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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…
A cluster finding method was developed and applied in four Local Group Galaxies (SMC, M31, M33 and NGC 6822). The aim is to study the young stellar population of these galaxies by identifying stellar structures in small and large scales.…
We apply the clustering algorithm HDBSCAN on the Gaia early third data release astrometry combined with the Gaia second data release radial velocity measurements of almost 5.5 million stars to identify the local stellar kinematic…
Young stellar associations hold a star formation record that can persist for millions of years, revealing the progression of star formation long after the dispersal of the natal cloud. To identify nearby young stellar populations that trace…
Context. This work is part of a long-term spectroscopic study of a sample of 30 multiple stars with early-type components. In this second paper we present the results of six multiple systems in which new stellar components have been…
Young stellar clusters harbour complex spatial structures emerging from the star formation process. Identifying stellar over-densities is a key step to constrain better how these structures are formed. The high accuracy of distances derived…
We present a comprehensive study of the star cluster population and the hierarchical structure in the clustering of blue stars with ages <~ 500 Myr in the Local Group dwarf irregular galaxy NGC 6822. Our observational material comprises the…
Molecular line emissions are commonly used to trace the distribution and properties of molecular Interstellar Medium (ISM). However, the emissions are heavily blended on the Galactic disk toward the inner Galaxy because of the relatively…
Recent studies have identified star clusters with multiple components based on accurate spatial distributions and/or proper motions from Gaia DR3, utilising diverse diagnostics to improve our understanding of subgroup evolution. These…
We are conducting a survey of several regions of high-mass star formation to assess their content and structure. The observations include Spitzer observations, ground-based optical and near-IR imaging surveys, and optical and IR spectra of…
For the first time, we explore the dynamics of the central region of a galaxy cluster within $r_{500}\sim 600h^{-1}$~kpc from its center by combining optical and X-ray spectroscopy. We use (1) the caustic technique that identifies the…
Context. Filaments are ubiquitous in the Galaxy, and they host star formation. Detecting them in a reliable way is therefore key towards our understanding of the star formation process. Aims. We explore whether supervised machine learning…
The existence of satellite galaxy planes poses a major challenge for the standard picture of structure formation with non-baryonic dark matter. Recently Tully et al. (2015) reported the discovery of two almost parallel planes in the nearby…
The kinematic plane of stars near the Sun has proven an indispensable tool for untangling the complexities of the structure of our Milky Way (MW). With ever improving data, numerous kinematic "moving groups" of stars have been better…
This work proposes a multiple machine learning method (MMLM) aiming to improve the accuracy and robustness in the analysis of star clusters. The MMLM performance is evaluated by applying it to the reanalysis of the old binary cluster…
We explore the potential of the Gaussian Mixture Model (GMM), an unsupervised machine learning method, to identify coherent physical structures in the ISM. The implementation we present can be used on any kind of spatially and spectrally…
Subjective classification of spiral galaxies is not sufficient for studying the effect of bars on their physical characteristics. In reality the problem is to comprehend the complex correlations in a multivariate parametric space.…
We have developed a multiscale structure identification algorithm for the detection of overdensities in galaxy data that identifies structures having radii within a user-defined range. Our "multiscale probability mapping" technique combines…
The spatial and dynamical structure of star-forming regions can help provide insights on stellar formation patterns. The amount of data from current and upcoming surveys calls for robust and objective procedures to detect structure, so the…
Star-formation within galaxies appears on multiple scales, from spiral structure, to OB associations, to individual star clusters, and often sub-structure within these clusters. This multitude of scales calls for objective methods to find…