All Outputs (2)

Machine Learning Classification of Young Stellar Objects and Evolved Stars in the Magellanic Clouds Using the Probabilistic Random Forest Classifier (2024)
Journal Article
Ghaziasgar, S., Abdollahi, M., Javadi, A., van Loon, J. T., McDonald, I., Oliveira, J., & Khosroshahi, H. G. (in press). Machine Learning Classification of Young Stellar Objects and Evolved Stars in the Magellanic Clouds Using the Probabilistic Random Forest Classifier. Communications of the Byurakan Astrophysical Observatory, 71(2), 377-382. https://doi.org/10.52526/25792776-24.71.2-377

The Magellanic Clouds (MCs) are excellent locations to study stellar dust emission and its contribution to galaxy evolution. Through spectral and photometric classification, MCs can serve as a unique environment for studying stellar evolution and gal... Read More about Machine Learning Classification of Young Stellar Objects and Evolved Stars in the Magellanic Clouds Using the Probabilistic Random Forest Classifier.

SMC-Last Extracted Photometry (2024)
Journal Article
Kuchar, T. A., Sloan, G. C., Mizuno, D. R., Kraemer, K. E., Boyer, M. L., Groenewegen, M. A. T., Jones, O. C., Kemper, F., McDonald, I., Oliveira, J. M., Sewiło, M., Srinivasan, S., van Loon, J. T., & Zijlstra, A. (2024). SMC-Last Extracted Photometry. Astronomical Journal, 167(4), Article 149. https://doi.org/10.3847/1538-3881/ad2601

We present point-source photometry from the Spitzer Space Telescope's final survey of the Small Magellanic Cloud (SMC). We mapped nearly 30 deg2 in two epochs in 2017, with the second extending to early 2018 at 3.6 and 4.5 μm using the Infrared Array... Read More about SMC-Last Extracted Photometry.