[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-127887-en":3,"doc-seo-127887-105":31,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},127887,2336474459895,"Aria","https://ap-avatar.wpscdn.com/avatar/22000baeef7a5ed0655?x-image-process=image/resize,m_fixed,w_180,h_180&k=1786071322749376916",8,"Research & Report","Low surface brightness galaxies from BASS+MzLS with Machine Learning","Combining about 5000 deg² of the Beijing-Arizona Sky Survey (BASS) and the Mayall z-band Legacy Survey (MzLS)—covering the northern sky region of the DESI Legacy Imaging Surveys—we build a machine-learning–based photometric sample of 31,825 low surface brightness galaxy candidates. Their mean effective surface brightness and size limits span 24.2\u003Cµ̄eff,g\u003C28.8 mag arcsec⁻² and 2.5″\u003Creff\u003C20″. Color bimodality separates blue and red systems, linking color to morphology: blue galaxies show disk/spiral/irregular structures, red ones are spheroidal/elliptical and more clustered.","arXiv :2404 . 18408v2 [ astro-ph .GA] 30 Apr 2024  \nResearch in Astronomy and Astrophysics manuscript no.  \n(LATEX: ms2024-0041.tex; printed on May 1, 2024; 1:08)  \nLow surface brightness galaxies from BASS+MzLS with Machine Learning  \nPeng-liang Du 1 ,2 , Wei Du 1 , Bing-qing Zhang 1 , Zhen-ping Yi3 , Min He 1 , Hong Wu 1 ,2   \n1 Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing,100101,China; [wdu@nao.cas.cn](wdu@nao.cas.cn)  \n2 School of Astronomy and Space Science, University of Chinese Academy of Sciences, 19A Yuquan Road, Shijingshan District, Beijing, 100049, China  \n3 School of Mechanical, Electrical and Information Engineering, Shandong University, 180 Wenhua Xilu, Weihai, 264209, Shandong, People’s Republic of China  \nReceived 20XX Month Day; accepted 20XX Month Day  \nAbstract From ∼ 5000 deg2 of the combination of the Beijing-Arizona Sky Survey (BASS) and Mayall z-band Legacy Survey (MzLS) which is also the northern sky region of the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys, we selected a sample of  \n31,825 candidates oflow surface brightness galaxies (LSBGs) with the mean effective surface brightness 24.2 \u003C µ¯eff ,g \u003C 28.8 mag arcsec −2 and the half-light radius 2.5′′ \u003C reff \u003C 20′′ based on the released photometric catalogue and the machine learning model. The distribution of the LSBGs is of bimodality in the g -r color, indicating the two distinct populations of the blue (g -r \u003C 0.60) and the red (g -r > 0.60) LSBGs. The blue LSBGs appear spiral, disk or irregular while the red LSBGs are spheroidal or ellipitcal 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 populated denser environment than the blue LSBGs. Besides, both populations have consistent distribution of ellipticity (median ϵ ∼ 0.3), half-light radius (median reff ∼ 4′′), and S´ersic 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 SDSS-based samples.  \nKey words: catalogues – galaxies: disc – galaxies: fundamental parameters – galaxies: statis  \ntics – techniques: photometric  \n2 P.-L. Du et al.  \n1 INTRODUCTION  \nLow surface brightness galaxies (LSBGs) are traditionally defined as galaxies with the B-band central surface brightnesses (µ0 ) fainter than a threshold value within 21 .65-23.0 mag arcsec −2(Freeman 1970; Impey & Bothun 1997; O’Neil et al. 1997; Zhong et al. 2008; Du et al. 2015) . In addition, the µ0 in some other optical or near infrared bands such as the r (Courteau 1996), R (Adami et al. 2006), and KS bands (Monnier Ragaigne et al. 2003) have been adopted to distinguish between LSBGs and high surface brightness galaxies (HSBGs) as well. Besides the µ0 , the mean surface brightness within effective radius (µ¯eff ) has also been utilized to define LSBGs, for example, the criterion of the g-band µ¯eff > 24.2-24.3 mag arcsec−2 was once used to select LSBGs in Greco et al. (2018); Tanoglidis et al. (2021b), allowing for the retention of nucleated galaxies in the sample.  \nLSBGs are characterized by their diffuse, extended, low-density stellar discs and most of them are blue in color (de Blok et al. 1996; Burkholder et al. 2001; O’Neil et al. 2004; Trachternach et al. 2006; Vorobyovet al. 2009; Zhang et al. 2024) . In morphology, they are disk-like or irregular (de Blok & McGaugh 1996, 1997; de Blok et al. 2001) . Compared to HSBGs, LSBGs have different properties, including low star formation rates (van der Hulst et al. 1993; van Zee et al. 1997; van den Hoek et al. 2000; Wyder et al. 2009; Schombert et al. 2011; Galaz et al. 2","cbCaimkbS5mq8WD1","https://ap.wps.com/l/cbCaimkbS5mq8WD1","pdf",9754350,2,1,20,"English","en",105,"# Introduction\n## Definitions and selection criteria for LSBGs\n## Physical properties and significance of LSBGs\n## Prior surveys and motivation for wide-field searching\n## Bimodality and population differences in the new sample","[{\"question\":\"How were low surface brightness galaxy candidates selected in this study?\",\"answer\":\"The work uses released photometric catalogs from BASS and MzLS together with a machine learning model to select 31,825 candidate low surface brightness galaxies.\"},{\"question\":\"What selection ranges characterize the final LSBG sample?\",\"answer\":\"The sample is defined by mean effective surface brightness and half-light radius constraints: 24.2\\u003cµ̄eff,g\\u003c28.8 mag arcsec⁻² and 2.5″\\u003creff\\u003c20″.\"},{\"question\":\"How does color relate to morphology and environment for LSBGs?\",\"answer\":\"The galaxies show bimodality in g−r color that corresponds to morphology: blue LSBGs tend to be spiral/disk/irregular, while red LSBGs tend to be spheroidal/elliptical and preferentially reside in denser environments.\"}]","Low surface brightness galaxies from BASS+MzLS with Machine Learning | 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were low surface brightness galaxy candidates selected in this study?","Question",{"text":76,"@type":77},"The work uses released photometric catalogs from BASS and MzLS together with a machine learning model to select 31,825 candidate low surface brightness galaxies.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"What selection ranges characterize the final LSBG sample?",{"text":81,"@type":77},"The sample is defined by mean effective surface brightness and half-light radius constraints: 24.2\u003Cµ̄eff,g\u003C28.8 mag arcsec⁻² and 2.5″\u003Creff\u003C20″.",{"name":83,"@type":74,"acceptedAnswer":84},"How does color relate to morphology and environment for LSBGs?",{"text":85,"@type":77},"The galaxies show bimodality in g−r color that corresponds to morphology: blue LSBGs tend to be spiral/disk/irregular, while red LSBGs tend to be spheroidal/elliptical and preferentially reside in denser 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