Mining the UKIDSS GPS: star formation and embedded clusters

Otto Solin (Departments of Physics and Computer Science, University of Helsinki)

Abstract

The aim of this research is to locate previously unknown stellar clusters from the near-infrared UKIDSS Galactic Plane Survey. The cluster candidates were computationally searched from pre-filtered catalogue data using a recently proposed method that fits a mixture model of Gaussian densities and background noise using the Expectation Maximization algorithm. The pre-filtering of the data involves both removing data artefacts and searching for sources classified as non-stellar due to associated surface brightness thus directing the search to particularly embedded stellar clusters. The findings were further screened by visual inspection of images, and SIMBAD was used to study sources in the direction of the candidates. Our search resulted in 130 new cluster candidates.

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Paper ID: P143

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