The atmospheric parameters of FGK stars using wavelet analysis of CORALIE spectra
Samuel Gill, Pierre. F. L. Maxted, Barry Smalley (Keele, University, UK)

TL;DR
This paper introduces a wavelet-based automated spectral analysis method for FGK stars using CORALIE spectra, enabling reliable determination of atmospheric parameters despite low signal-to-noise ratios.
Contribution
The study develops and validates a novel wavelet decomposition approach combined with Bayesian inference to analyze low-quality spectra for stellar atmospheric parameters.
Findings
Achieves 85K precision in effective temperature measurement.
Determines metallicity with 0.06 dex accuracy.
Reliable for spectra with SNR above 40.
Abstract
Atmospheric properties of F-,G- and K-type stars can be measured by spectral model fitting. These methods require data with good signal-to-noise ratio and reliable continuum normalisation. This is particularly challenging for the spectra we have obtained with the CORALIE \'{e}chelle spectrograph for FGK stars with transiting M-dwarf companions. The spectra tend to have low signal-to-noise ratios, which makes it difficult to analyse them using existing methods. Our aim is to create a reliable automated spectral analysis routine to determine , [Fe/H], from the CORALIE spectra of FGK stars. We use wavelet decomposition to distinguish between noise, continuum trends, and stellar spectral features in the CORALIE spectra. A subset of wavelet coefficients from the target spectrum are compared to those from a grid of models in a Bayesian framework to determine the…
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