ALMA Band 3 Source Counts: A Machine Learning Approach to Contamination Mitigation below 5 Sigma

We performed differential number counts down to 4.25 sigma using ALMA Band 3 calibrator images, which are known for their high dynamic range and susceptibility to various types of contamination. Estimating the fraction of contaminants is an intricate process due to correlated non-Gaussian noise, and...

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Détails bibliographiques

Auteurs principaux:	Ivano Baronchelli, Matteo Bonato, Gianfranco De Zotti, Viviana Casasola, Michele Delli Veneri, Fabrizia Guglielmetti, Elisabetta Liuzzo, Rosita Paladino, Leonardo Trobbiani, Martin Zwaan
Format:	Artigo
Langue:	Inglês
Publié:	MDPI AG 2024-05-01
Collection:	Galaxies
Sujets:	galaxies: photometry galaxies: active galaxies: abundances sub-millimeter: galaxies
Accès en ligne:	https://www.mdpi.com/2075-4434/12/3/26
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