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arXiv · 2204.09014

Leveraging space-based data from the nearest Solar-type star to better understand stellar activity signatures in radial velocity data

Tamar Ervin·Samuel Halverson·Abigail Burrows·Neil Murphy·Arpita Roy·Raphaelle D. Haywood·Federica Rescigno·Chad F. Bender·Andrea S. J. Lin·Jennifer Burt·Suvrath Mahadevan
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Abstract

Stellar variability is a key obstacle in reaching the sensitivity required to recover Earth-like exoplanetary signals using the radial velocity (RV) detection method. To explore activity signatures in Sun-like stars, we present SolAster, a publicly-distributed analysis pipeline that allows for comparison of space-based measurements with ground-based disk-integrated RVs. Using high spatial resolution Dopplergrams, magnetograms, and continuum filtergrams from the Helioseismic and Magnetic Imager (HMI) aboard the Solar Dynamics Observatory (SDO), we estimate 'Sun-as-a-star' disk-integrated RVs due to rotationally modulated flux imbalances and convective blueshift suppression, as well as other observables such as unsigned magnetic flux. Comparing these measurements with ground-based RVs from the NEID instrument, which observes the Sun daily using an automated solar telescope, we find a strong relationship between magnetic activity indicators and RV variation, supporting efforts to examine unsigned magnetic flux as a proxy for stellar activity in slowly rotating stars. Detrending against measured unsigned magnetic flux allows us to improve the NEID RV measurements by ~20\% (~50 cm/s in a quadrature sum), yielding an RMS scatter of ~60 cm/s over five months. We also explore correlations between individual and averaged spectral line shapes in the NEID spectra and SDO-derived magnetic activity indicators, motivating future studies of these observables. Finally, applying SolAster to archival planetary transits of Venus and Mercury, we demonstrate the ability to recover small amplitude (< 50 cm/s) RV variations in the SDO data by directly measuring the Rossiter-McLaughlin (RM) signals.

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Tamar Ervin, Samuel Halverson, Abigail Burrows, Neil Murphy, Arpita Roy, Raphaelle D. Haywood, Federica Rescigno, Chad F. Bender, Andrea S. J. Lin, Jennifer Burt, Suvrath Mahadevan. 2022-04-19. Leveraging space-based data from the nearest Solar-type star to better understand stellar activity signatures in radial velocity data. https://doi.org/10.3847/1538-3881/ac67e6

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