“Deep learning on galaxy images: training dataset”的版本间差异

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==high z galaxy sample==
==high z galaxy sample==
* COSMOS F814W galaxy postages
* COSMOS F814W galaxy postages
* COSMOS F814W structural parameters (Sersic index, Re, CAS, GINI, M20) catalog (F814W<23.5)
* CANDELS 5 fields galaxy postages (H<24.5)
* CANDELS 5 fields galaxy postages (H<24.5)
* CANDELS 5 fields GALFIT structural parameters catalog
⚫
:*contact zhuchen@staff.shnu.edu.cn for more information
* CANDELS 5 fields two components structural parameters catalog (H<23, 0<z<2)
⚫
contact zhuchen@staff.shnu.edu.cn for more information


==Mock galaxies==
==Mock galaxies==
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*generate using GalSim-Hub[https://arxiv.org/abs/2008.03833]
*generate using GalSim-Hub[https://arxiv.org/abs/2008.03833]


* A sample of CGS galaxies[https://arxiv.org/abs/1111.4605] manually move to high redshifts and observed in other surveys(PS1, SDSS stripe82, CANDELS_AEGIS , Hubble Frontier Fields) , contact ssy@shao.ac.cn for more information
* A sample of CGS galaxies[https://arxiv.org/abs/1111.4605] manually move to high redshifts and mocked in other surveys(PS1, SDSS stripe82, CANDELS_AEGIS , Hubble Frontier Fields) , contact ssy@shao.ac.cn for more information

2021年11月11日 (四) 08:58的最新版本

This page is used to collect the training dataset for deep learning applications on galaxy images.

If you want to contribute, please contact Shiyin Shen (ssy@shao.ac.cn)

local galaxy sample

  • galaxy zoo data [1]
  • Galaxy Zoo DECaLS[2]
  • stamps of SDSS main sample galaxies(r<17.77) in DESI [3]

high z galaxy sample

  • COSMOS F814W galaxy postages
  • COSMOS F814W structural parameters (Sersic index, Re, CAS, GINI, M20) catalog (F814W<23.5)
  • CANDELS 5 fields galaxy postages (H<24.5)
  • CANDELS 5 fields GALFIT structural parameters catalog
  • CANDELS 5 fields two components structural parameters catalog (H<23, 0<z<2)

contact zhuchen@staff.shnu.edu.cn for more information

Mock galaxies

  • generate using GalSim (with CSST-like survey parameters)
  • tel_diam=200mm, exptime=150s, lam=5500A, sky_mag=23, psf_sigma=0.2, gain=1, readnoise=5, pixel_scale=0.074
  • generate using GalSim-Hub[4]
  • A sample of CGS galaxies[5] manually move to high redshifts and mocked in other surveys(PS1, SDSS stripe82, CANDELS_AEGIS , Hubble Frontier Fields) , contact ssy@shao.ac.cn for more information
取自“http://cluster.shao.ac.cn/wiki/index.php?title=Deep_learning_on_galaxy_images:_training_dataset&oldid=4327”