Identifying Physical Structures in Our Galaxy with Gaussian Mixture Models: An Unsupervised Machine Learning Technique

Identifying Physical Structures in Our Galaxy with Gaussian Mixture Models: An Unsupervised Machine Learning Technique

We explore the potential of the Gaussian mixture model (GMM), an unsupervised machine-learning method, to identify coherent physical structures in the interstellar medium. The implementation we present can be used on any kind of spatially and spectrally resolved data set. We provide a step-by-step g...

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Bibliographic Details
Main Authors: M. Tiwari, R. Kievit, S. Kabanovic, L. Bonne, F. Falasca, C. Guevara, R. Higgins, M. Justen, R. Karim, Ü. Kavak, C. Pabst, M. W. Pound, N. Schneider, R. Simon, J. Stutzki, M. Wolfire, A. G. G. M. Tielens
Format: Article
Language:English
Published: IOP Publishing 2023-01-01
Series:The Astrophysical Journal
Subjects:
Star forming regions
Gaussian mixture model
Online Access:https://doi.org/10.3847/1538-4357/ad003c

Internet

https://doi.org/10.3847/1538-4357/ad003c

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