相关论文: The IACOB project: A grid-based automatic tool for…

In this paper, we investigate the photometric variability of magnetic O-type stars. Such stars possess oblique, predominantly dipolar magnetic fields that confine their winds roughly axisymmetrically about the magnetic equator, thus forming…

Upcoming large-scale spectroscopic surveys with e.g. WEAVE and 4MOST will provide thousands of spectra of massive stars, which need to be analysed in an efficient and homogeneous way. Usually, studies of massive stars are limited to samples…

Current and future large astronomical surveys will yield multiparameter databases on millions or even billions of objects. The scientific exploitation of these will require powerful, robust, and automated classification tools tailored to…

Modern spectroscopic surveys combined with Gaia distances are enabling reliable estimates of fundamental parameters for hundreds of Galactic O-type stars and the full range of spectral types and luminosity classes. Here we provide updated,…

We present first results from the quantitative spectroscopic analysis of 266 Galactic O-type stars targeted by the IACOB and OWN surveys (implying the largest sample of stars of this type analyzed homogeneously). We also evaluate what is…

We present the Stagger-grid, a comprehensive grid of time-dependent, 3D hydrodynamic model atmospheres for late-type stars with realistic treatment of radiative transfer, covering a wide range in stellar parameters. This grid of 3D models…

The fast classification of new variable stars is an important step in making them available for further research. Selection of science targets from large databases is much more efficient if they have been classified first. Defining the…

This paper deals with the state estimation of stochastic models with continuous dynamics. The aim is to incorporate spectral differentiation methods into the solution to the Fokker-Planck equation in grid-based state estimation routine,…

Technical description of the new project called All Sky Automated Survey and results of the tests of our prototype instrument are presented. The ultimate goal of this project is photometric monitoring of the large area of the sky with fully…

The goal of AIMS (Asteroseismic Inference on a Massive Scale) is to estimate stellar parameters and credible intervals/error bars in a Bayesian manner from a set of asteroseismic frequency data and so-called classical constraints. To…

Stellar rotation is an important parameter in the evolution of massive stars. Accurate and reliable measurements of projected rotational velocities in large samples of OB stars are crucial to confront the predictions of stellar evolutionary…

We aim to extend and test the classifiers presented in a previous work against an independent dataset. We complement the assessment of the validity of the classifiers by applying them to the set of OGLE light curves treated as variable…

We present a software package, IDA, which can easily handle two-dimensional spectroscopy data. IDA has been written in IDL and offers a window-based interface. The available tools can visualize a recovered image from spectra at any desired…

We developed a 2D Finite-Difference Time-Domain (FDTD) method for modeling a space-time modulated guidestar targeting wavefront shaping applications in disordered media. Space-time modulation in general (a particular example being the…

We present a comprehensive grid of synthetic stellar-atmosphere spectra, suitable for the analysis of high resolution spectra of hydrogen-deficient post-Asymptotic Giant Branch (post-AGB) objects hotter than 50000 K, migrating along the…

We present a massive spectroscopic survey of Galactic O stars, GOSSS, based on new, high signal-to-noise ratio, R~2500 blue-violet digital observations from both hemispheres. The sample size and selection criteria; the relationship between…

Statistical pattern recognition methods have provided competitive solutions for variable star classification at a relatively low computational cost. In order to perform supervised classification, a set of features is proposed and used to…

Blue supergiants (BSGs) are important objects to study the intermediate phases of massive star evolution, helping to constrain evolutionary models. However, the lack of a holistic study of a statistically significant and unbiased sample of…

In this paper we have analyzed 25 Galactic O and early B-stars by means of H and K band spectroscopy, with the primary goal to investigate to what extent a lone near-IR spectroscopy is able to recover stellar and wind parameters derived in…

We develop a novel method based on machine learning principles to achieve optimal initiation of CPU-intensive computations for forward asteroseismic modeling in a multi-D parameter space. A deep neural network is trained on a precomputed…