Zobrazeno 1 - 10
of 107
pro vyhledávání: '"Smirnov, Lev"'
The use of machine learning to predict wave dynamics is a topic of growing interest, but commonly-used deep learning approaches suffer from a lack of interpretability of the trained models. Here we present an interpretable machine learning framework
Externí odkaz:
http://arxiv.org/abs/2411.11556
Autor:
Pikovsky, Arkady, Smirnov, Lev A.
Publikováno v:
Chaos, v. 34, 073120 (2024)
We explore large populations of phase oscillators interacting via random coupling functions. Two types of coupling terms, the Kuramoto-Daido coupling and the Winfree coupling, are considered. Under the assumption of statistical independence of the ph
Externí odkaz:
http://arxiv.org/abs/2404.06193
Autor:
Bolotov, Maxim I., Munyayev, Vyacheslav O., Smirnov, Lev A., Osipov, Grigory V., Belykh, Igor
Cyclops states are intriguing cluster patterns observed in oscillator networks, including neuronal ensembles. The concept of cyclops states formed by two distinct, coherent clusters and a solitary oscillator was introduced in [Munyayev {\it et al.},
Externí odkaz:
http://arxiv.org/abs/2312.09831
We study deterministic dynamics of overactive Brownian particles in 2D and 3D potentials. This dynamics is Hamiltonian. Integrals of motion for continuous rotational symmetries are reported. The cases of 2D, axisymmetric and non-axisymmetric 3D poten
Externí odkaz:
http://arxiv.org/abs/2312.09141
In this work, two-cluster modes are studied in a system of globally coupled Kuramoto-Sakaguchi phase oscillators with inertia. It is shown that these regimes can be of two types: with a constant intercluster phase difference rotating at the same freq
Externí odkaz:
http://arxiv.org/abs/2311.12172
We show how machine learning techniques can be applied for the classification of topological phases in leaky photonic lattices using limited measurement data. We propose an approach based solely on bulk intensity measurements, thus exempt from the ne
Externí odkaz:
http://arxiv.org/abs/2308.14407
Autor:
Smirnov, Lev A., Pikovsky, Arkady
Publikováno v:
Phys. Rev. Lett., v. 132, 107401 (2024)
We consider a population of globally coupled oscillators in which phase shifts in the coupling are random. We show that in the maximally disordered case, where the pairwise shifts are i.i.d. random variables, the dynamics of a large population reduce
Externí odkaz:
http://arxiv.org/abs/2307.12563
Publikováno v:
Phys. Rev. A 108, L061501 (2023)
Localized nonlinear modes at valley-Hall interfaces in staggered photonic graphene can be described in the long-wavelength limit by a nonlinear Dirac-like model including spatial dispersion terms. It leads to a modified nonlinear Schr\"odinger equati
Externí odkaz:
http://arxiv.org/abs/2305.06544
Publikováno v:
Nanophotonics, Vol 13, Iss 3, Pp 271-281 (2024)
We show how machine learning techniques can be applied for the classification of topological phases in finite leaky photonic lattices using limited measurement data. We propose an approach based solely on a single real-space bulk intensity image, thu
Externí odkaz:
https://doaj.org/article/54d9f2abf81644aba91e26c6332529b1
Autor:
Smirnova, Daria A., Smirnov, Lev A., Smolina, Ekaterina O., Angelakis, Dimitris G., Leykam, Daniel
Publikováno v:
Phys. Rev. Research 3, 043027 (2021)
We derive nonlinear wave equations describing the propagation of slowly-varying wavepackets formed by topological valley-Hall edge states. We show that edge pulses break up even in the absence of spatial dispersion due to nonlinear self-steepening. S
Externí odkaz:
http://arxiv.org/abs/2102.10569