Using Doppler Imaging to model stellar activity and search for planets around Sun-like stars

TL;DR

This study demonstrates that Doppler Imaging, traditionally used for rapidly-rotating stars, can be adapted to Sun-like stars for modeling stellar activity and searching for low-mass exoplanets using high-resolution spectra.

Contribution

It shows that traditional Doppler Imaging algorithms can be applied to Sun-like stars with new spectrographs, enabling activity modeling and planet detection with comparable accuracy to advanced methods.

Findings

Doppler Imaging can retrieve Sun's surface brightness with ~36° resolution.

RV residuals after DI correction are about 0.6 m/s, similar to current techniques.

DI can detect planets with periods longer than ~100 days, with accurate mass estimates.

Abstract

Doppler Imaging (DI) is a well-established technique to map a physical field at a stellar surface from a time series of high-resolution spectra. In this proof-of-concept study, we aim to show that traditional DI algorithms, originally designed for rapidly-rotating stars, have also the ability to model the activity of Sun-like stars, when observed with new-generation highly-stable spectrographs, and search for low-mass planets around them. We used DI to retrieve the relative brightness distribution at the surface of the Sun from radial velocity (RV) observations collected by HARPS-N between 2022 and 2024. The brightness maps obtained with DI have a typical angular resolution of about 36 degrees and are a good match to low-resolution disc-resolved Dopplergrams of the Sun at epochs when the absolute, disc-integrated RV exceeds ~2 m/s. The RV residuals after DI correction exhibit a dispersion of about 0.6 m/s, comparable with existing state-of-the-art activity correction techniques. Using planet injection-recovery tests, we also show that DI can be a powerful tool for blind planet searches, so long as the orbital period is larger than ~100days (i.e. 3 to 4 stellar rotation periods), and that it yields planetary mass estimates with an accuracy comparable to, for example, multi-dimensional Gaussian process regression. Finally, we highlight some limitations of traditional DI algorithms, which should be addressed to make DI a reliable alternative to state-of-the-art RV-based planet search techniques.