Electron‐Scale Magnetic Structure Observed Adjacent to an Electron Diffusion Region at the Dayside Magnetopause

2019 ◽  
Vol 124 (12) ◽  
pp. 10153-10169
Author(s):  
S. Hoilijoki ◽  
R. E. Ergun ◽  
S. J. Schwartz ◽  
S. Eriksson ◽  
F. D. Wilder ◽  
...  
Keyword(s):  
Magnetic Structure ◽  
Diffusion Region ◽  
Electron Diffusion ◽  
Dayside Magnetopause

A Survey of Plasma Waves Appearing Near Dayside Magnetopause Electron Diffusion Region Events

2019 ◽  
Vol 124 (10) ◽  
pp. 7837-7849 ◽  
Author(s):  
F. D. Wilder ◽  
R. E. Ergun ◽  
S. Hoilijoki ◽  
J. Webster ◽  
M. R. Argall ◽  
...  
Keyword(s):  
Plasma Waves ◽  
Diffusion Region ◽  
Electron Diffusion ◽  
Dayside Magnetopause

On the identification of Electron Diffusion Regions at the magnetopause with an AI approach

2020 ◽  
Author(s):  
Quentin Lenouvel ◽  
Vincent Génot ◽  
Philippe Garnier ◽  
Sergio Toledo-Redondo ◽  
Benoît Lavraud ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Science ◽  
Phase 1 ◽  
Diffusion Region ◽  
Data Set ◽  
Electron Diffusion ◽  
Training Techniques ◽  
Research Fields ◽  
Dayside Magnetopause

<div> <div> <div> <div> <div> <div> <div> <div> <div> <div> <p><strong></strong></p> <p>MMS has already been producing a very large dataset with invaluable information about how the solar wind and the Earth's magnetosphere interact. However, it remains challenging to process all these new data and convert it into scientific knowledge, the ultimate goal of the mission. Data science and machine learning are nowadays a very powerful and successful technology that is employed to many applied and research fields. During this presentation, I shall discuss the tentative use of machine learning for the automatic detection and classification of plasma regions, relevant to the study of magnetic reconnection in the MMS data set, with a focus on the critical but poorly understood electron diffusion region (EDR) at the Earth's dayside magnetopause. We make use of the EDR database and the plasma regions nearby that has been identified by the MMS community and compiled by Webster et al. (2018) as well as the Magnetopause crossings database compiled by the ISSI team, to train a neural network using supervised training techniques. I shall present a list of new EDR candidates found during the phase 1 of MMS and do a case study of some of the strong candidates.</p> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div>

scholarly journals Identification of the Electron-Diffusion Region during Magnetic Reconnection in a Laboratory Plasma

2008 ◽  
Vol 101 (8) ◽  
Author(s):  
Yang Ren ◽  
Masaaki Yamada ◽  
Hantao Ji ◽  
Stefan P. Gerhardt ◽  
Russell Kulsrud
Keyword(s):  
Magnetic Reconnection ◽  
Diffusion Region ◽  
Laboratory Plasma ◽  
Electron Diffusion

Reconstruction of the electron diffusion region

2016 ◽  
Vol 121 (5) ◽  
pp. 4279-4290 ◽  
Author(s):  
B. U. Ö. Sonnerup ◽  
H. Hasegawa ◽  
R. E. Denton ◽  
T. K. M. Nakamura
Keyword(s):  
Diffusion Region ◽  
Electron Diffusion

Micro-scale tearing mode turbulence in the diffusion region during macro-scale evolution of turbulent reconnection

2021 ◽  
Author(s):  
Takuma Nakamura ◽  
Hiroshi Hasegawa ◽  
Tai Phan ◽  
Kevin Genestreti ◽  
Richard Denton ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Energy Conversion ◽  
Magnetic Reconnection ◽  
Diffusion Region ◽  
Electron Diffusion ◽  
Efficient Energy ◽  
Micro Scale ◽  
Island Evolution ◽  
Macro Scale ◽  
Scale Evolution

<p>Magnetic reconnection is a key fundamental process in collisionless plasmas that explosively converts magnetic energy to plasma kinetic and thermal energies through a change of magnetic field topology in an electron-scale central region called the electron diffusion region. Past simulations and observations demonstrated that this process causes efficient energy conversion through the formation of multiple macro-scale or micro-scale magnetic islands/flux ropes. However, how these different spatiotemporal scale phenomena are coupled is still poorly understood. In this study, to investigate the turbulent evolution of magnetic reconnection, we perform a new large-scale fully kinetic simulation of a thin current sheet considering a power-law spectrum of initial fluctuations in the magnetic field as frequently observed in the Earth’s magnetotail. The simulation demonstrates that during a macro-scale evolution of turbulent reconnection, the merging of macro-scale islands results in reduction of the rate of reconnection as well as the aspect ratio of the electron diffusion region. This allows the repeated, quick formation of new electron-scale islands within the electron diffusion region, leading to an efficient energy cascade between macro- and micro-scales. The simulation also demonstrates that a strong electron acceleration/heating occurs during the micro-scale island evolution within the EDR. These new findings indicate the importance of non-steady features of the EDR to comprehensively understand the energy conversion and cascade processes in collisionless reconnection.</p>

scholarly journals Spatial dimensions of the electron diffusion region in anti-parallel magnetic reconnection

2016 ◽  
Vol 34 (3) ◽  
pp. 357-367 ◽  
Author(s):  
Takuma Nakamura ◽  
Rumi Nakamura ◽  
Hiroshi Haseagwa
Keyword(s):  
Electric Field ◽  
Magnetic Reconnection ◽  
Real Space ◽  
Diffusion Region ◽  
Electron Mass ◽  
Plasma Parameters ◽  
Electron Diffusion ◽  
Background Density ◽  
Spatial Dimensions ◽  
Inner Region

Abstract. Spatial dimensions of the detailed structures of the electron diffusion region in anti-parallel magnetic reconnection were analyzed based on two-dimensional fully kinetic particle-in-cell simulations. The electron diffusion region in this study is defined as the region where the positive reconnection electric field is sustained by the electron inertial and non-gyrotropic pressure components. Past kinetic studies demonstrated that the dimensions of the whole electron diffusion region and the inner non-gyrotropic region are scaled by the electron inertial length de and the width of the electron meandering motion, respectively. In this study, we successfully obtained more precise scalings of the dimensions of these two regions than the previous studies by performing simulations with sufficiently small grid spacing (1∕16–1∕8 de) and a sufficient number of particles (800 particles cell−1 on average) under different conditions changing the ion-to-electron mass ratio, the background density and the electron βe (temperature). The obtained scalings are adequately supported by some theories considering spatial variations of field and plasma parameters within the diffusion region. In the reconnection inflow direction, the dimensions of both regions are proportional to de based on the background density. Both dimensions also depend on βe based on the background values, but the dependence in the inner region ( ∼ 0.375th power) is larger than the whole region (0.125th power) reflecting the orbits of meandering and accelerated electrons within the inner region. In the outflow direction, almost only the non-gyrotropic component sustains the positive reconnection electric field. The dimension of this single-scale diffusion region is proportional to the ion-electron hybrid inertial length (dide)1∕2 based on the background density and weakly depends on the background βe with the 0.25th power. These firm scalings allow us to predict observable dimensions in real space which are indeed in reasonable agreement with past in situ spacecraft observations in the Earth's magnetotail and have important implications for future observations with higher resolutions such as the NASA Magnetospheric Multiscale (MMS) mission.

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