Stellar activity correction using PCA decomposition of shells
M. Cretignier, X. Dumusque, F. Pepe

TL;DR
This paper introduces a PCA-based method to analyze spectral shells for improved correction of stellar activity signals in radial velocity data, enhancing the detection of Earth-like planets.
Contribution
The study demonstrates a novel PCA decomposition technique of spectral shells that effectively separates stellar activity signals from planetary signals in RV measurements.
Findings
Successfully disentangled planetary signals from instrumental systematics.
Reduced RV residuals from 2.44 m/s to 1.73 m/s on HD128621.
Mitigated stellar activity signals at stellar rotation and alias periods.
Abstract
Context. Stellar activity and instrumental signals are the main limitations to the detection of Earth-like planets using the radial velocity (RV) technique. Recent studies show that the key to mitigating those perturbing effects might reside in analysing the spectra themselves, rather than the RV time series and a few activity proxies. Aims. The goal of this paper is to demonstrate that we can reach further improvement in RV precision by performing a principal component analysis (PCA) decomposition of the shell time series, with the shell as the projection of a spectrum onto the spacenormalised flux versus flux gradient. Methods. By performing a PCA decomposition of shell time series, it is possible to obtain a basis of first-order spectral variations that are not related to Keplerian motion. The time coeffcients associated with this basis can then be used to correct for non-Dopplerian…
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