Spectrum radial velocity analyser (SERVAL). High-precision radial velocities and two alternative spectral indicators

TL;DR

SERVAL is a high-precision, publicly available Python tool that measures stellar radial velocities and introduces spectral diagnostics like the chromatic index and differential line width to identify stellar activity effects.

Contribution

We developed the SERVAL algorithm, providing high-precision RV measurements and novel spectral indicators to analyze stellar activity in high-resolution spectra.

Findings

SERVAL achieves 1 m/s RV precision with HARPS data.

The chromatic index effectively identifies activity-induced RV variations.

Differential line width serves as an alternative stellar activity indicator.

Abstract

Context: The CARMENES survey is a high-precision radial velocity (RV) programme that aims to detect Earth-like planets orbiting low-mass stars. Aims: We develop least-squares fitting algorithms to derive the RVs and additional spectral diagnostics implemented in the SpEctrum Radial Velocity Analyser (SERVAL), a publicly available python code. Methods: We measured the RVs using high signal-to-noise templates created by coadding all available spectra of each star.We define the chromatic index as the RV gradient as a function of wavelength with the RVs measured in the echelle orders. Additionally, we computed the differential line width by correlating the fit residuals with the second derivative of the template to track variations in the stellar line width. Results: Using HARPS data, our SERVAL code achieves a RV precision at the level of 1m/s. Applying the chromatic index to CARMENES data of the active star YZ CMi, we identify apparent RV variations induced by stellar activity. The differential line width is found to be an alternative indicator to the commonly used full width half maximum. Conclusions: We find that at the red optical wavelengths (700--900 nm) obtained by the visual channel of CARMENES, the chromatic index is an excellent tool to investigate stellar active regions and to identify and perhaps even correct for activity-induced RV variations.