V. M. Souza

Outer radiation belt dropout dynamics following the arrival of two interplanetary coronal mass ejections

Magnetopause shadowing and wave-particle interactions are recognized as the two primary mechanisms for losses of electrons from the outer radiation belt. We investigate these mechanisms, sing satellite observations both in interplanetary space and within the magnetosphere and particle drift modeling. Two interplanetary shocks sheaths impinged upon the magnetopause causing a relativistic electron flux dropout. The magnetic cloud (C) and interplanetary structure sunward of the MC had primarily northward magnetic field, perhaps leading to a concomitant lack of substorm activity and a 10 day long quiescent period. The arrival of two shocks caused an unusual electron flux dropout. Test-particle simulations have shown 2 to 5 MeV energy, equatorially mirroring electrons with initial values of L 5.5can be lost to the magnetosheath via magnetopause shadowing alone. For electron losses at lower L-shells, coherent chorus wave-driven pitch angle scattering and ULF wave-driven radial transport have been shownto be viable mechanisms.

Classification of Magnetospheric Particle Distributions Via Neural Networks

Abstract In this chapter we introduce a special kind of neural network known as a self-organizing map (SOM) and use it to cluster/classify pitch angle-resolved particle flux data obtained by instruments onboard satellites orbiting the Earth. As an example of the technique, we employ electron flux data at both relativistic and subrelativistic energies provided by two instruments onboard one of the twin NASA’s Van Allen Probes. For these data sets the SOM can identify the shapes of three well-known types of pitch angle distributions, and from that knowledge one can infer the associated physical mechanisms in the near-Earth space environment, particularly in the Van Allen radiation belts region. The SOM-based methodology can be used with multiplatform spacecraft data, thus enabling a prompt characterization of the physical processes throughout the Earth’s magnetosphere. The steps required to apply our neural network-based approach to pitch angle-resolved particle flux data from any spacecraft mission are laid out.

Acceleration of radiation belt electrons and the role of the average interplanetary magnetic field Bz component in high‐speed streams

In this study we examine the recovery of relativistic radiation belt electrons on November 15-16, 2014, after a previous reduction in the electron flux resulting from the passage of a Corotating Interaction Region (CIR). Following the CIR, there was a period of high-speed streams characterized by large, nonlinear fluctuations in the interplanetary magnetic field (IMF) components. However, the outer radiation belt electron flux remained at a low level for several days before it increased in two major steps. The first increase is associated with the IMF background field turning from slightly northward on average, to slightly southward on average. The second major increase is associated with an increase in the solar wind velocity during a period of southward average IMF background field. We present evidence that when the IMF Bz is negative on average, the whistler mode chorus wave power is enhanced in the outer radiation belt, and the amplification of magnetic integrated power spectral density in the ULF frequency range, in the nightside magnetosphere, is more efficient as compared to cases in which the mean IMF Bz is positive. Preliminary analysis of the time evolution of phase space density radial profiles did not provide conclusive evidence on which electron acceleration mechanism is the dominant. We argue that the acceleration of radiation belt electrons requires (i) a seed population of keV electrons injected into the inner magnetosphere by substorms, and both (ii) enhanced whistler mode chorus waves activity as well as (iii) large-amplitude MHD waves.

A Neural Network Approach for Identifying Particle Pitch Angle Distributions in Van Allen Probes Data

Analysis of particle pitch angle distributions (PADs) has been used as a means to comprehend a multitude of different physical mechanisms that lead to flux variations in the Van Allen belts and also to particle precipitation into the upper atmosphere. In this work we developed a neural network-based data clustering methodology that automatically identifies distinct PAD types in an unsupervised way using particle flux data. One can promptly identify and locate three well-known PAD types in both time and radial distance, namely, 90deg peaked, butterfly, and flattop distributions. In order to illustrate the applicability of our methodology, we used relativistic electron flux data from the whole month of November 2014, acquired from the Relativistic Electron-Proton Telescope instrument on board the Van Allen Probes, but it is emphasized that our approach can also be used with multiplatform spacecraft data. Our PAD classification results are in reasonably good agreement with those obtained by standard statistical fitting algorithms. The proposed methodology has a potential use for Van Allen belts monitoring.

Bases teóricas da reconexão magnética

In this work both the concept and historical origins of the physical process known as magnetic reconnection are presented, as well as one of the first analytical models which was used as theoretical basis for future investigations on the phenomenon. Magnetic reconnection can occur between two or more magnetized plasma regimes which are close enough to allow non-ideal magnetohydrodynamic effects to take place and consequently change the topological structure of the interacting magnetic fields. As a result, the plasma can be accelerated in a short amount of time, as has been observed in explosive physical phenomena like solar flares. In this work, it is emphasized the first mathematical efforts employed in order to understand and describe reconnection according to the point of view of magnetohydrodynamics. Magnetic reconnection has the potential of becoming a universal mechanism which can be used to help to understand a myriad of physical processes occurring in both laboratory and astrophysical plasmas.