A census of young stellar objects in two line-of-sight star forming regions toward IRAS 22147+5948 in the outer Galaxy
Agata Karska, Maciej Koprowski, Aleksandra Solarz, Ryszard Szczerba,, Marta Sewi{\l}o, Natasza Si\'odmiak, Davide Elia, Marcin Gawro\'nski, Konrad, Grzesiak, Bosco H. K. Yung, William J. Fischer, Lars E. Kristensen

TL;DR
This study develops a machine learning-based methodology to identify and classify young stellar objects in the outer Galaxy, clarifying their distribution and properties in two star-forming regions along the line of sight to IRAS 22147+5948.
Contribution
It introduces a novel combination of support vector machine and clustering algorithms to improve YSO identification and distance estimation in the outer Galaxy.
Findings
Identified 13 Class I and 13 Class II YSO candidates using color diagrams.
Discovered two clusters at ~2.2 kpc and five at ~5.6 kpc, confirming multiple star-forming regions.
Validated the methodology with physical modeling of YSO spectral energy distributions.
Abstract
(abridged) Star formation in the outer Galaxy, i.e., outside of the Solar circle, has been lightly studied in part due to low CO brightness of molecular clouds linked with the negative metallicity gradient. Recent infrared surveys provide an overview of dust emission in large sections of the Galaxy, but suffer from cloud confusion and poor spatial resolution at far-infrared wavelengths. We aim to develop a methodology to identify and classify young stellar objects (YSOs) in star-forming regions in the outer Galaxy, and use it to solve a long-standing confusion with the distance and evolutionary status of IRAS 22147+5948. We use Support Vector Machine learning algorithm to complement standard color-color and color-magnitude diagrams in search for YSOs in the IRAS 22147 region using publicly available data from the `Spitzer Mapping of the Outer Galaxy' survey. The agglomerative…
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