. Katsnelson, A. A. Bagrov, V. V. Mazurenko
Publikováno v:
npj Quantum Information, Vol 8, Iss 1, Pp 1-13 (2022)
Abstract The rapid development of quantum computing technologies already made it possible to manipulate a collective state of several dozens of qubits, which poses a strong demand on efficient methods for characterization and verification of large-sc
Externí odkaz:
https://doaj.org/article/86c0f01056e94a83a5ec492140d3affd
Publikováno v:
2023 International Russian Smart Industry Conference (SmartIndustryCon).
Autor:
Alexander N. Rudenko, E. A. Stepanov, Georgy V. Pushkarev, D. A. Prishchenko, Vladimir G. Mazurenko, Vladimir V. Mazurenko, I. A. Iakovlev
Publikováno v:
Physical Review B. 102
Single-layer antimony or antimonene is a recently discovered two-dimensional material with high environmental stability and appealing electronic properties. Antimonene is characterized by strong spin-orbit coupling, which suggests unconventional beha
Autor:
I. K. Iakovlev, A. A. Maslov
Publikováno v:
Euroasian Entomological Journal. 17:440-444
Autor:
I V Iakovlev, A P Pesterev
Publikováno v:
IOP Conference Series: Earth and Environmental Science. 988:022038
The management of industrial safety and occupational health associated with oil and gas production is one of the vital components of the oil and gas industry, since it is well known that most conditions of operation, processing and storage of chemica
Autor:
I. A. Iakovlev, Alexander A. Tsirlin, Yoshifumi Tokiwa, Philipp Gegenwart, Qingming Zhang, Vladimir V. Mazurenko, Andreas Wörl, Yuesheng Li, Langsheng Ling, Sebastian Bachus
Publikováno v:
Phys. Rev. B
Physical Review B
Physical Review B
We report magnetization, heat capacity, thermal expansion, and magnetostriction measurements down to millikelvin temperatures on the triangular antiferromagnet YbMgGaO4. Our data exclude the formation of the distinct 13 plateau phase observed in othe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f5764e22bec163ac1caee4b77911e18
http://arxiv.org/pdf/2006.09775
http://arxiv.org/pdf/2006.09775
Autor:
Vladimir V. Mazurenko, Andrey A. Bagrov, Askar A. Iliasov, Mikhail I. Katsnelson, I. A. Iakovlev
Publikováno v:
Proceedings of the National Academy of Sciences USA, 117, 30241-30251
Proc. Natl. Acad. Sci. U. S. A.
Proceedings of the National Academy of Sciences of the United States of America
Proceedings of the National Academy of Sciences USA, 117, 48, pp. 30241-30251
Proc Natl Acad Sci U S A
Proc. Natl. Acad. Sci. U. S. A.
Proceedings of the National Academy of Sciences of the United States of America
Proceedings of the National Academy of Sciences USA, 117, 48, pp. 30241-30251
Proc Natl Acad Sci U S A
Complexity of patterns is a key information for human brain to differ objects of about the same size and shape. Like other innate human senses, the complexity perception cannot be easily quantified. We propose a transparent and universal machine meth
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1b89e11f6e40be4e2b522e9643d5c02f
https://doi.org/10.1073/pnas.2004976117
https://doi.org/10.1073/pnas.2004976117
Publikováno v:
Phys. Rev. B
Physical Review B
Physical Review B
We propose an approach for low-dimensional visualization and classification of complex topological magnetic structures formed in magnetic materials. Within the approach one converts a three-dimensional magnetic configuration to a vector containing th
Publikováno v:
Phys. Rev. Appl.
Physical Review Applied
Physical Review Applied
By using the supervised learning we train a recurrent neural network to recognize and classify ultrafast magnetization processes realized in two-dimensional nanosystems with Dzyaloshinskii-Moriya interaction. Our focus is on the different types of sk
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::13f23fac1848973700df46c27b8a241e
https://hdl.handle.net/10995/112281
https://hdl.handle.net/10995/112281
Publikováno v:
Phys. Rev. B
Physical Review B
Physical Review B
We propose and apply simple machine learning approaches for recognition and classification of complex noncollinear magnetic structures in two-dimensional materials. The first approach is based on the implementation of the single-hidden-layer neural n