MagneToRE: Mapping the 3-D Magnetic Structure of the Solar Wind Using a Large Constellation of Nanosatellites

Unlike the vast majority of astrophysical plasmas, the solar wind is accessible to spacecraft, which for decades have carried in-situ instruments for directly measuring its particles and fields. Though such measurements provide precise and detailed information, a single spacecraft on its own cannot...

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Veröffentlicht in:Frontiers in astronomy and space sciences 2021-07, Vol.8
Hauptverfasser: Maruca, Bennett A., Agudelo Rueda, Jeffersson A., Bandyopadhyay, Riddhi, Bianco, Federica B., Chasapis, Alexandros, Chhiber, Rohit, DeWeese, Haley, Matthaeus, William H., Miles, David M., Qudsi, Ramiz A., Richardson, Michael J., Servidio, Sergio, Shay, Michael A., Sundkvist, David, Verscharen, Daniel, Vines, Sarah K., Westlake, Joseph H., Wicks, Robert T.
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Sprache:eng
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Zusammenfassung:Unlike the vast majority of astrophysical plasmas, the solar wind is accessible to spacecraft, which for decades have carried in-situ instruments for directly measuring its particles and fields. Though such measurements provide precise and detailed information, a single spacecraft on its own cannot disentangle spatial and temporal fluctuations. Even a modest constellation of in-situ spacecraft, though capable of characterizing fluctuations at one or more scales, cannot fully determine the plasma’s 3-D structure. We describe here a concept for a new mission, the Magnetic Topology Reconstruction Explorer (MagneToRE), that would comprise a large constellation of in-situ spacecraft and would, for the first time, enable 3-D maps to be reconstructed of the solar wind’s dynamic magnetic structure. Each of these nanosatellites would be based on the CubeSat form-factor and carry a compact fluxgate magnetometer. A larger spacecraft would deploy these smaller ones and also serve as their telemetry link to the ground and as a host for ancillary scientific instruments. Such an ambitious mission would be feasible under typical funding constraints thanks to advances in the miniaturization of spacecraft and instruments and breakthroughs in data science and machine learning.
ISSN:2296-987X
2296-987X
DOI:10.3389/fspas.2021.665885