Kea: a new tool to obtain stellar parameters from low to moderate signal/noise and high-resolution Echelle spectra

TL;DR

Kea is a new spectroscopic fitting tool designed to accurately derive stellar parameters from low to moderate signal-to-noise, high-resolution spectra, aiding analysis of large astronomical datasets like Kepler reconnaissance spectra.

Contribution

This paper introduces Kea, a novel method that uses synthetic spectra libraries and calibration on standard stars to determine stellar parameters from challenging spectra.

Findings

Achieves 100 K accuracy in effective temperature

Provides 0.12 dex precision in metallicity

Attains 0.18 dex accuracy in surface gravity

Abstract

In this paper we describe Kea a new spectroscopic fitting method to derive stellar parameters from moderate to low signal/noise, high-resolution spectra. We developed this new tool to analyze the massive data set of the Kepler mission reconnaissance spectra that we have obtained at McDonald Observatory. We use Kea to determine effective temperatures (T_eff), metallicity ([Fe/H]), surface gravity (log g) and projected rotational velocity (v sin i). Kea compares the observations to a large library of synthetic spectra that covers a wide range of different T_eff, [Fe/H] and log g values. We calibrated Kea on observations of well-characterized standard stars (the Kepler field "platinum" sample) which range in T_eff from 5000 to 6500 K, in [Fe/H] from -0.5 to +0.4 dex and in log g from 3.2 to 4.6 dex. We then compared the Kea results from reconnaissance spectra of 45 KOIs (Kepler Object of Interest) to stellar parameters derived from higher signal/noise spectra obtained with Keck/HIRES. We find typical uncertainties of 100 K in T_eff, 0.12 dex in [Fe/H] and 0.18 dex in log g.