Zobrazeno 1 - 10
of 1 451
pro vyhledávání: '"Ivanov, Sergey A."'
Publikováno v:
Chaos, Solitons & Fractals, 186, 115239 (2024)
We introduce traveling Floquet valley Hall edge solitons in a genuinely continuous system consisting of a waveguide array with a dynamically varying domain wall between two honeycomb structures exhibiting broken inversion symmetry. Inversion symmetry
Externí odkaz:
http://arxiv.org/abs/2407.09973
Publikováno v:
Chaos, Solitons and Fractals 174, 113866 (2023)
We study the existence and stability of $\pi$-solitons on a ring of periodically oscillating waveguides. The array is arranged into Su-Schrieffer-Heeger structure placed on a ring, with additional spacing between two ends of the array. Due to longitu
Externí odkaz:
http://arxiv.org/abs/2307.09881
Publikováno v:
Optics Letters 48, 14, 3797-3800 (2023)
We show that optical moire lattices enable the existence of vortex solitons of different types in self-focusing Kerr media. We address the properties of such states both in lattices having commensurate and incommensurate geometries (i.e., constructed
Externí odkaz:
http://arxiv.org/abs/2306.15358
Publikováno v:
Phys. Rev. A 107, 033514 (2023)
We introduce a different class of thresholdless three-dimensional soliton states that form in higher-order topological insulators based on a two-dimensional Su-Schrieffer-Heeger array of coupled waveguides. The linear spectrum of such structures is c
Externí odkaz:
http://arxiv.org/abs/2303.15891
Publikováno v:
Optics Letters 48, 5, 1268-1271 (2023)
We address the formation of topological edge solitons in rotating Su-Schrieffer-Heeger waveguide arrays. The linear spectrum of the non-rotating topological array is characterized by the presence of topological gap with two edge states residing in it
Externí odkaz:
http://arxiv.org/abs/2302.00477
Graph Neural Networks (GNNs) have been predominant for graph learning tasks; however, recent studies showed that a well-known graph algorithm, Label Propagation (LP), combined with a shallow neural network can achieve comparable performance to GNNs i
Externí odkaz:
http://arxiv.org/abs/2205.09389
Autor:
Ivanov, Sergey
This textbook covers principles behind main modern deep reinforcement learning algorithms that achieved breakthrough results in many domains from game AI to robotics. All required theory is explained with proofs using unified notation and emphasize o
Externí odkaz:
http://arxiv.org/abs/2201.09746
Autor:
Talanov, Mikhail V., Avakyan, Leon A., Kozlov, Vladislav I., Ivanov, Sergey A., Stash, Adam I., Zhukova, Elena S., Gorshunov, Boris P., Bush, Alexander A.
Publikováno v:
In Acta Materialia 15 September 2024 277
Autor:
Zavestovskaya, Irina N., Filimonova, Marina V., Popov, Anton L., Zelepukin, Ivan V., Shemyakov, Alexander E., Tikhonowski, Gleb V., Savinov, Maxim, Filimonov, Alexander S., Shitova, Anna A., Soldatova, Olga V., Kolmanovich, Danil D., Shakhov, Pavel V., Kotelnikova, Polina A., Popov, Anton A., Chukavin, Nikita N., Pivovarov, Nikita A., Syuy, Alexander V., Klimentov, Sergey M., Ryabov, Vladimir A., Ivanov, Sergey A., Kaprin, Andrei D., Prasad, Paras N., Deyev, Sergey M., Koryakin, Sergei N., Kabashin, Andrei V.
Publikováno v:
In Materials Today Nano August 2024 27
Publikováno v:
Optics Letters Vol. 46, Issue 19, pp. 4710-4713 (2021)
We consider a topological Floquet insulator realized as a honeycomb array of helical waveguides imprinted in weakly birefringent medium. The system accounts for four-wave mixing occurring at a series of resonances arising due to Floquet phase matchin
Externí odkaz:
http://arxiv.org/abs/2111.01293