6 papers
Metallicity Effects on Machine Learning Classification of Dusty Stellar Sources in the Magellanic Clouds
Sepideh Ghaziasgar, Mahdi Abdollahi, Atefeh Javadi +4
Differences in metallicity between the Large Magellanic Cloud (LMC) and the Small Magellanic Cloud (SMC) offer an opportunity to examine whether environmental metallicity affects t…
Comparison of Photometric and Spectroscopic Labels in Classifying Dusty Stellar Sources Using Machine Learning in the Magellanic Clouds
Sepideh Ghaziasgar, Mahdi Abdollahi, Atefeh Javadi +4
Dusty stellar sources, including young stellar objects (YSOs) and evolved stars such as oxygen- and carbon-rich AGBs (OAGBs, CAGBs), red supergiants (RSGs), and post-AGB stars (PAG…
The VMC survey -- LIV. The internal kinematics of the LMC with new VISTA observations
S. Vijayasree, F. Niederhofer, M. -R. L. Cioni +10
Context: Studying the internal kinematics of galaxies provides insights into their past evolution, current dynamics, and future trajectory. The Large Magellanic Cloud (LMC), as the…
Dusty stellar sources classification by implementing machine learning methods based on spectroscopic observations in the Magellanic Clouds
Sepideh Ghaziasgar, Mahdi Abdollahi, Atefeh Javadi +7
Dusty stellar point sources are a significant stage in stellar evolution and contribute to the metal enrichment of galaxies. These objects can be classified using photometric and s…
Machine Learning Classification of Young Stellar Objects and Evolved Stars in the Magellanic Clouds Using the Probabilistic Random Forest Classifier
Sepideh Ghaziasgar, Mahdi Abdollahi, Atefeh Javadi +4
The Magellanic Clouds (MCs) are excellent locations to study stellar dust emission and its contribution to galaxy evolution. Through spectral and photometric classification, MCs ca…
The VMC Survey : LI. Classifying extragalactic sources using a probabilistic random forest supervised machine learning algorithm
Clara M. Pennock, Jacco Th. van Loon, Maria-Rosa L. Cioni +10
We used a supervised machine learning algorithm (probabilistic random forest) to classify ~130 million sources in the VISTA Survey of the Magellanic Clouds (VMC). We used multi-wav…