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Membership determination in open clusters using the DBSCAN Clustering Algorithm

Hasan, P.; Raja, M.; Mahmudunnobe, Md. +2 more

In this paper, we apply the machine learning clustering algorithm Density Based Spatial Clustering of Applications with Noise (DBSCAN) to study the membership of stars in twelve open clusters (NGC 2264, NGC 2682, NGC 2244, NGC 3293, NGC 6913, NGC 7142, IC 1805, NGC 6231, NGC 2243, NGC 6451, NGC 6005 and NGC 6583) based on Gaia DR3 Data. This sampl…

Using GMM in open cluster membership: An insight

Hasan, P.; Raja, M.; Hasan, S. N. +2 more

The unprecedented precision of Gaia has led to a paradigm shift in membership determination of open clusters where a variety of machine learning (ML) models can be employed. In this paper, we apply the unsupervised Gaussian Mixture Model (GMM) to a sample of thirteen clusters with varying ages (log t ≈ 6.38-9.64) and distances (441-5183 pc) from G…

LCGCT: A light curve generator in customisable-time-bin based on time-series database

Xu, Y.; Cui, C.; Fan, D. +1 more

In the era of time-domain astronomy, scientists often need to generate light curves with varying time-bin. However, an increase in time resolution typically leads to a substantial increase in data transmission. To enhance the data processing efficiency in time-domain astronomy, we propose a novel time-series data model for storing time-series obse…

The effect of baseline on the uncertainties of range determination performed by two-site astrometric observations. A sample case for the triangulation method: TURKSAT 3A and TURKSAT 4A

Gökay, H. G.; Özdemi̇r, S.; Bağıran, M. N. +1 more

The uncertainties in range determination depending on two-site locations for GEO satellites were calculated and shown that the uncertainty in the range depends not only on linear baseline distance between the locations but also both latitude and longitude of geographic coordinates of the sites. By taking the first observing site as fixed and chang…