Vol 24, No 5

Low Surface Brightness Galaxies from BASS+MzLS with Machine Learning

Peng-Liang Du, Wei Du, Bing-Qing Zhang, Zhen-Ping Yi, Min He and Hong Wu


From ∼5000 deg2 of the combination of the Beijing–Arizona Sky Survey and Mayall z-band Legacy Survey which is also the northern sky region of the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys, we selected a sample of 31,825 candidates of low surface brightness galaxies (LSBGs) with the mean effective surface brightness and the half-light radius based on the released photometric catalog and the machine learning model. The distribution of the LSBGs is bimodal in the g − r color, indicating the two distinct populations of the blue (g − r < 0.60) and red (g − r > 0.60) LSBGs. The blue LSBGs appear spiral, disk or irregular while the red LSBGs are spheroidal or elliptical and spatially clustered. This trend shows that the color has a strong correlation with galaxy morphology for LSBGs. In the spatial distribution, the blue LSBGs are more uniformly distributed while the red ones are highly clustered, indicating that red LSBGs preferentially populate a denser environment than the blue LSBGs. Besides, both populations have a consistent distribution of ellipticity (median ), half-light radius (median reff ∼ 4'') and Sérsic index (median n = 1), implying the dominance of the full sample by the round and disk galaxies. This sample has definitely extended the studies of LSBGs to a regime of lower surface brightness, fainter magnitude and broader other properties than the previously Sloan Digital Sky Survey-based samples.


Key words: catalogs – galaxies: fundamental parameters – galaxies: statistics – techniques: photometric

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