Separating planetary reflex Doppler shifts from stellar variability in the wavelength domain
A. Collier Cameron, E. B. Ford, S. Shahaf, S. Aigrain, X. Dumusque, R., D. Haywood, A. Mortier, D. F. Phillips, L. Buchhave, M. Cecconi, H. Cegla, R., Cosentino, M. Cretignier, A. Ghedina, M. Gonzalez, D. W. Latham, M. Lodi, M., Lopez-Morales, G. Micela, E. Molinari, F. Pepe

TL;DR
This paper introduces a novel data-driven method to distinguish planetary Doppler signals from stellar activity-induced variations in high-precision radial velocity measurements, enhancing the detection of Earth-like exoplanets.
Contribution
The authors develop an ACF-based technique that effectively separates stellar activity signals from planetary signals in radial velocity data, demonstrated on solar observations with high accuracy.
Findings
Successfully removed stellar activity signals from solar radial velocity data.
Recovered synthetic low-mass planet signals with ~6.6 cm/s precision.
Enabled detection of terrestrial-mass exoplanets across various orbital periods.
Abstract
Stellar magnetic activity produces time-varying distortions in the photospheric line profiles of solar-type stars. These lead to systematic errors in high-precision radial-velocity measurements, which limit efforts to discover and measure the masses of low-mass exoplanets with orbital periods of more than a few tens of days. We present a new data-driven method for separating Doppler shifts of dynamical origin from apparent velocity variations arising from variability-induced changes in the stellar spectrum. We show that the autocorrelation function (ACF) of the cross-correlation function used to measure radial velocities is effectively invariant to translation. By projecting the radial velocities on to a subspace labelled by the observation identifiers and spanned by the amplitude coefficients of the ACF's principal components, we can isolate and subtract velocity perturbations caused…
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