Deriving precise parameters for cool solar-type stars. Optimizing the iron line list

TL;DR

This study refines spectroscopic parameters for cool solar-type stars by optimizing the iron line list, resulting in more accurate temperature estimates and improved abundance ratio consistency, especially for stars below 5000 K.

Contribution

The paper introduces a new optimized iron line list for spectroscopic analysis, enhancing temperature accuracy for cool stars compared to previous methods.

Findings

Reduced temperature discrepancies for stars below 5000 K.

Improved homogeneity in temperature estimates across the sample.

Better consistency in abundance ratios like [Cr I/Cr II] and [Ti I/Ti II].

Abstract

Temperature, surface gravity, and metallicitity are basic stellar atmospheric parameters necessary to characterize a star. We aim to improve the description of the spectroscopic temperatures especially for the cooler stars where the differences with the Infrared Flux Method are higher, as presented in previous work. Our spectroscopic analysis is based on the iron excitation and ionization balance, assuming Kurucz model atmospheres in LTE. The abundance analysis is determined using the code MOOG. We optimize the line list using a cool star with high resolution and high signal-to-noise spectrum, as a reference in order to check for weak, isolated lines. We test the quality of the new line list by re-deriving stellar parameters for 451 stars with high resolution and signal-to-noise HARPS spectra, that were analyzed in a previous work with a larger line list. The comparison in temperatures between this work and the latest IRFM shows that the differences for the cooler stars are significantly smaller and more homogeneously distributed than in previous studies for stars with temperatures below 5000 K. We use the new line list to re-derive parameters for some of the cooler stars that host planets. Finally, we present the impact of the new temperatures on the [Cr I/Cr II] and [Ti I/Ti II] abundance ratios that previously showed systematic trends with temperature.