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Determining the Photoelectron Energy Distribution using Arecibo Plasma Lines

Aidan
Thayer
Center for Solar-Terrestrial Research, New Jersey Institute of Technology
Abstract text

The incoherent scatter radar telescope that operated at Arecibo Observatory from 1963 to 2020 provided unparalleled resolution in imaging the upper regions of our atmosphere with data on plasma density, temperature, and line of sight velocity. The scale of the radar dish coupled with a software defined USRP receiver installed in 2015 allowed for scientists to record the plasma line in unprecedented resolution. The improved measurements of plasma lines resulted in new observations of striations or bands in the signal power that changed as a function of plasma density and aspect angle. Work by Longley et al4 found strong evidence for these bands being caused by the natural grouping of the suprathermal electron populations at ionization energies consistent with those of the species known to be present at the altitudes observed. This initial work continues and expands upon the work of Longley et al in furthering the predictive theory developed there by using an inverse framework in which the relative populations of suprathermal electrons at key ionization energies are fit for during multiple Arecibo experiments. The inverse algorithm for characterizing photoelectron distribution as a function of altitude is broken down step by step and explained for a single range gate and time stamp. We also investigate the effects of an anisotropic photoelectron distribution on the up versus down shifted plasma lines.

4: Longley, W. J., Vierinen, J., Sulzer, M. P., Varney, R. H., Erickson, P. J., & Perillat, P. (2021). An explanation for Arecibo plasma line power striations. Journal of Geophysical Research: Space Physics, 126, e2020JA028734. https://doi.org/10.1029/2020JA028734

Authors
Aidan Thayer, Center for Solar-Terrestrial Research, New Jersey Institute of Technology, Newark, NJ
William J Longley, Center for Solar-Terrestrial Research, New Jersey Institute of Technology, Newark, NJ
Nathaniel Sebastian Vargas, Department of Data Science, New Jersey Institute of Technology, Newark, NJ
Lindsay V Goodwin, Center for Solar-Terrestrial Research, New Jersey Institute of Technology, Newark, NJ
Philip J Erickson, Massachusetts Institute of Technology, Haystack Observatory, Westford, MA
Nestor Aponte, Massachusetts Institute of Technology, Haystack Observatory, Westford, MA
Student in poster competition
Poster category
DATA - Data Assimilation, Data Analytics, Methods and Management
Poster number
14