Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
6
datasets available to search
ShareScore release 0.9.0
Dataset results
6 results for “Electron Diffusion Region”
List of Electron Diffusion Regions (EDR) observed by NASA/MMS
<p><strong>List of Electron Diffusion Regions (EDR) during the phases 1a & 1b of the NASA/MMS mission.</strong><br> EDR from Lenouvel_et_al._[2021] and Lenouvel_(unpublished) were detected with two distinct machine learning algorithms. The first algorithm (MLP) is detailed in Lenouvel_et_al._[2021]. Both algorithms (MLP and CNN) are described in Q. Lenouvel's PhD manuscript and in "Advanced Methods for Analyzing In-Situ Observations of Magnetic Reconnection" submitted to Space Science Reviews by Hasegawa et al..<br> For completeness, other EDR events reported in the literature are added to the list. All references are given below. Note that some events were observed by other MMS spacecraft at slightly different times.</p> <p>Burch, J. L., and T. D. Phan, Magnetic reconnection at the dayside magnetopause: Advances with MMS, Geophysical Research Letters, 43 (16), 8327–8338, https://doi.org/10.1002/2016GL069787, 2016.<br> Burch, J. L., et al., Electron-scale measurements of magnetic reconnection in space, Science, 352 (6290), aaf2939, https://doi.org/10.1126/science.aaf2939, 2016.<br> Chen, L.-J., et al., Electron energization and mixing observed by mms in the vicinity of an electron diffusion region during magnetopause reconnection, Geophysical Research Letters, 43 (12), 6036–6043, https://doi.org/10.1002/2016GL069215, 2016.<br> Chen, L.-J., et al., Electron diffusion region during magnetopause reconnection with an intermediate guide field: Magnetospheric multiscale observations, Journal of Geophysical Research: Space Physics, 122 (5), 5235–5246, https://doi.org/10.1002/2017JA024004, 2017.<br> Cozzani, G., et al., In situ spacecraft observations of a structured electron diffusion region during magnetopause reconnection, Phys. Rev. E 99, 043204 (2019); https://doi.org/10.1103/PhysRevE.99.043204<br> Dong, X.-C., et al., Observation of nonuniform energy dissipation in the electron diffusion region of magnetopause reconnection, Geophysical Research Letters, 48 (13), e2020GL091928, https://doi.org/10.1029/2020GL091928, 2021.<br> Ergun, R. E., et al., Drift waves, intense parallel electric fields, and turbulence associated with asymmetric magnetic reconnection at the magnetopause, Geophysical Research Letters, 44 (7), 2978–2986, https://doi.org/10.1002/2016GL072493, 2017.<br> Eriksson, S., et al., Magnetospheric multiscale observations of the electron diffusion region of large guide field magnetic reconnection, Phys. Rev. Lett., 117, 015,001, https://doi.org/10.1103/PhysRevLett.117.015001, 2016.<br> Fuselier, S. A., et al., Large-scale characteristics of reconnection diffusion regions and associated magnetopause crossings observed by mms, Journal of Geophysical Research: Space Physics, 122 (5), 5466–5486, https://doi.org/10.1002/2017JA024024, 2017.<br> Genestreti, K. J., et al., Mms observation of asymmetric reconnection supported by 3-d electron pressure divergence, Journal of Geophysical Research: Space Physics, 123 (3), 1806–1821, https://doi.org/10.1002/2017JA025019, 2018.<br> Graham, D. B., et al., Instability of agyrotropic electron beams near the electron diffusion region, Phys. Rev. Lett., 119, 025,101, https://doi.org/10.1103/PhysRevLett.119.025101, 2017.<br> Khotyaintsev, Y. V., et al., Electron jet of asymmetric reconnection, Geophysical Research Letters, 43 (11), 5571–5580, https://doi.org/10.1002/2016GL069064, 2016.<br> Lenouvel, Q., Identification par apprentissage machine et analyse de régions de diffusion électronique à la magnétopause terrestre observées par MMS, Thèse de doctorat en Astrophysique, Sciences de l'Espace, Planétologie, Université de Toulouse, http://thesesups.ups-tlse.fr/5558/, 2022.<br> Lenouvel, Q., et al., Identification of electron diffusion regions with a machine learning approach on mms data at the earth’s magnetopause, Earth and Space Science, 8 (5), e2020EA001530, https://doi.org/10.1029/2020EA001530, 2021.