arXiv subjects

Prapti Mondal

Publications and source records attributed to Prapti Mondal.

5 recordsLinked to original sources

arXiv2026

Cluster Membership Probabilities: A Review of Methods and Gaia Applications

Reliable stellar-cluster membership is essential for deriving cluster ages, distances, reddenings, metallicities, mass functions, dynamical parameters, and Galactic-structure tracers. The Gaia era has produced a proliferation of membership and cluster-detection methods, but the resulting catalogues are not interchangeable. We review the historical development of membership assignment, compare the statistical assumptions of major methods, and explicitly examine the practical consequences of methodological choices on real Gaia data. We consider spatial, proper-motion, maximum-likelihood, photometric, UPMASK, density-based, machine-learning, Bayesian, and bootstrap membership approaches. We add three case studies: a direct comparison of \citet{CantatGaudinAnders2020}, \citet{HuntReffert2023}, and \citet{Perren2023} for common clusters; a Pleiades astrometric comparison; and a critical examination of low-trust candidates in the Unified Cluster Catalogue (UCC), including CWNU, CWWDL, and CKCWDM objects. The literature shows that disagreement is not simply a consequence of Gaia measurement errors. Different definitions of a cluster, different magnitude limits, different treatment of uncertainties, different spatial priors, and different tolerances for extended or low-density populations can lead to substantially different member lists. \citet{Perren2023} reported an average member-list overlap of roughly 75--80\% with \citet{CantatGaudinAnders2020} and 70--75\% with \citet{HuntReffert2023} at bright magnitudes, with the HUNT23 overlap decreasing to about 35\% at $G=20$. The UCC also flags many newly reported candidates as low-trust objects when their member distribution is sparse, their literature support is weak, or they have strong duplicate/non-cluster indicators.

astro-ph.GA↗

arXiv2026

Tidal Tails of Galactic Open Clusters: A Review of Methods, Evidence, and Sources of Disagreement

Tidal tails are a natural consequence of the dynamical evolution of open clusters in the Galactic tidal field, but their observational identification is intrinsically difficult because their surface density is low and the Galactic disc contains a dense and kinematically structured field population. This review paper provides a critical synthesis of the observational and theoretical status of tidal tails of Galactic open clusters and, in particular, assesses how membership definitions, data dimensionality, clustering algorithms, and dynamical assumptions affect reported tail detections. We compare the principal approaches used with Gaia data, including convergent-point and co-moving selection, density-based clustering, probabilistic membership models, machine-learning methods, and orbit/N-body-based filtering. We compile published measurements for a representative sample of nearby clusters and explicitly distinguish robust detections from candidate or method-dependent extended structures. The literature has progressed from detailed studies of a few nearby clusters to systematic searches involving tens to hundreds of systems. The Hyades remains a benchmark because independent analyses recover coherent leading and trailing tails, but the extent and membership of the tails depend on the adopted selection. Large Gaia DR3 studies demonstrate that extended populations are common among nearby and intermediate-age clusters, while also showing that some structures can be produced or exaggerated by projection, field contamination, or the assumptions built into the membership model. Recent homogeneous analyses report tails in most of the nearby clusters in selected samples, but the corresponding catalogues should not be interpreted as equivalent because their completeness, contamination, and physical definitions of a "tail member" differ.

astro-ph.GA↗

arXiv2026

The different methods to calculate cluster membership probabilities

Reliable membership determination is a fundamental step in the study of star clusters. With the advent of $Gaia$ astrometry, a wide range of statistical and machine-learning techniques has been developed to assign membership probabilities. However, the current situation of membership lists is very unsatisfactory. This review summarises the main methodologies, compares their strengths and limitations, and discusses future directions. The aim is to provide a comprehensive overview and to lead to a more efficient and reliable approach for the forthcoming $Gaia$ DR4. Basically, we know of spatial, classical kinematic, and photometric methods, as well as maximum likelihood and Bayesian statistical methods, and machine learning and clustering algorithms. These different methods come with many modifications and flavours. We assessed all the advantages and disadvantages of the known methods to determine cluster membership probabilities. Although nowadays most methods are based on poor statistical numerics, the more robust algorithms should still be taken into account. It is important to apply and compare several methods. The next step must be to define a list of standard star clusters to test and verify all known methods. The list must cover the complete grid of cluster parameters (age, distance, reddening, and metallicity) and total masses.

astro-ph.GA↗

arXiv2026

Chemically peculiar stars investigated by the BRITE Mission

We present a comprehensive analysis of BRITE photometry for 85 chemically peculiar stars, aimed at refining or determining their rotational periods. Utilizing a uniform Lomb-Scargle-based pipeline, we derived significant periods for 47 targets. A comparison with existing literature periods reveals generally good agreement, although several stars exhibit discrepant or previously unrecognized behavior. Notably, six targets display clear multiperiodicity, which, when combined with archival TESS data, suggests that these six candidates are likely misclassified, for example, as a magnetic CP2 or a CP4 star and instead exhibit characteristics consistent with a Be/shell star. Furthermore, eleven stars show no detectable periodic variations within the precision limits of BRITE. Our analysis demonstrates the effectiveness of long-term nanosatellite photometry, particularly when complemented by TESS data, in verifying catalogue periods, identifying multiperiodic behavior, and detecting potential misclassifications among bright CP stars.

astro-ph.SR↗

arXiv2024

Estimation of radial velocities of BHB stars

We studied blue horizontal branch stars (BHBs), and calculated their radial velocities. Spectra of these stars have been obtained with moderate signal-to-noise ratio for five blue horizontal-branch stars using the 2 meter telescope and Echelle Spectrograph in Ondrejov observatory, Czech republic.

astro-ph.SR↗