Related papers: A Generalist Model Including Evolved Star Mass and…
Grid-based modelling is widely used for estimating stellar parameters. However, stellar model grid is sparse because of the computational cost. This paper demonstrates an application of a machine-learning algorithm using the Gaussian…
We present a new processing of XP spectra for 220 million stars released in Gaia DR3. The new data model is capable of handling objects with Teff between 2000 and 50,000 K, and with log g between 0 and 10, including objects of multitude of…
Large-scale spectroscopic surveys have collectively observed millions of stars across the Milky Way, but each derives stellar labels using independent pipelines with distinct modelling assumptions, introducing systematic offsets that…
The third Gaia data release contains, beyond the astrometry and photometry, dispersed light for hundreds of millions of sources from the Gaia prism spectra (BP and RP) and the spectrograph (RVS). This data release opens a new window on the…
We present the results of a novel application of Bayesian modelling techniques, which, although purely data driven, have a physically interpretable result, and will be useful as an efficient data mining tool. We base our studies on the…
We develop a data-driven model to map stellar parameters (effective temperature, surface gravity and metallicity) accurately and precisely to broad-band stellar photometry. This model must, and does, simultaneously constrain the…
The inference of stellar parameters (such as radius and mass) through asteroseismic forward modelling depends on the number, accuracy, and precision of seismic and atmospheric constraints. ESA's Gaia space mission is providing precise…
We present a catalogue of distances, masses and ages for $\sim3$ million stars in the second Gaia data release with spectroscopic parameters available from the large spectroscopic surveys: APOGEE, Gaia-ESO, GALAH, LAMOST, RAVE and SEGUE. We…
The GAIA space mission is impacting astronomy in many significant ways by providing a uniform, homogeneous and precise data set for over 1 billion stars and other celestial objects in the Milky Way and beyond. Exoplanet science has greatly…
Aims. We present an innovative artificial neural network (ANN) architecture, called Generative ANN (GANN), that computes the forward model, that is it learns the function that relates the unknown outputs (stellar atmospheric parameters, in…
We derive distances and masses of stars from the Sloan Digital Sky Survey (SDSS) Apache Point Observatory Galactic Evolution Experiment (APOGEE) Data Release 17 (DR17) using simple neural networks. Training data for distances comes from…
Stellar ages are extremely difficult to determine and often subject to large uncertainties, especially for field low-mass stars. We plan to carry out a calibration of the decrease in high-energy emissions of low-mass GKM stars with time,…
We derive new spectral H_gamma index definitions which are robust age indicators for old and relatively old stellar populations and thus have great potential for solving the age-metallicity degeneracy of galaxy spectra. To study H_gamma as…
[Abridged] Ensemble studies of red-giant stars with exquisite asteroseismic, spectroscopic, and astrometric constraints offer a novel opportunity to recast and address long-standing questions concerning the evolution of stars and of the…
The Gaia Data Release 3 (DR3), published in June 2022, delivers a diverse set of astrometric, photometric, and spectroscopic measurements for more than a billion stars. The wealth and complexity of the data makes traditional approaches for…
In this contribution I will discuss fundamental stellar parameters as determined from young star clusters; specifically those with ages less than or approximately equal to that of the Pleiades. I will focus primarily on the use of stellar…
Gaia will observe more than one billion objects brighter than V=20, including stars, asteroids, galaxies and quasars. As Gaia performs real time detection (i.e. without an input catalogue) the intrinsic properties of most of these objects…
In systems undergoing starbursts the evolution of the young stellar population is expected to drive changes in the emission line properties. This evolution is usually studied theoretically, with a combination of evolutionary synthesis…
We show that the masses of red giant stars can be well predicted from their photospheric carbon and nitrogen abundances, in conjunction with their spectroscopic stellar labels log g, Teff, and [Fe/H]. This is qualitatively expected from…
Understanding the ages of stars is crucial for unraveling the formation history and evolution of our Galaxy. Traditional methods for estimating stellar ages from spectroscopic data often struggle with providing appropriate uncertainty…