From Particles to Fluids: Dimensionality Reduction for Non-Maxwellian Plasma Velocity Distributions Validated in the Fluid Context
This code accompanies two papers: a short conference proceedings paper to the NeurIPS 2022 conference, and a full-length version of that paper published early the following year in Frontiers in Astronomy and Space Sciences. The title of the NeurIPS paper is above, and the full-length paper is titled "The Impact of Dimensionality Reduction of Ion Counts Distributions on Preserving Moments with Applications to Data Compression".
This code trains a learned, patch-based, dimensionality reductive method for plasma ion counts distributions using data from the MMS satellite mission's FPI/DIS instrument. It requires data from MMS FPI/DIS, available for free online at the MMS Science Data Center.
References
- da Silva, Daniel E., et al. "The Impact of Dimensionality Reduction of Ion Counts Distributions on Preserving Moments with Applications to Data Compression." Frontiers in Astronomy and Space Sciences 9: 431.
- da Silva, Daniel, and Christopher Bard. "From Particles to Fluids: Dimensionality Reduction for Non-Maxwellian Plasma Velocity Distributions Validated in the Fluid Context."
- da Silva, Daniel, et al. "Neural network repair of Lossy compression Artifacts in the September 2015 to March 2016 duration of the MMS/FPI data set." Journal of Geophysical Research: Space Physics 125.4 (2020): e2019JA027181.
- Pollock, C., et al. "Fast plasma investigation for magnetospheric multiscale." Space Science Reviews 199.1 (2016): 331-406.
- Burch, J. L., et al. "Magnetospheric multiscale overview and science objectives." Space Science Reviews 199.1 (2016): 5-21.
Contact
The author can be reached at daniel.e.dasilva@nasa.gov or mail@danieldasilva.org.