相关论文: Random Forest classification of Gaia DR3 white dwa…
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…
In our previous work, we introduced a method that combines two unsupervised algorithms: DBSCAN and GMM. We applied this method to 12 open clusters based on Gaia EDR3 data, demonstrating its effectiveness in identifying reliable cluster…
Aims. In this work we use the Gaia DR3 set of ultracool dwarf candidates and complement the Gaia spectrophotometry with additional photometry in order to characterise its global properties. This includes the inference of the distances,…
Close white dwarf binaries (CWDBs) are considered to be progenitors of several exotic astronomical phenomena (e.g., type Ia supernovae, cataclysmic variables). These violent events are broadly used in studies of general relativity and…
Gaia Data Release 3 contains a wealth of new data products for the community. Astrophysical parameters are a major component of this release. They were produced by the Astrophysical parameters inference system (Apsis) within the Gaia Data…
Wide binaries made up of two white dwarfs (WDs) receive far less attention than their tight counterparts. However, our tests using the binary population synthesis code {\tt StarTrack} indicate that, for any set of reasonable initial…
We present an updated version of the spectroscopic white dwarf-main sequence (WDMS) binary catalogue from the Sloan Digital Sky Survey (SDSS). 395 new systems are serendipitous discoveries from the spectroscopic SDSSI/II Legacy targets. As…
The recent Gaia third data release (DR3) has brought some new exciting data about stellar binaries. It provides new opportunities to fully characterize more stellar systems and contribute to enforce our global knowledge of stars behaviour.…
Gaia DR3, released in June 2022, included low-resolution XP spectra that have been used for the classification of various types of emission-line objects through machine-learning techniques. The Gaia Extended Stellar Parametrizer for…
We present a set of white dwarf-main sequence (WDMS) binaries identified spectroscopically from the Large sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST, also called the Guo Shou Jing Telescope) pilot survey. We develop a color…
We present a Bayesian method to cross-match 5,827,988 high proper motion Gaia sources ($\mu>40 \ mas \ yr^{-1}$) to various photometric surveys: 2MASS, AllWISE, GALEX, RAVE, SDSS and Pan-STARRS. To efficiently associate these objects across…
We present a catalogue of 62 polluted white dwarfs observed by the 9th Low-Resolution Data Release of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST LRS DR9v1; R$\approx$1,800) and the Early Data Release 3 (EDR3) of…
Hot sub-luminous stars represent a population of stripped and evolved red giants that is located on the extreme horizontal branch. Since they exhibit a wide range of variability due to pulsations or binary interactions, it is crucial to…
Context: Unresolved binaries in star clusters can bias stellar and cluster mass estimates, making their proper treatment essential for studying cluster dynamics and evolution. Aims: We aim to develop a fast and robust framework for jointly…
Context. It is possible to accurately measure the masses of the white dwarfs (WDs) in the Hyades cluster using gravitational redshift, because the radial velocity of the stars can be obtained independently of spectroscopy from astrometry…
A significant fraction of white dwarfs, the degenerate remnants of low- and intermediate-mass stars, host strong magnetic fields; yet, the origin and evolution of these magnetic fields remain poorly understood. Building a large,…
Membership studies characterising open clusters with Gaia data, most using DR2, are so far limited at magnitude G = 18 due to astrometric uncertainties at the faint end. Our goal is to extend current open cluster membership lists with faint…
This paper investigates tree species classification using Sentinel-2 multispectral satellite image time-series. Despite their critical importance for many applications, such maps are often unavailable, outdated, or inaccurate for large…
Random Forest (RF) is a powerful supervised learner and has been popularly used in many applications such as bioinformatics. In this work we propose the guided random forest (GRF) for feature selection. Similar to a feature selection method…
The Distributional Random Forest (DRF) is a recently introduced Random Forest algorithm to estimate multivariate conditional distributions. Due to its general estimation procedure, it can be employed to estimate a wide range of targets such…