ZASPE: A Code to Measure Stellar Atmospheric Parameters and their Covariance from Spectra

TL;DR

ZASPE is a new algorithm and code for accurately determining stellar atmospheric parameters and their uncertainties from high-resolution spectra of FGK stars, by focusing on sensitive spectral zones and estimating covariances.

Contribution

The paper introduces ZASPE, a novel method that improves parameter estimation accuracy and uncertainty quantification from stellar spectra, and evaluates synthetic spectral libraries for this purpose.

Findings

ZASPE accurately estimates stellar parameters from high-resolution spectra.

Existing spectral libraries are unsuitable for precise parameter determination.

A new synthetic spectral library was developed and validated.

Abstract

We describe the Zonal Atmospheric Stellar Parameters Estimator (ZASPE), a new algorithm, and its associated code, for determining precise stellar atmospheric parameters and their uncertainties from high resolution echelle spectra of FGK-type stars. ZASPE estimates stellar atmospheric parameters by comparing the observed spectrum against a grid of synthetic spectra only in the most sensitive spectral zones to changes in the atmospheric parameters. Realistic uncertainties in the parameters are computed from the data itself, by taking into account the systematic mismatches between the observed spectrum and the best-fit synthetic one. The covariances between the parameters are also estimated in the process. ZASPE can in principle use any pre-calculated grid of synthetic spectra. We tested the performance of two existing libraries (Coehelo et al. 2005, Husser et al. 2013) and we concluded that neither is suitable for computing precise atmospheric parameters. We describe a process to synthesise a new library of synthetic spectra that was found to generate consistent results when compared with parameters obtained with different methods (interferometry, asteroseismology, equivalent widths).