J/A+A/661/A52 North Ecliptic Pole merging galaxy catalogue (Pearson+, 2022)
North Eclotic Pole merging galaxy catalogue.
Pearson W.J., Suelves L.E., Ho S.C.-C., Oi N., Brough S., Holwerda B.W.,
Hopkins A.M., Huang T.-C., Hwang H.S., Kelvin L.S., Kim S.J.,
Lopez-Sanchez A.R., MaLek K., Pearson C., Poliszczuk A., Pollo A.,
Rodriguez-Gomez V., Shim H., Toba Y., Wang L.
<Astron. Astrophys. 661, A52 (2022)>
=2022A&A...661A..52P 2022A&A...661A..52P (SIMBAD/NED BibCode)
ADC_Keywords: Galaxy catalogs ; Morphology
Keywords: catalogs - galaxies: interactions - galaxies: evolution -
methods: data analysis - galaxies: statistics
Abstract:
We aim to generate a catalogue of merging galaxies within the
5.4deg2. North Ecliptic Pole over the redshift range 0.0<z<0.3. To
do this, imaging data from the Hyper Suprime-Cam will be used along
with morphological parameters derived from these same data. The
catalogue is generated using a hybrid approach. Two neural networks
are trained to perform binary merger non-merger classifications: one
for galaxies with z<0.15 and another for 0.15≤z<0.30. Each network
uses the image and morphological parameters of a galaxy as input. The
galaxies that are identified as merger candidates by the network are
then visually checked by experts. The resulting mergers will be used
to calculate the merger fraction as a function of redshift and
compared with literature results. We found that 86.3% of galaxy
mergers at z<0.15 and 79.0% of mergers at 0.15≤z<0.30 are expected to
be correctly identified by the networks. Of the 34264 galaxies
classified by the neural networks, 10195 were found to be merger
candidates. Of these, 2109 were visually identified to be merging
galaxies. We find that the merger fraction increases with redshift,
consistent with literature results from observations and simulations,
and that there is a mild star-formation rate enhancement in the merger
population of a factor of 1.102±0.084.
Description:
Catalogues of optical, r-band morphologies and convolutional neural
network and visual merger classification for galaxies detected in the
North Ecliptic Pole by the Hyper Suprime Cam.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
table1.dat 295 34264 Catalogues of optical, r-band morphologies and
convolutional neural network
table4.dat 43 34264 Visual merger classification
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Byte-by-byte Description of file: table1.dat
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Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1- 17 I17 --- HSC HSC ID
19- 31 F13.9 --- Asymm Asymmetry as described in Lotz et al.
(2004AJ....128..163L 2004AJ....128..163L, Cat. J/AJ/128/163)
33- 43 F11.9 --- Concent Concentration as described in Lotz et al.
(2004AJ....128..163L 2004AJ....128..163L, Cat. J/AJ/128/163)
45- 57 F13.9 --- Dev Deviation as described in Peth et al.
(2016MNRAS.458..963P 2016MNRAS.458..963P,
Cat. J/MNRAS/458/963)
59- 69 F11.9 --- ell-Asymm Ellipticity relative to the point that
minimizes the asymmetry
71- 81 F11.9 --- ell-Cent Ellipticity relative to the centroid
83- 93 F11.9 --- elong-Asymm Elongation relative to the point that
minimizes the asymmetry
95-106 F12.9 --- elong-Cent Elongation relative to the centroid
108-118 F11.9 --- gini Gini coefficient as described in Lotz et
al. (2004AJ....128..163L 2004AJ....128..163L,
Cat. J/AJ/128/163)
120-131 F12.9 --- giniM20Bulge Gini-M20 bulge statistic as defined in
Rodriguez-Gomez et al.
(2019MNRAS.483.4140R 2019MNRAS.483.4140R)
133-144 F12.9 --- giniM20Merger Gini-M20 merger statistic as defined in
Rodriguez-Gomez et al.
(2019MNRAS.483.4140R 2019MNRAS.483.4140R)
146-156 F11.9 --- Int Intensity as described in Peth et al.
(2016MNRAS.458..963P 2016MNRAS.458..963P,
Cat. J/MNRAS/458/963)
158-169 F12.9 --- M20 M_20 coefficient as described in Lotz et
al. (2004AJ....128..163L 2004AJ....128..163L,
Cat. J/AJ/128/163)
171-181 F11.9 --- Multimode Multimode as described in Freeman et al.
(2013MNRAS.434..282F 2013MNRAS.434..282F) and Peth et al.
(2016MNRAS.458..963P 2016MNRAS.458..963P,
Cat. J/MNRAS/458/963)
183-194 F12.9 pix r20 Radius that contains 20% of the light
196-207 F12.9 pix r50 Radius that contains 50% of the light
209-220 F12.9 pix r80 Radius that contains 80% of the light
222-236 F15.9 --- SersicAmp Amplitude of the 2D Sersic fit at the
effective (half-light) radius
238-249 F12.9 --- SersicEllip Ellipticity of the 2D Sersic fit
251-263 F13.9 --- Sersicn Sersic index n
265-277 F13.9 --- Smooth Smoothness (a.k.a. clumpiness) as defined
in Lotz et al. (2004AJ....128..163L 2004AJ....128..163L,
Cat. J/AJ/128/163)
279-291 F13.9 --- SNperpixel signal-to-noise per pixel
293 I1 --- Flag [0/1] 1 if the fit is bad
295 I1 --- FlagSersic [0/1] 1 if the Sersic fit is bad
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Byte-by-byte Description of file: table4.dat
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Bytes Format Units Label Explanations
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1- 17 I17 --- HSC HSC ID
19- 29 F11.9 --- FracMerger NN merger fraction
31- 41 F11.9 --- FracNonmerger NN non-merger fraction
43 I1 --- VisMerger [0/1] Visually confirmed merger
(1: merger, 0: non-merger)
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Acknowledgements:
William J. Pearson, william.pearson(at)ncbj.gov.pl
(End) Patricia Vannier [CDS] 22-Feb-2022