Photometric Classification of Stars Around the Milky Way's Central Black Hole: I. Central Parsec
E. Gallego-Cano, T. Fritz, R. Sch\"odel, A. Feldmeier-Krause, T. Do,, and S. Nishiyama

TL;DR
This study uses advanced photometric techniques and machine learning to identify and analyze the distribution and initial mass function of young stars near the Milky Way's central black hole, revealing a top-heavy IMF close to Sgr A*.
Contribution
It introduces a novel photometric and machine learning approach to classify stars and determine the IMF in the Galactic Centre, improving understanding of star formation near the black hole.
Findings
Identification of 155 new early-type star candidates.
Detection of a broken power-law density profile for stars.
Evidence of a top-heavy IMF within 9 arcseconds of Sgr A*.
Abstract
The presence of young massive stars in the Galactic Centre (GC) raises questions about star formation near the black hole Sagittarius A* (Sgr A*). Additionally, the initial mass function (IMF) in this region appears different from the standard Salpeter/Kroupa law. Extreme extinction and crowding limit our understanding of the stellar population, with spectroscopic data available only for selected bright sources. We aim to improve knowledge about the distribution and IMF of young, massive stars near Sgr A*. Using intermediate band (IB) photometry, we identify candidates for massive young stars through Bayesian inference, a neural network, and a gradient-boosted trees algorithm. We obtained spectral energy distributions for 6590 stars, 1181 of which have been previously classified spectroscopically. We identify 351 stars classified as early types by all three methods, including 155 newly…
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Taxonomy
TopicsAstronomy and Astrophysical Research · Astrophysical Phenomena and Observations · Stellar, planetary, and galactic studies
