J/A+A/682/A4 DES Y3 low surface brightness galaxies (Thuruthipilly+, 2024)
Shedding light on low surface brightness galaxies in
Dark Energy Survey with transformers.
Thuruthipilly H., Junais, Pollo A., Sureshkumar U., Grespan M., Sawant P.,
Malek K., Zadrozny A.
<Astron. Astrophys. 682, A4 (2024)>
=2024A&A...682A...4T 2024A&A...682A...4T (SIMBAD/NED BibCode)
ADC_Keywords: Galaxies, photometry ; Optical ; Surveys ; Morphology
Keywords: methods: data analysis - techniques: image processing -
Galaxy formation - galaxies: clusters: general - galaxies: evolution
Abstract:
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°. 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.
Description:
The Dark Energy Survey (DES) is an optical-near-infrared imaging
survey covering ∼5000deg2 of the southern Galactic cap using the
Dark Energy Camera (DECam) on the 4-m Blanco Telescope at the Cerro
Tololo Inter-American Observatory (CTIO). We use data collected from
the first three years of DES observing (DES Y3 Gold; 2013-August -
2016-February).
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
catalog.dat 109 4083 Extended low-surface-brightness galaxy catalog
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See also:
https://des.ncsa.illinois.edu/releases/y3a2 : DES Y3 Home Page
Byte-by-byte Description of file: catalog.dat
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Bytes Format Units Label Explanations
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1- 9 I9 --- CoadID Coadd object identifier (COADDOBJECTID)
11- 20 F10.6 deg RAdeg Right Ascension (J2000) from galfit (RA)
22- 31 F10.6 deg DEdeg Declination (J2000) from galfit (DEC)
33- 37 F5.2 mag gmag g-band magnitude, galfit (g_gf)
39- 43 F5.2 mag gmagcor Extinction corrected g-bang magnitude
(g_cor)
45- 49 F5.2 mag/arcsec2 mug g-band mean surface brightness,
galfit (g_mu)
51- 55 F5.2 arcsec rhlg Half-light radius, g-band (r_g1/2)
57- 60 F4.2 --- n Sersic index (n)
62- 65 F4.2 --- q Axis ratio (q)
67- 70 F4.2 [Msun/kpc2] log(Sigma*) ?=- Stellar mass surface density
in log scale (log10(Sigma_star))
72- 75 F4.2 --- rchi2g Reduced chi-square of the g-band galfit
(g_rchi2)
77- 81 F5.2 mag imag ?=- i-band magnitude, galfit (i_gf)
83- 87 F5.2 mag imagcor ?=- Extinction corrected i-bang magnitude
(i_cor)
89- 93 F5.2 mag/arcsec2 mui i-band mean surface brightness from
galfit (i_mu)
95- 99 F5.2 arcsec rhli Half-light radius, i-band (r_i1/2)
101-109 F9.2 --- rchi2i Reduced chi-square of the i-band galfit
(i_rchi2)
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Acknowledgements:
Hareesh Thuruthipilly, hareesh.thuruthipilly(at)ncbj.gov.pl
(End) Patricia Vannier [CDS] 21-Nov-2023