<br> Li, W. Y., et al., Electron Bernstein waves driven by electron crescents near the electron diffusion region, Nature Communications, 11 (1), 141, https://doi.org/10.1038/s41467-019-13920-w, 2020.<br> Norgren, C., et al., Finite gyroradius effects in the electron outflow of asymmetric magnetic reconnection, Geophysical Research Letters, 43 (13), 6724–6733, https://doi.org/10.1002/2016GL069205, 2016.<br> Phan, T. D., et al., Mms observations of electron-scale filamentary currents in the reconnection exhaust and near the x line, Geophysical Research Letters, 43 (12), 6060–6069, https://doi.org/10.1002/2016GL069212, 2016.<br> Webster, J. M., et al., Magnetospheric Multiscale Dayside Reconnection Electron Diffusion Region Events, Journal of Geophysical Research (Space Physics), 123 (6), 4858–4878, https://doi.org/10.1029/2018JA025245, 2018.</p> <p> </p>
Origin and Structure of Electromagnetic Generator Regions at the Edge of the Electron Diffusion Region
<p>The data included here is for an article submission to the Physics of Plasmas: MMS special Issue. There are electric field, magnetic field, and particle data files from MMS (cdf files). There are files from Particle-in-Cell simulations (xdmf files, h5 files, and a log file with run info). Included here is the python notebook (ipynb file) used to analyze the simulation data, and two IDL files (generator_fig.pro and Energy_Flux.pro) that were used to produce the panel plots of MMS data in the article.</p>
The Effects of Upper-Hybrid Waves on Energy Conversion in the Electron Diffusion Region
<p>The data from the simulations of upper-hybrid waves near the electron diffusion region. </p> <p>Read 'note.txt' for the description about the data. </p>
Data for Theory, Observations, and Simulations of Kinetic Entropy in a Magnetotail Electron Diffusion Region
<p>This .rar file contains the simulation data used in the paper titled "Theory, Observations, and Simulations of Kinetic Entropy in a Magnetotail ElectronDiffusion Region" along with needed instructions for reproducing the simulation plots shown in the paper. </p>
Energy Balance and Time Dependence of a Magnetotail Electron Diffusion Region
<p>The data sets and python notebook included are for a submitted manuscript to the Journal of Geophysical Review: Space Physics.</p> <p>An IDL save file has also been included which contains variables from a reconstruction of the event in the manuscript. The time variable in tt2000. Other variables are in units of nW/m^3 by default. <br> <br> The purpose of the work is to determine how electromagnetic energy is converted into plasma energy in the electron diffusion region of magnetic reconnection. Using both spacecraft data and simulations, we investigate how the terms in Poynting's theorem change as reconnection begins and evolves in time. </p>
Multi-scale coupling during magnetopause reconnection: interface between the electron and ion diffusion regions
<p>Output in IDL-save format from four frames of the two particle-in-cell simulations used in the manuscript. See manuscript (Appendix C) for simulation set-up. Unless otherwise specified, each of the following variables are given as NxM matrices, where N is the number of grid cells per row (X axis) and M is the number per column (Z axis). Among other variables, the data files named "frame#.sav" contain the following items, used in the paper:</p> <ul> <li>E[i]: the i (X, Y, or Z) component of the electric field vector</li> <li>B[i]: the i (X, Y, or Z) component of the magnetic field vector</li> <li>Ay: the Y component of the magnetic vector potential</li> <li>V[s][i]: the i (X, Y, or Z) component of the bulk velocity of species s (ions or electrons)</li> <li>den[s]: the number density of species s</li> <li>xx: N-element vector of the x location of each grid cell</li> <li>zz: M-element vector of the z location of each grid cell</li> </ul> <p>One other file, named "frame38_P.sav", gives each of the 6 unique elements of the ion and electron pressure tensor with the variables named as P[s][i][j], where i and j are X, Y, or Z and s is either i for ions or e for electrons. </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.