Related papers: Crossmatching variable objects with the Gaia data

Classification is a major tool of statistics and machine learning. A classification method first processes a training set of objects with given classes (labels), with the goal of afterward assigning new objects to one of these classes. When…

Datasets containing both categorical and continuous variables are frequently encountered in many areas, and with the rapid development of modern measurement technologies, the dimensions of these variables can be very high. Despite 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…

The information contained in the Gaia Second Data Release (DR2) allows to search for the unusual objects with the pre-selected properties, literally constructing the stars with the desired characteristics. This work describes the idea of…

Using Gaia DR3 data, binary star catalogs have been created containing information on a total of more than 2.6 million pairs. This increases by more than an order of magnitude the ensemble of binary stars with known characteristics, which…

The publication of the Gaia Data Release 2 (Gaia DR2) opens a new era in Astronomy. It includes precise astrometric data (positions, proper motions and parallaxes) for more than $1.3$ billion sources, mostly stars. To analyse such a vast…

Binary classification is a task that involves the classification of data into one of two distinct classes. It is widely utilized in various fields. However, conventional classifiers tend to make overconfident predictions for data that…

Gaia can not individually resolve very close binary systems, however, the collected data can still be used to identify them. A powerful indicator of stellar multiplicity is the sources reported Renormalized Unit Weight Error (ruwe), which…

Context: Gaia DR3 time series data may contain spurious signals related to the time-dependent scan angle. Aims: We aim to explain the origin of scan-angle dependent signals and how they can lead to spurious periods, provide statistics to…

Transfer learning with pre-training on large-scale datasets has played an increasingly significant role in computer vision and natural language processing recently. However, as there exist numerous application scenarios that have…

We here apply a novel technique selecting quasar candidates purely as sources with zero proper motions in the Gaia data release 2 (DR2). We demonstrate that this approach is highly efficient toward high Galactic latitudes with < 25%…

Since July 2014, the ESA Gaia mission has been surveying the entire sky down to magnitude 20.7 in the visible. In addition to the millions of stars, thousands of Solar System Objects (SSOs) are observed daily. By comparing their positions…

Context.The Gaia Early Data Release 3 contained the positions, parallaxes and proper motions of 1.5 billion sources, among which some did not fit well the "single star" model. Binarity is one of the causes of this. Aims. Four million of…

The Gaia mission is expected to yield the detection of several thousands of exoplanets, perhaps at least doubling the number of known exoplanets. Although the harvest is expected to occur when the astrometric time series will be published…

The ESA Gaia satellite scans the whole sky with a temporal sampling ranging from seconds and hours to months. Each time a source passes within the Gaia field of view, it moves over 10 CCDs in 45 s and a lightcurve with 4.5 s sampling (the…

Gaia is a cornerstone mission of the European Space Agency (ESA) selected in 2000, with a target launch date of 2011. The Gaia mission will perform a survey of about 1 billion sources brighter than V=20. Its goal is to provide astrometry…

Machine learning models of visual action recognition are typically trained and tested on data from specific situations where actions are associated with certain objects. It is an open question how action-object associations in the training…

A key science goal of large sky surveys such as those conducted by the Vera C. Rubin Observatory and precursors to the Square Kilometre Array is the identification of variable and transient objects. One approach is the statistical analysis…

Gait recognition is a crucial biometric identification technique. Camera-based gait recognition has been widely applied in both research and industrial fields. LiDAR-based gait recognition has also begun to evolve most recently, due to the…

Gait recognition is a computer vision task that identifies individuals based on their walking patterns. Gait recognition performance is commonly evaluated by ranking a gallery of candidates and measuring the accuracy at the top Rank-$K$.…