Zobrazeno 1 - 10
of 10 639
pro vyhledávání: '"Soloviev A. A."'
Publikováno v:
Solar-Terrestrial Physics, Vol 10, Iss 1, Pp 76-83 (2024)
We solve the problem of recognizing geomagnetic storms from matrix time series of observations with the URAGAN muon hodoscope, using deep learning neural networks. A variant of the neural network software module is selected and its parameters are det
Externí odkaz:
https://doaj.org/article/e27182eb865b451e8802ac314a9895ba
Autor:
Belov I. O., Soloviev A. A., Pilipenko V. A., Dobrovolskiy M. N., Bogoutdinov S. R., Kalinkin K. D.
Publikováno v:
Solar-Terrestrial Physics, Vol 9, Iss 4, Pp 111-122 (2023)
In this paper, we describe the TeslaSwarm online system [http://aleph.gcras.ru/teslaswarm] for visualizing field-aligned currents in the upper ionosphere, using data from Swarm low-orbit satellites. The system provides researchers with a simple and c
Externí odkaz:
https://doaj.org/article/a2ccee1f3c384d80a42626480fed5084
Autor:
Vorobev A. V., Soloviev A. A., Pilipenko V. A., Vorobeva G. R., Gainetdinova A. A., Lapin A. N., Belahovskiy V. B., Roldugin A. V.
Publikováno v:
Solar-Terrestrial Physics, Vol 9, Iss 2, Pp 26-34 (2023)
Despite the existing variety of approaches to monitoring space weather and geophysical parameters in the auroral oval region, the issue of effective prediction and diagnostics of auroras as a special state of the upper ionosphere at high latitudes re
Externí odkaz:
https://doaj.org/article/205896c9d39e4bbe882033b3d7ed3dd4
Publikováno v:
Solar-Terrestrial Physics, Vol 8, Iss 2, Pp 84-90 (2022)
An interactive computer model of a short-term (with a horizon 30–70 min) forecast of aurora intensity has been developed in the form of a web-based geoinformation system. The OVATION-Prime empirical model is used as the basic software, which establ
Externí odkaz:
https://doaj.org/article/2784b74d6b1d4cbfa188ddfd84708784
We determine the behavior of an out-of-equilibrium superfluid, composed of a $U(1)$ Goldstone mode coupled to hydrodynamic modes in a M\"uller-Israel-Stewart theory, in expanding backgrounds relevant to heavy ion collision experiments and cosmology.
Externí odkaz:
http://arxiv.org/abs/2410.01892
Publikováno v:
JHEP 10 (2024) 226
Gubser flow is an evolution with cylindrical and boost symmetries, which can be best studied by mapping the future wedge of Minkowski space (R$^{3,1}$) to dS$_3$ $\times$ $\mathbb{R}$ in a conformal relativistic theory. Here, we sharpen our previous
Externí odkaz:
http://arxiv.org/abs/2408.04001
Autor:
Bakurskiy, S. V., Ruzhickiy, V. I., Neilo, A. A., Klenov, N. V., Soloviev, I. I., Elistratova, A. A., Shishkin, A. G., Stolyarov, V. S., Kupriyanov, M. Yu.
Publikováno v:
Published in JMSN: 2024-07-27 , Article , 01-01003, Volume 1, Issue 1
We have studied the Thouless energy in Josephson superconductor-normal metal-superconductor (SN-N-NS) bridges analytically and numerically, taking into account the influence of the sub-electrode regions. We have found a significant suppression of the
Externí odkaz:
http://arxiv.org/abs/2408.01717
Quantum architecture search (QAS) involves optimizing both the quantum parametric circuit configuration but also its parameters for a variational quantum algorithm. Thus, the problem is known to be multi-level as the performance of a given architectu
Externí odkaz:
http://arxiv.org/abs/2407.20091
Publikováno v:
Phys. Rev. D 110, 056053 (2024)
Diffusion is a dissipative transport phenomenon ubiquitously present in nature. Its details can now be analysed with modern effective field theory (EFT) techniques that use the closed-time-path (or Schwinger-Keldysh) formalism. We discuss the structu
Externí odkaz:
http://arxiv.org/abs/2407.13550
Autor:
Pashin, D. S., Bastrakova, M. V., Rybin, D. A., Soloviev, I. I., Schegolev, A. E., Klenov, N. V.
In this article, we consider designs of simple analog artificial neural networks based on adiabatic Josephson cells with a sigmoid activation function. A new approach based on the gradient descent method is developed to adjust the circuit parameters,
Externí odkaz:
http://arxiv.org/abs/2405.03521