Derived Electron Densities from Linear Polarization Observations of the Visible-Light Corona During the 14 December 2020 Total Solar Eclipse

Liam Edwards*, Kaine A. Bunting, Brad Ramsey, Matthew Gunn, Tomos Fearn, Thomas Knight, Gabriel Domingo Muro, Huw Morgan

*Corresponding author for this work

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Abstract

A new instrument was designed to take visible-light (VL) polarized brightness (pB) observations of the solar corona during the 14 December 2020 total solar eclipse. The instrument, called the Coronal Imaging Polarizer (CIP), consisted of a 16 MP CMOS detector, a linear polarizer housed within a piezoelectric rotation mount, and an f-5.6, 200 mm DSLR lens. Observations were successfully obtained, despite poor weather conditions, for five different exposure times (0.001 s, 0.01 s, 0.1 s, 1 s, and 3 s) at six different orientation angles of the linear polarizer (0 , 30 , 60 , 90 , 120 , and 150 ). The images were manually aligned using the drift of background stars in the sky and images of different exposure times were combined using a simple signal-to-noise ratio cut. The polarization and brightness of the local sky were also estimated and the observations were subsequently corrected. The pB of the K-corona was determined using least-squares fitting and radiometric calibration was done relative to the Mauna Loa Solar Observatory (MLSO) K-Cor pB observations from the day of the eclipse. The pB data was then inverted to acquire the coronal electron density, ne , for an equatorial streamer and a polar coronal hole, which agreed very well with previous studies. The effect of changing the number of polarizer angles used to compute the pB is also discussed and it is found that the results vary by up to ≈ 13 % when using all six polarizer angles versus only a select of three angles.

Original languageEnglish
Article number140
Number of pages22
JournalSolar Physics
Volume298
Issue number12
DOIs
Publication statusPublished - 05 Dec 2023

Keywords

  • Visible
  • Optical
  • Polarization
  • Eclipse observations
  • Instrumentation and data management
  • Spectrum

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