Upgrades to the MAVEN Echelle Data Reduction Pipeline: New Calibration Standard and Improved Faint Emission Detection Algorithm at Lyman-α - INSU - Institut national des sciences de l'Univers Accéder directement au contenu
Article Dans Une Revue (Article De Synthèse) Earth and Space Science Année : 2023

Upgrades to the MAVEN Echelle Data Reduction Pipeline: New Calibration Standard and Improved Faint Emission Detection Algorithm at Lyman-α

Résumé

The Mars Atmosphere and Volatile Evolution (MAVEN) mission instrument suite includes an ultraviolet echelle spectrograph with high-spectral resolution designed to resolve D and H Lyman-α emissions. The high-spectral resolution mode was previously characterized in the lab and in the cruise phase to Mars and had been calibrated using observations and models of interplanetary hydrogen Lyman-α emissions. This work presents improved characterizations of the high-spectral resolution mode using in-orbit observations that allow for more robust detections of the faint D Lyman-α emission line. Additionally, the instrument was re-calibrated using simultaneous and comparable observations made with the Hubble Space Telescope high-spectral resolution instrument. Comparisons to Lyman-α observations made with the low-resolution UV channel on the spectrometer, that had been calibrated with stars, showed consistency in the brightness values for measurements obtained at similar observational conditions. The combined upgrades to the faint-emission fitting and new calibration techniques of the MAVEN echelle channel have resulted in an improved data-reduction pipeline with favorable implications for the science utility of D and H Lyman-α emissions.
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Dates et versions

insu-03911930 , version 1 (23-12-2022)
insu-03911930 , version 2 (27-04-2023)

Identifiants

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M. Mayyasi, J. Clarke, Jean-Loup Bertaux, J. Deighan, D. Bhattacharyya, et al.. Upgrades to the MAVEN Echelle Data Reduction Pipeline: New Calibration Standard and Improved Faint Emission Detection Algorithm at Lyman-α. Earth and Space Science, 2023, 10 (4), pp.e2022EA002602. ⟨10.1029/2022ea002602⟩. ⟨insu-03911930v2⟩
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