Related papers: Data-Driven Stellar Models
Massive stars condition the evolution of the interstellar medium by the amount of energy released during their lives and especially by their deaths as supernova explosions. The vast amounts of spectroscopic data for massive stars provided…
A new optical reddening model for the Solar neighborhood is presented. The model makes use of the large-scale properties of the dust layer in the Galaxy, and of the observed clumpiness in its distribution, and it is used to compute…
Probing properties of neutron stars from photometric observations of these objects helps us answer crucial questions at the forefront of multi-messenger astronomy, such as, what is behavior of highest density matter in extreme environments…
We present a new 3D map of interstellar dust reddening, covering three quarters of the sky (declinations greater than -30 degrees) out to a distance of several kiloparsecs. The map is based on high-quality stellar photometry of 800 million…
We explores the Pantheon+SH0ES dataset to identify patterns that can discriminate between different cosmological models. We focus on determining whether the behaviour of dark energy is consistent with the standard $\Lambda$CDM model or…
Photospheric radiation momentum is efficiently transferred by absorption through metal lines to the gaseous matter in the atmospheres of massive stars, sustaining strong winds and mass loss rates. Not only is this critical for the evolution…
We aim to prepare the machine-learning ground for the next generation of spectroscopic surveys, such as 4MOST and WEAVE. Our goal is to show that convolutional neural networks can predict accurate stellar labels from relevant spectral…
We present stellar parameter estimates for 939,457 southern FGK stars that are candidate targets for the TESS mission. Using a data-driven method similar to the CANNON, we build a model of stellar colours as a function of stellar…
We proposed a machine learning approach to identify and distinguish dusty stellar sources employing supervised and unsupervised methods and categorizing point sources, mainly evolved stars, using photometric and spectroscopic data collected…
Multi-band images of galaxies reveal a huge amount of information about their morphology and structure. However, inferring properties of the underlying stellar populations such as age, metallicity or kinematics from those images is…
Transmission spectroscopy is currently the technique best suited to study a wide range of planetary atmospheres, leveraging the filtering of a star's light by a planet's atmosphere rather than its own emission. However, as both a planet and…
Stellar streams provide one of the most promising avenues for constraining the global mass distribution of the Milky Way and the nature of dark matter (DM). The stream stars' kinematic "track" enables inference of large-scale properties of…
Based on luminosity contributions, we develop a spectroscopic modelling method to derive atmospheric parameters of component stars in binary systems. The method is designed for those spectra of binaries which show double-lined features due…
We present a mock catalog of Milky Way stars, matching in volume and depth the content of the Gaia data release 2 (GDR2). We generated our catalog using Galaxia, a tool to sample stars from a Besancon Galactic model, together with a…
With the help of model calculations we aim at reproducing the observational photometric findings for a large sample of well-characterised galactic C-type Mira variables losing mass at different rates. We used dynamic model atmospheres,…
A fundamental challenge for wide-field imaging surveys is obtaining follow-up spectroscopic observations: there are > $10^9$ photometrically cataloged sources, yet modern spectroscopic surveys are limited to ~few x $10^6$ targets. As we…
We study the spectroscopic and photometric properties of carbon stars. In the first paper of this series we focus on objects that can be described by hydrostatic models neglecting dynamical phenomena like pulsation and mass loss. As a…
I briefly introduce a database of models that describe the evolution of star clusters in several broad-band photometric systems. Models are based on the latest Padova stellar evolutionary tracks - now including the alpha-enhanced case and…
We present a data-driven technique to analyze multifrequency images from upcoming cosmological surveys mapping large sky area. Using full information from the data at the two-point level, our method can simultaneously constrain the…
In order to retrieve cosmological parameters from photometric surveys, we need to estimate the distribution of the photometric redshift in the sky with excellent accuracy. We use and apply three different machine learning methods to…