Machine learning-enabled membership determination of open cluster AH03_J0748-26.9 using Gaia DR3 astrometry

As populations of stars born concurrently, open clusters serve as fundamental laboratories for validating models of star formation, stellar evolution, and the dynamical processes of the Galactic disk. This paper provides a comprehensive astrometric and photometric analysis of the open cluster AH03_J0748-26.9, leveraging data from the Gaia DR3 catalog. We employ the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) algorithm to analyze astrometric data from Gaia Data Release 3 (DR3). Our analysis characterizes the identified clusters through several fundamental parameters, specifically the census of probable members, spatial radii, age, distance, the initial mass function (IMF), and total cluster mass.We determined a concentration parameter of [Formula: see text] for AH03_J0748-26.9. The estimated number of members for AH03_J0748-26.9 is 128 stars. A distance modulus of [Formula: see text] mag and an age of 114.815 Myr ([Formula: see text]) were derived using PARSEC isochrone fitting. Given a relaxation time of 32.125 Myr and an age of 114.815 Myr ([Formula: see text]), the cluster AH03_J0748-26.9 is found to be dynamically relaxed. We analyzed the mass function (MF) for AH03_J0748-26.9 using a Monte Carlo method coupled with synthetic cluster modeling. We characterized the MF over the range 0.102-[Formula: see text] by fitting a two-segment broken power law, deriving slopes of [Formula: see text] (for [Formula: see text]) and [Formula: see text] (for [Formula: see text]) with a characteristic break mass of [Formula: see text]. The steep slope in the higher mass regime suggests a deviation from the canonical Salpeter IMF, which is consistent with the effects of dynamical evolution and mass segregation. By integrating this best-fit MF and adopting a binary fraction of [Formula: see text]-typical for concentrated open clusters-we estimate a total cluster mass of [Formula: see text]. A sensitivity analysis indicates that varying the binary fraction between 0.5 and 0.9 alters the total mass estimate by approximately [Formula: see text], supporting the robustness of the mass scale. A sample of 128 member stars yielded a mean radial velocity of [Formula: see text]. These kinematic data, combined with proper motions, served as input for the galpy package to determine the cluster's Galactic orbit.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-08-25
DOI
https://doi.org/10.1038/s41598-026-67279-2
Primary Topic
Stellar, planetary, and galactic studies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Machine learning-enabled membership determination of open cluster AH03_J0748-26.9 using Gaia DR3 astrometry

W. A. Badawy, H. I. Abdel Rahman
Scientific Reports
Stellar, planetary, and galactic studies
article

Machine learning-enabled membership determination of open cluster AH03_J0748-26.9 using Gaia DR3 astrometry

W. A. Badawy, H. I. Abdel Rahman
article en

Abstract

As populations of stars born concurrently, open clusters serve as fundamental laboratories for validating models of star formation, stellar evolution, and the dynamical processes of the Galactic disk. This paper provides a comprehensive astrometric and photometric analysis of the open cluster AH03_J0748-26.9, leveraging data from the Gaia DR3 catalog. We employ the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) algorithm to analyze astrometric data from Gaia Data Release 3 (DR3). Our analysis characterizes the identified clusters through several fundamental parameters, specifically the census of probable members, spatial radii, age, distance, the initial mass function (IMF), and total cluster mass.We determined a concentration parameter of [Formula: see text] for AH03_J0748-26.9. The estimated number of members for AH03_J0748-26.9 is 128 stars. A distance modulus of [Formula: see text] mag and an age of 114.815 Myr ([Formula: see text]) were derived using PARSEC isochrone fitting. Given a relaxation time of 32.125 Myr and an age of 114.815 Myr ([Formula: see text]), the cluster AH03_J0748-26.9 is found to be dynamically relaxed. We analyzed the mass function (MF) for AH03_J0748-26.9 using a Monte Carlo method coupled with synthetic cluster modeling. We characterized the MF over the range 0.102-[Formula: see text] by fitting a two-segment broken power law, deriving slopes of [Formula: see text] (for [Formula: see text]) and [Formula: see text] (for [Formula: see text]) with a characteristic break mass of [Formula: see text]. The steep slope in the higher mass regime suggests a deviation from the canonical Salpeter IMF, which is consistent with the effects of dynamical evolution and mass segregation. By integrating this best-fit MF and adopting a binary fraction of [Formula: see text]-typical for concentrated open clusters-we estimate a total cluster mass of [Formula: see text]. A sensitivity analysis indicates that varying the binary fraction between 0.5 and 0.9 alters the total mass estimate by approximately [Formula: see text], supporting the robustness of the mass scale. A sample of 128 member stars yielded a mean radial velocity of [Formula: see text]. These kinematic data, combined with proper motions, served as input for the galpy package to determine the cluster's Galactic orbit.

Scientific ReportsVol. 16(1)
National Research Institute of Astronomy and Geophysics (EG)
Academy of Scientific Research and Technology, Science and Technology Development Fund
Peace, Justice and strong institutions
Openalex Percentile: Top 10%
Stellar, planetary, and galactic studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.