相关论文: A new method for the inversion of atmospheric para…
This work addresses a procedure to estimate fundamental stellar parameters such as T eff , logg, [Fe/H], and v sin i using a dimensionality reduction technique called Principal Component Analysis (PCA), applied to a large database of…
We present a method for deriving stellar fundamental parameters. It is based on a regularized sliced inverse regression (RSIR). We first tested it on noisy synthetic spectra of A, F, G, and K-type stars, and inverted simultaneously their…
We show how the range of application of the principal component analysis-based inversion method of Paletou et al. (2015) can be extended to late-type stars data. Besides being an extension of its original application domain, for FGK stars,…
The general context of this study is the inversion of stellar fundamental parameters from high-resolution Echelle spectra. We aim at developing a fast and reliable tool for the post-processing of spectra produced, in particular, by the…
Our aim is to evaluate fundamental parameters from the analysis of the electromagnetic spectra of stars. We may use $10^3$-$10^5$ spectra; each spectrum being a vector with $10^2$-$10^4$ coordinates. We thus face the so-called "curse of…
DEM analysis is a major diagnostic tool for stellar atmospheres. But both its derivation and its interpretation are notably difficult because of random and systematic errors, and the inverse nature of the problem. We use simulations with…
The derivation of the effective temperature of a star is a critical first step in a detailed spectroscopic analysis. Spectroscopic methods suffer from systematic errors related to model simplifications. Photometric methods may be more…
We present a spectroscopic and photometric calibration to derive effective temperatures $T_{\mathrm{eff}}$ and metallicities [Fe/H] for M dwarfs, based on a Principal Component Analysis of 147 spectral indices measured off moderate…
For many transitions, atomic data, such as the oscillator strength (log(gf)) and the central wavelength of the line, are poorly constrained or even unknown. We present and test a new inversion method that infers atomic line parameters and…
This work describes a procedure to derive several fundamental parameters such as the effective temperature, surface gravity, equatorial rotational velocity and microturbulent velocity. In this work, we have written a numerical procedure in…
The increasing number of spectra gathered by spectroscopic sky surveys and transiting exoplanet follow-up has pushed the community to develop automated tools for atmospheric stellar parameters determination. Here we present a novel approach…
The inference of the underlying state of the plasma in the solar chromosphere remains extremely challenging because of the nonlocal character of the observed radiation and plasma conditions in this layer. Inversion methods allow us to…
We present interferometric observations of 7 main-sequence and 3 giant stars with spectral types from B2 to F6 using the PAVO beam combiner at the CHARA array. We have directly determined the angular diameters for these objects with an…
Regression methods based in Machine Learning Algorithms (MLA) have become an important tool for data analysis in many different disciplines. In this work, we use MLA in an astrophysical context; our goal is to measure the mean longitudinal…
The determination of stellar effective temperature ($T_{\mathrm{eff}}$) in F, G, and K stars using H$\alpha$ profile fitting is a quite remarkable and powerful tool, because it practically does not depend on other atmospheric parameters and…
We have assessed how well stellar parameters (T_eff, logg and [Fe/H]) can be retrieved from low-resolution dispersed images to be obtained by the DIVA satellite. Although DIVA is primarily an all-sky astrometric mission, it will also obtain…
High-resolution spectroscopy of strong chromospheric absorption lines delivers nowadays several millions of spectra per observing day, when using fast scanning devices to cover large regions on the solar surface. Therefore, fast and robust…
This paper reports on the application of the supervised machine-learning algorithm to the stellar effective temperature regression for the second $Gaia$ data release, based on the combination of the stars in four spectroscopic surveys:…
Since the early 1970s, inversion techniques have become the most useful tool for inferring the magnetic, dynamic, and thermodynamic properties of the solar atmosphere. The intrinsic model dependence makes it necessary to formulate specific…
The general context of this study is the inversion of stellar fundamental parameters from high-resolution Echelle spectra. We aim indeed at developing a fast and reliable tool for the post-processing of spectra produced by Espadons and…