EXPRES. II. Searching for Planets Around Active Stars: A Case Study of HD 101501

TL;DR

This study demonstrates how Gaussian Process regression, combined with high-cadence observations, can effectively model stellar activity in radial velocity data to detect low-mass planets around active stars like HD 101501.

Contribution

It provides a case study applying GP models to high-precision radial velocity data, emphasizing the importance of observation cadence for planet detection.

Findings

GP models can accurately account for stellar activity in RV data.

High-cadence observations improve the detection of low-mass planets.

Sparse sampling can cause GPs to absorb potential planetary signals.

Abstract

By controlling instrumental errors to below 10 cm/s, the EXtreme PREcision Spectrograph (EXPRES) allows for a more insightful study of photospheric velocities that can mask weak Keplerian signals. Gaussian Processes (GP) have become a standard tool for modeling correlated noise in radial velocity datasets. While GPs are constrained and motivated by physical properties of the star, in some cases they are still flexible enough to absorb unresolved Keplerian signals. We apply GP regression to EXPRES radial velocity measurements of the 3.5 Gyr old chromospherically active Sun-like star, HD 101501. We obtain tight constraints on the stellar rotation period and the evolution of spot distributions using 28 seasons of ground-based photometry, as well as recent $TESS$ data. Light curve inversion was carried out on both photometry datasets to reveal the spot distribution and spot evolution timescales on the star. We find that the $> 5$ m/s rms radial velocity variations in HD 101501 are well-modeled with a GP stellar activity model without planets, yielding a residual rms scatter of 45 cm/s. We carry out simulations, injecting and recovering signals with the GP framework, to demonstrate that high-cadence observations are required to use GPs most efficiently to detect low-mass planets around active stars like HD 101501. Sparse sampling prevents GPs from learning the correlated noise structure and can allow it to absorb prospective Keplerian signals. We quantify the moderate to high-cadence monitoring that provides the necessary information to disentangle photospheric features using GPs and to detect planets around active stars.