Related papers: Data-Driven Stellar Models
Stellar streams are sensitive probes of the Milky Way's gravitational potential. The mean track of a stream constrains global properties of the potential, while its fine-grained surface density constrains galactic substructure. A precise…
We present a method for accurately and precisely inferring photometric dust extinction towards stars at mid-to-high Galactic latitudes using probabilistic machine learning to model the colour-magnitude distribution of zero-extinction stars…
Machine Learning is an efficient method for analyzing and interpreting the increasing amount of astronomical data that is available. In this study, we show, a pedagogical approach that should benefit anyone willing to experiment with Deep…
The Gaia satellite will observe the positions and velocities of over a billion Milky Way stars. In the early data releases, the majority of observed stars do not have complete 6D phase-space information. In this Letter, we demonstrate the…
A simple, fully connected neural network with a single hidden layer is used to estimate stellar masses for star-forming galaxies. The model is trained on broad-band photometry - from far-ultraviolet to mid-infrared wavelengths - generated…
The advent of space-based observatories such as CoRoT and Kepler has enabled the testing of our understanding of stellar evolution on thousands of stars. Evolutionary models typically require five input parameters, the mass, initial Helium…
A new generative technique is presented in this paper that uses Deep Learning to reconstruct stellar spectra based on a set of stellar parameters. Two different Neural Networks were trained allowing the generation of new spectra. First, an…
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…
Accurate determinations of metallicity for large, complete stellar samples are essential for advancing various studies of the Milky Way. In this paper, we present a data-driven algorithm that leverages photometric data from the KiDS and the…
A deep understanding of the Milky Way galaxy, its formation and evolution requires observations of huge numbers of stars. Stellar photometry, therefore, provides an economical method to obtain intrinsic stellar parameters. With the addition…
Stellar parameters for large samples of stars play a crucial role in constraining the nature of stars and stellar populations in the Galaxy. An increasing number of medium-band photometric surveys are presently used in estimating stellar…
The ability to make accurate determinations of planetary parameters is inextricably linked to measuring physical parameters of the host star, in particular the stellar radius. In this paper we fit the stellar spectral energy distributions…
We present a non-parametric model for inferring the three-dimensional (3D) distribution of dust density in the Milky Way. Our approach uses the extinction measured towards stars at different locations in the Galaxy at approximately known…
Despite the advances provided by large-scale photometric surveys, stellar features - such as metallicity - generally remain limited to spectroscopic observations often of bright, nearby low-extinction stars. To rectify this, we present a…
Temperature and luminosity are the two key diagnostics of a star, yet these cannot come directly from survey data, but must be imputed by comparing those data to models. SED fitting offers a high-precision method to obtain both parameters…
We derive and publish data-driven estimates of stellar metallicities [M/H] for 175 million stars with low-resolution XP spectra published in Gaia DR3. The [M/H] values, along with Teff and logg, are derived using the XGBoost algorithm,…
Gaia DR3 provides radial velocities for 33 million stars and spectroscopically derived atmospheric parameters for more than five million targets. When combined with the astrometric data, these allow us to derive orbital and stellar…
Gaia measures the five astrometric parameters for stars in the Milky Way, but only four of them (positions and proper motion, but not parallax) are well measured beyond a few kpc from the Sun. Modern spectroscopic surveys such as APOGEE…
As a tool to interpret nearby and high redshift galaxy data from optical to K-band we present our chemically consistent spectrophotometric evolutionary synthesis models. These models take into account the increasing initial metallicity of…
We present the DustFilaments code, a full sky model for the millimeter Galactic emission of thermal dust. Our model, composed of millions of filaments that are imperfectly aligned with the magnetic field, is able to reproduce the main…