DES Y3 low surface brightness galaxies J/A+A/682/A4 ivo://CDS.VizieR/J/A+A/682/A4 doi:10.26093/cds/vizier.36820004 CDS Thuruthipilly H. Junais Pollo A. Sureshkumar U. Grespan M. Sawant P.,Malek K. Zadrozny A. 2026-07-03T06:35:58Z 2024-01-26T10:42:40Z CDS support team CDS, Observatoire de Strasbourg, 11 rue de l'Universite, F-67000 Strasbourg, France cds-question@unistra.fr galaxies photometry visible-astronomy surveys galaxy-classification-systems Low surface brightness galaxies (LSBGs) which are defined as galaxies that are fainter than the night sky, play a crucial role in understanding galaxy evolution and cosmological models. Upcoming large-scale surveys like Rubin Observatory Legacy Survey of Space and Time (LSST) and Euclid are expected to observe billions of astronomical objects. In this context, using semi-automatic methods to identify LSBGs would be a highly challenging and time-consuming process and demand automated or machine learning-based methods to overcome this challenge. We study the use of transformer models in separating LSBGs from artefacts in the data from the Dark Energy Survey (DES) data release 1. Using the transformer models, we then search for new LSBGs from the DES that the previous searches may have missed. Properties of the newly found LSBGs are investigated, along with an analysis of the properties of the total LSBG sample in DES. We identified 4083 new LSBGs in DES, adding an additional to the LSBGs already known in DES. This also increased the number density of LSBGs in DES to 5.5{deg}. We performed a clustering analysis of the LSBGs in DES using an angular two-point auto-correlation function and found that LSBGs cluster more strongly than their high surface brightness counterparts. We associated 1310 LSBGs with galaxy clusters and identified 317 among them as ultra-diffuse galaxies (UDGs). We found that these cluster LSBGs are getting bluer and larger in size towards the edge of the clusters when compared with those in the centre. Transformer models have the potential to be on par with convolutional neural networks as state-of-the-art algorithms in analysing astronomical data. 2024A&A...682A...4T https://cdsarc.cds.unistra.fr/viz-bin/cat/J/A+A/682/A4 Catalog Research IsServedBy TAP VizieR generic service IsServedBy Conesearch service related-to https://des.ncsa.illinois.edu/releases/y3a2 : DES Y3 Home Page https://cds.unistra.fr/vizier-org/licences_vizier.html https://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/A+A/682/A4 https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/A+A/682/A4 http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/A+A/682/A4 https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/A+A/682/A4 https://vizier.iucaa.in/viz-bin/votable?-source=J/A+A/682/A4 http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/A+A/682/A4 GET text/xml+votable https://tapvizier.cds.unistra.fr/TAPVizieR/tap Cone search capability for table J/A+A/682/A4/catalog (Extended low-surface-brightness galaxy catalog) https://vizier.cds.unistra.fr/viz-bin/conesearch/J/A+A/682/A4/catalog? https://vizier.iucaa.in/viz-bin/conesearch/J/A+A/682/A4/catalog? http://vizieridia.saao.ac.za/viz-bin/conesearch/J/A+A/682/A4/catalog? 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g-bang magnitude (g_cor) mag phot.mag;em.opt.B float mug g-band mean surface brightness, galfit (g_mu) mag.arcsec**-2 phot.mag.sb float rhlg Half-light radius, g-band (r_g1/2) arcsec phys.angSize;src float n Sersic index (n) stat.fit.param float q Axis ratio (q) phys.size.axisRatio float log(Sigma*) ? Stellar mass surface density in log scale (log10(Sigma_star)) log(solMass.kpc**-2) phys.density float nullable rchi2g Reduced chi-square of the g-band galfit (g_rchi2) meta.note float imag ? i-band magnitude, galfit (i_gf) mag phot.mag;em.opt.I float nullable imagcor ? Extinction corrected i-bang magnitude (i_cor) mag phot.mag;em.opt.I float nullable mui i-band mean surface brightness from galfit (i_mu) mag.arcsec**-2 phot.mag.sb;em.opt.I float rhli Half-light radius, i-band (r_i1/2) arcsec phys.angSize;src float rchi2i Reduced chi-square of the i-band galfit (i_rchi2) stat.fit.chi2 double Simbad Simbad column added by the CDS meta.ref.url char recno Record number assigned by the VizieR team. Should Not be used for identification. meta.record int CoadID Coadd object identifier (COADD_OBJECT_ID) meta.id;meta.main long