Data Mining Reconstruction of Magnetotail Reconnection and Implications for Its First-Principle Modeling
Magnetic reconnection is a fundamental process providing topological changes of the magnetic field, reconfiguration of space plasmas and release of energy in key space weather phenomena, solar flares, coronal mass ejections and magnetospheric substorms. Its multiscale nature is difficult to study in...
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Frontiers Media S.A.
2021-04-01
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| Series: | Frontiers in Physics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphy.2021.644884/full |
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doaj-a2d62dbe02824a1894d29bd39b413a592021-04-21T05:06:59ZengFrontiers Media S.A.Frontiers in Physics2296-424X2021-04-01910.3389/fphy.2021.644884644884Data Mining Reconstruction of Magnetotail Reconnection and Implications for Its First-Principle ModelingMikhail Sitnov0Grant Stephens1Tetsuo Motoba2Marc Swisdak3Applied Physics Laboratory, The Johns Hopkins University, Laurel, MD, United StatesApplied Physics Laboratory, The Johns Hopkins University, Laurel, MD, United StatesApplied Physics Laboratory, The Johns Hopkins University, Laurel, MD, United StatesInstitute for Research in Electronics and Applied Physics, University of Maryland, College Park, MD, United StatesMagnetic reconnection is a fundamental process providing topological changes of the magnetic field, reconfiguration of space plasmas and release of energy in key space weather phenomena, solar flares, coronal mass ejections and magnetospheric substorms. Its multiscale nature is difficult to study in observations because of their sparsity. Here we show how the lazy learning method, known as K nearest neighbors, helps mine data in historical space magnetometer records to provide empirical reconstructions of reconnection in the Earth’s magnetotail where the energy of solar wind-magnetosphere interaction is stored and released during substorms. Data mining reveals two reconnection regions (X-lines) with different properties. In the mid tail (∼30RE from Earth, where RE is the Earth’s radius) reconnection is steady, whereas closer to Earth (∼20RE) it is transient. It is found that a similar combination of the steady and transient reconnection processes can be reproduced in kinetic particle-in-cell simulations of the magnetotail current sheet.https://www.frontiersin.org/articles/10.3389/fphy.2021.644884/fulldata mining and knowledge discoverynearest neighbor methodmagnetospheremagnetotailmagnetic reconnectionspace weather |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Mikhail Sitnov Grant Stephens Tetsuo Motoba Marc Swisdak |
| spellingShingle |
Mikhail Sitnov Grant Stephens Tetsuo Motoba Marc Swisdak Data Mining Reconstruction of Magnetotail Reconnection and Implications for Its First-Principle Modeling Frontiers in Physics data mining and knowledge discovery nearest neighbor method magnetosphere magnetotail magnetic reconnection space weather |
| author_facet |
Mikhail Sitnov Grant Stephens Tetsuo Motoba Marc Swisdak |
| author_sort |
Mikhail Sitnov |
| title |
Data Mining Reconstruction of Magnetotail Reconnection and Implications for Its First-Principle Modeling |
| title_short |
Data Mining Reconstruction of Magnetotail Reconnection and Implications for Its First-Principle Modeling |
| title_full |
Data Mining Reconstruction of Magnetotail Reconnection and Implications for Its First-Principle Modeling |
| title_fullStr |
Data Mining Reconstruction of Magnetotail Reconnection and Implications for Its First-Principle Modeling |
| title_full_unstemmed |
Data Mining Reconstruction of Magnetotail Reconnection and Implications for Its First-Principle Modeling |
| title_sort |
data mining reconstruction of magnetotail reconnection and implications for its first-principle modeling |
| publisher |
Frontiers Media S.A. |
| series |
Frontiers in Physics |
| issn |
2296-424X |
| publishDate |
2021-04-01 |
| description |
Magnetic reconnection is a fundamental process providing topological changes of the magnetic field, reconfiguration of space plasmas and release of energy in key space weather phenomena, solar flares, coronal mass ejections and magnetospheric substorms. Its multiscale nature is difficult to study in observations because of their sparsity. Here we show how the lazy learning method, known as K nearest neighbors, helps mine data in historical space magnetometer records to provide empirical reconstructions of reconnection in the Earth’s magnetotail where the energy of solar wind-magnetosphere interaction is stored and released during substorms. Data mining reveals two reconnection regions (X-lines) with different properties. In the mid tail (∼30RE from Earth, where RE is the Earth’s radius) reconnection is steady, whereas closer to Earth (∼20RE) it is transient. It is found that a similar combination of the steady and transient reconnection processes can be reproduced in kinetic particle-in-cell simulations of the magnetotail current sheet. |
| topic |
data mining and knowledge discovery nearest neighbor method magnetosphere magnetotail magnetic reconnection space weather |
| url |
https://www.frontiersin.org/articles/10.3389/fphy.2021.644884/full |
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