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Tidally-disrupted globular clusters are transformed into thin, dynamically-cold streams of stars that are extremely valuable tracers of the large- and small-scale distribution of mass in the Galaxy. Using data from the Gaia second data…
Open clusters are key targets for both Galaxy structure and evolution and stellar physics studies. Since \textit{Gaia} DR2 publication, the discovery of undetected clusters has proven that our samples were not complete. Our aim is to…
Numerous stellar surveys have been or will provide photometric, astrometric, and spectroscopic data for a large number of stars in the Milky Way and neighbouring galaxies. Modern data processing tools and analysis methods are needed to deal…
The last decade has witnessed a rapid growth of the field of exoplanet discovery and characterisation. However, several big challenges remain, many of which could be addressed using machine learning methodology. For instance, the most…
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…
The Gaia mission will have a profound impact on our understanding of the structure and dynamics of the Milky Way. Gaia is providing an exhaustive census of stellar parallaxes, proper motions, positions, colors and radial velocities, but…
Gaia Data Release 3 (DR3) published for the first time epoch photometry, BP/RP (XP) low-resolution mean spectra, and supervised classification results for millions of variable sources. This extensive dataset offers a unique opportunity to…
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…
A machine-learning-based method is developed to identify objects with unusual stellar spectra. The method employs an autoencoder, a neural network trained to compress spectral data into a low-dimensional representation and subsequently…
Upcoming ground and space-based surveys are poised to illuminate low surface brightness tidal features, providing a new observable connection to dark matter physics. From imaging of tidal debris, the morphology of stellar streams can be…
Recent studies have shown that autoencoder-based models can achieve superior performance on anomaly detection tasks due to their excellent ability to fit complex data in an unsupervised manner. In this work, we propose a novel…
The observation of our home galaxy, the Milky Way (MW), is made difficult by our internal viewpoint. The Gaia survey that contains around 1.6 billion star distances is the new flagship of MW structure and can be combined with other…
Anomaly detection is critical for finding suspicious behavior in innumerable systems. We need to detect anomalies in real-time, i.e. determine if an incoming entity is anomalous or not, as soon as we receive it, to minimize the effects of…
We propose an extension of the GC3 streamer finding method of Johnston et al. 1996 that can be applied to the future Gaia database. The original method looks for streamers along great circles in the sky, our extension adds the kinematical…
We address the problem of identifying remnants of satellite galaxies in the halo of our galaxy with Gaia data. The remnants have to be extracted from a very large data set (of order 10^9 stars) in the presence of observational errors and…
Gravitational microlensing method is a powerful method to detect isolated black holes in the Milky Way. During a microlensing event brightness of the source increases and this feature is used by many photometric surveys to alert on…
Stellar streams are potentially a very sensitive observational probe of galactic astrophysics, as well as the dark matter population in the Milky Way. On the other hand, performing a detailed, high-fidelity statistical analysis of these…
Here we develop a general statistical procedure for the analysis of finite two-dimensional (2D) patterns inspired by the analysis of heavy-ion data. The method is used in the study of publicly available data obtained by the Gaia-ESA…
We present an application of an artificial neural network methodology to a modern wide-field sky survey Pan-STARRS1 in order to build a high-quality sample of disk galaxies visible in edge-on orientation. Such galaxies play an important…
During the past 20 years, numerous stellar streams have been discovered in both the Milky Way and the Local Group. These streams have been tidally torn from orbiting systems, which suggests that most of them should roughly trace the orbit…