Related papers: Using GMM in Open Cluster Membership: An Insight
Gaussian Mixture Models (GMM) have found many applications in density estimation and data clustering. However, the model does not adapt well to curved and strongly nonlinear data. Recently there appeared an improvement called AcaGMM (Active…
Context. Open clusters are very good tracers of the evolution of the Galactic disc. Thanks to Gaia, their kinematics can be investigated with an unprecedented precision and accuracy. Aims. The distribution of open clusters in the 6D phase…
We investigate a novel non-parametric regression-based clustering algorithm for longitudinal data analysis. Combining natural cubic splines with Gaussian mixture models (GMM), the algorithm can produce smooth cluster means that describe the…
Gaia EDR3 offers greatly improved kinematics for nearby objects, including members of nearby young stellar moving groups (NYMGs). In this study, we aim to identify low-mass NYMG members (spectral types of M0 to mid-L) in Gaia EDR3. We…
We present a detailed photometric and kinematical analysis of poorly studied open cluster IC 1434 using CCD VRI, APASS, and Gaia DR2 database for the first time. BY determining the membership probability of stars, we identified the 238 most…
Open clusters and associations are groups of young stars, respectively bound and unbound, that share the same origin and disperse over time into the galactic field. As such, their formation and evolution are the key to understand the origin…
The Gaussian mixture model is widely used in unsupervised learning, owing to its simplicity and interpretability. However, a fundamental limitation of the classical Gaussian mixture model is that it forces each observation to belong to…
This paper presents a new distance metric to compare two continuous probability density functions. The main advantage of this metric is that, unlike other statistical measurements, it can provide an analytic, closed-form expression for a…
Context. Star clusters constitute a significant part of the stellar population in our Galaxy. The feedback processes they exert on the interstellar medium impact multiple physical processes from the chemical to the dynamical evolution of…
Most stars in our Galaxy form in stellar aggregates, which can become long-lived structures called open clusters (OCs). Along their dynamical evolution, their gradual depletion leave some imprints on their structure. In this work, we…
We use stellar proper motions (PM) from Gaia Data Release 2 for studying the internal kinematics of Milky Way globular clusters. In addition to statistical measurement errors, there are significant spatially correlated systematic errors,…
We derive photometric, structural and dynamical evolution-related parameters of 11 nearby open clusters with ages in the range 70 Myr to 7 Gyr and masses in the range $\approx400$ \ms to $\approx5 300$ \ms. We search for relations of…
During the last years and decades several individual studies and large-scale spectroscopic surveys significantly improved our knowledge of the Galactic metallicity distribution based on open clusters. The availability of Gaia data provided…
We propose a hybrid method for accurately estimating the score function, i.e., the gradient of the log steady-state density, using a Gaussian Mixture Model (GMM) in conjunction with a bisecting K-means clustering step. Our approach, which…
UBC 1 is an open cluster discovered in Gaia data and located near the edge of the Transiting Exoplanet Survey Satellite's (TESS) continuous viewing zone. We aim to provide age constraints for this poorly studied open cluster from the…
(ABRIDGED) We assess the systematic uncertainties in (young) cluster age, mass, and - to a lesser extent - extinction and metallicity determinations, based on broad-band imaging observations with the Hubble Space Telescope. Our aim here is…
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 Gromov-Wasserstein (GW) distance is frequently used in machine learning to compare distributions across distinct metric spaces. Despite its utility, it remains computationally intensive, especially for large-scale problems. Recently, a…
Classical Cepheids in open clusters are key ingredients for stellar population studies and the characterization of variable stars, as they are tracers of young and massive populations and of recent star formation episodes. Cluster Cepheids…
In this work we improve a previously published method to calculate in a reliable way the radius of an open cluster. The method is based on the behaviour of stars in the proper motion space as the sampling changes in the position space. Here…