Related papers: Transferring spectroscopic stellar labels to 217 m…
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…
We present an updated catalog of stellar parameters, including effective temperature, luminosity classification, and metallicity, for over fifty million stars from the SkyMapper Southern Survey (SMSS) DR4 and Gaia DR3. The accuracy of the…
The Gaia Galactic survey mission is designed and optimized to obtain astrometry, photometry, and spectroscopy of nearly two billion stars in our Galaxy. Yet as an all-sky multi-epoch survey, Gaia also observes several million extragalactic…
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 unprecedented volume and quality of data from space- and ground-based telescopes present an opportunity for machine learning to identify new classes of variable stars and peculiar systems that may have been overlooked by traditional…
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…
In modern astrophysics, the machine learning has increasingly gained more popularity with its incredibly powerful ability to make predictions or calculated suggestions for large amounts of data. We describe an application of the supervised…
Context. Gaia Early Data Release 3 (EDR3), published in December 2020, features improved photometry and astrometry over that published in the previous DR2 file, and includes a substantially larger number of sources, of the order of 2,000…
We apply the stellar locus method to synthetic $(BP-RP)_{XPSP}$ and $(BP-G)_{XPSP}$ colors derived from corrected Gaia BP/RP (XP) spectra to obtain precise estimates of metallicity for about 100 million stars in the Milky Way (34 million…
We present the main-sequence binary (MSMS) Catalog derived from Gaia Data Release 3 BP/RP (XP) spectra. Leveraging the vast sample of low-resolution Gaia XP spectra, we develop a forward modeling approach that maps stellar mass and…
Context: New spectroscopic surveys will increase the number of astronomical objects requiring characterization by over tenfold.. Machine learning tools are required to address this data deluge in a fast and accurate fashion. Most machine…
We design an uncertainty-aware cost-sensitive neural network (UA-CSNet) to estimate metallicities from dereddened and corrected Gaia BP/RP (XP) spectra for giant stars. This method accounts for both stochastic errors in the input spectra…
The Gaia DR3 GSP-Spec parameters, including metallicity, for VMP stars suffer from parameter degeneracy due to a lack of information in their spectra. Furthermore, the recommended quality cuts filter out the majority of the VMP stars…
Gaia Data Release 3 has provided the astronomical community with the largest stellar spectroscopic survey to date ($>$ 220 million sources). The low resolution (R$\sim$50) blue photometer (BP) and red photometer (RP) spectra will allow for…
The u band magnitude is vital for determining stellar parameters and investigating specific astronomical objects. However, flux calibration in the u band for stars in the Galactic disk presents significant challenges. In this study, we…
We investigate the feasibility of accurately determining the helium-to-metal enrichment ratio, $\Delta Y/\Delta Z$, from Gaia DR3 photometry for nearby low-mass main sequence field stars. We selected a sample of 2770 nearby MS stars from…
The advent of large-scale stellar spectroscopic surveys naturally leads to the implementation of machine learning techniques to isolate, for example, small sub-samples of potentially interesting stars from the full data set. A recent…
Gaia DR3 contains 1.8 billion sources with G-band photometry, 1.5 billion of which with BP and RP photometry, complemented by positions on the sky, parallax, and proper motion. The median number of field-of-view transits in the three…
In the current panorama of large surveys, the vast amount of data obtained with different methods, data types, formats, and stellar samples, is making an efficient use of the available information difficult. The Survey of Surveys is a…
The third Gaia Data Release has provided the astronomical community with astrometric data of more than 1.8 billion sources, and low resolution spectra for 220 million. Such a large amount of data is difficult to handle by means of visual…