arXiv subjects

Alexander Drozdov

Publications and source records attributed to Alexander Drozdov.

6 recordsLinked to original sources

arXiv2023

The case for studying other planetary magnetospheres and atmospheres in Heliophysics

Heliophysics is the field that "studies the nature of the Sun, and how it influences the very nature of space - and, in turn, the atmospheres of planetary bodies and the technology that exists there." However, NASA's Heliophysics Division tends to limit study of planetary magnetospheres and atmospheres to only those of Earth. This leaves exploration and understanding of space plasma physics at other worlds to the purview of the Planetary Science and Astrophysics Divisions. This is detrimental to the study of space plasma physics in general since, although some cross-divisional funding opportunities do exist, vital elements of space plasma physics can be best addressed by extending the expertise of Heliophysics scientists to other stellar and planetary magnetospheres. However, the diverse worlds within the solar system provide crucial environmental conditions that are not replicated at Earth but can provide deep insight into fundamental space plasma physics processes. Studying planetary systems with Heliophysics objectives, comprehensive instrumentation, and new grant opportunities for analysis and modeling would enable a novel understanding of fundamental and universal processes of space plasma physics. As such, the Heliophysics community should be prepared to consider, prioritize, and fund dedicated Heliophysics efforts to planetary targets to specifically study space physics and aeronomy objectives.

astro-ph.IM↗

arXiv2022

Correlation between bandwidth and frequency of plasmaspheric hiss uncovered with unsupervised machine learning

Previous statistical studies of plasmaspheric hiss investigated the averaged shape of the magnetic field power spectra at various points in the magnetosphere. However, this approach does not consider the fact that very diverse spectral shapes exist at a given L-shell and magnetic local time. Averaging the data together means that important features of the spectral shapes are lost. In this paper, we use an unsupervised machine learning technique to categorize plasmaspheric hiss. In contrast to the previous studies, this technique allows us to identify power spectra that have "similar" shapes and study their spatial distribution without averaging together vastly different spectral shapes. We show that strong negative correlations exist between the hiss frequency and bandwidth, which suggests that the observed patterns are consistent with in situ wave growth.

physics.space-ph↗

arXiv2021

Machine-learning based discovery of missing physical processes in radiation belt modeling

Real-time prediction of the dynamics of energetic electrons in Earth's radiation belts incorporating incomplete observation data is important to protect valuable artificial satellites and to understand their physical processes. Traditionally, reduced models have employed a diffusion equation based on the quasilinear approximation. Using a Physics-Informed Neural Network (PINN) framework, we train and test a model based on Van Allen Probe data. We present a recipe for gleaning physical insight from solving the ill-posed inverse problem of inferring model coefficients from data using PINNs. With this, it is discovered that the dynamics of "killer electrons" is described more accurately instead by a drift-diffusion equation. A parameterization for the diffusion and drift coefficients, which is both simpler and more accurate than existing models, is presented.

physics.space-ph↗

arXiv2020

Bayesian inference of quasi-linear radial diffusion parameters using Van Allen Probes

The Van Allen radiation belts in the magnetosphere have been extensively studied using models based on radial diffusion theory, which is based on a quasi-linear approach with prescribed inner and outer boundary conditions. The 1-d diffusion model requires the knowledge of a diffusion coefficient and an electron loss timescale, which are typically parameterized in terms of various quantities such as the spatial ($L$) coordinate or a geomagnetic index (for example, $Kp$). These terms are empirically derived, not directly measurable, and hence are not known precisely, due to the inherent non-linearity of the process and the variable boundary conditions. In this work, we demonstrate a probabilistic approach by inferring the values of the diffusion and loss term parameters, along with their uncertainty, in a Bayesian framework, where identification is obtained using the Van Allen Probe measurements. Our results show that the probabilistic approach statistically improves the performance of the model, compared to the parameterization employed in the literature.

physics.space-ph↗

arXiv2019

Simulations of the inner magnetospheric energetic electrons using theIMPTAM-VERB coupled model

In this study, we present initial results of the coupling between the Inner Magnetospheric Particle Transport and Acceleration Model (IMPTAM) and the Versatile Electron Radiation Belt (VERB-3D) code. IMPTAM traces electrons of 10 - 100 keV energies from the plasma sheet (L = 9 Re) to inner L-shell regions. The flux evolution modeled by IMPTAM is used at the low energy and outer L* computational boundaries of the VERB code (assuming a dipole approximation) to perform radiation belt simulations of energetic electrons. The model was tested on the March 17th, 2013 storm, for a six-day period. Four different simulations were performed and their results compared to satellites observations from Van Allen probes and GOES. The coupled IMPTAM-VERB model reproduces evolution and storm-time features of electron fluxes throughout the studied storm in agreement with the satellite data (within ~0.5 orders of magnitude). Including dynamics of the low energy population at L* = 6.6 increases fluxes closer to the heart of the belt and has a strong impact in the VERB simulations at all energies. However, inclusion of magnetopause losses leads to drastic flux decreases even below L* = 3. The dynamics of low energy electrons (max. 10s of keV) do not affect electron fluxes at energies >= 900 keV. Since the IMPTAM-VERB coupled model is only driven by solar wind parameters and the Dst and Kp indexes, it is suitable as a forecasting tool. In this study, we demonstrate that the estimation of electron dynamics with satellite-data-independent models is possible and very accurate.

physics.space-ph↗

arXiv2015

Crystal Structure of 200 K-Superconducting Phase of Sulfur Hydride System

This article reports the experimentally clarified crystal structure of a recently discovered sulfur hydride in high temperature superconducting phase which has the highest critical temperature Tc over 200 K which has been ever reported. For understanding the mechanism of the high superconductivity, the information of its crystal structure is very essential. Herein we have carried out the simultaneous measurements electrical resistance and synchrotron x-ray diffraction under high pressure, and clearly revealed that the hydrogen sulfide, H2S, decomposes to H3S and its crystal structure has body-centered cubic symmetry in the superconducting phase.

cond-mat.supr-con↗