Obscured star clusters in the Inner Milky Way. How many massive young clusters are still awaiting detection?
Akash Gupta, Valentin D. Ivanov, Thomas Preibisch, Dante Minniti

TL;DR
This study uses advanced infrared survey data and clustering algorithms to identify potential new massive star clusters in the inner Milky Way, revealing a significant hidden population of such clusters.
Contribution
The paper introduces a novel automated method combining mid-infrared surveys and clustering algorithms to detect massive star clusters and assess their detection completeness.
Findings
Identified 659 cluster candidates, with 106 previously known.
Achieved a 70-95% recovery rate for simulated supermassive clusters.
Found no evidence of a large hidden population of supermassive clusters.
Abstract
Aims. Our goal is twofold. First, to detect new clusters we apply the newest methods for the detection of clustering with the best available wide-field sky surveys in the mid-infrared because they are the least affected by extinction. Second, we address the question of cluster detection's completeness, for now limiting it to the most massive star clusters. Methods. This search is based on the mid-infrared Galactic Legacy Infrared Mid Plane Survey Extraordinaire (GLIMPSE), to minimize the effect of dust extinction. The search Ordering Points To Identify the Clustering Structure (OPTICS) clustering algorithm is applied to identify clusters, after excluding the bluest, presumably foreground sources, to improve the cluster-to-field contrast. The success rate for cluster identification is estimated with a semi-empirical simulation that adds clusters, based on the real objects, to the point…
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Taxonomy
TopicsAstrophysics and Star Formation Studies · Stellar, planetary, and galactic studies · Astronomy and Astrophysical Research
