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Published March 19, 2025 | Version 0.0.1
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Euclid Quick Data Release (Q1): First visual morphology catalogue

Authors/Creators

  • 1. ROR icon University of Toronto
  • 2. ROR icon University of Manchester
  • 3. ROR icon Université Paris Descartes
  • 4. ROR icon Observatoire de Lyon
  • 5. EDMO icon Haverford College
  • 6. ROR icon European Space Astronomy Centre
  • 7. EDMO icon European Space Agency
  • 8. ROR icon The Open University
  • 9. ROR icon University of Trieste

Contributors

Description

Image to be added after embargo lifts on 19th

 

Contents

  1. Catalogue
    1. List of ID columns and morphology columns
    2. List of morphology questions and answers available
    3. List of additional columns copied from MER (flux, ellipticity, area, etc.)
  2. Images

 

Full documentation is available here. Below is a summary.

1. Catalogue

The morphology catalogue covers galaxies which are either bright or extended. Specifically, it includes galaxies matching one of the following criteria:

  • segmentation area > 700 pixels, or...
  • VIS < 20.5 AND segmentation area > 200 pixels

The measurements were made by Zoobot foundation models, finetuned on Euclid galaxies using the responses of Galaxy Zoo volunteers.

Our models were trained using galaxies from the selection cuts above but with the first option requiring 1200 pixels. Therefore, galaxies between 700 and 1200 pixels in area are may have less reliable measurements. 

The catalogue file is morphology_catalogue (.parquet or .csv, the contents are identical). It includes the following columns:

release_name Always Q1_R1, for now
tile_index Euclid tile index i.e. which MER tile hosts this galaxy
object_id Euclid object id i.e. the MER catalogue identifier for this galaxy
segmentation_map_id Alternative Euclid identifier. The first 9 digits are the tile index, the other digits match the internal segmentation id of the source.
right_ascension in degrees, from the MER catalogue
declination in degrees, from the MER catalogue
{question}_{answer}_fraction  e.g. smooth-or-featured_smooth_fraction. The fraction of volunteers expected to give this answer to this morphology question. Probably the morphology columns you want. 
{question}_{answer}_dirichlet e.g. smooth-or-featured_smooth_dirichlet. The concentration for a Dirichlet distribution (useful for uncertainties). See the paper.
warning_galaxy_fails_training_cuts Marks galaxies between 700px and 1200px, where performance may be lower. See above.
cutout_width_arcsec Width (and height) of cutout in arcseconds

 

The following questions and answers are available. 

Question Answer Notes
smooth-or-featured smooth May include face-on lenticulars, which are better identified with e.g. Sersic indices
how-rounded round  
how-rounded in-between  
how-rounded cigar-shaped  
smooth-or-featured featured-or-disk The question branch most commonly used by researchers
disk-edge-on yes  
edge-on-bulge boxy  
edge-on-bulge none  
edge-on-bulge rounded  
disk-edge-on no  
has-spiral-arms yes  
spiral-winding tight  
spiral-winding medium  
spiral-winding loose  
spiral-arm-count 1  
spiral-arm-count 2  
spiral-arm-count 3  
spiral-arm-count 4  
spiral-arm-count more-than-4 Often overlaps with cant-tell
spiral-arm-count cant-tell Often overlaps with more-than-4
has-spiral-arms no  
bar strong Bar strength is a mix of length and width
bar weak  
bar no  
bulge-size dominant  
bulge-size large  
bulge-size moderate  
bulge-size small  
bulge-size none  
smooth-or-featured problem  
problem star  
problem zoom i.e. bad zoom, a cutout which is too wide
problem artifact  
artifact satellite  
artifact scattered  
artifact diffraction  
artifact ray  
artifact saturation  
artifact other  
artifact ghost Dichrotic ghosts
merging none  
merging minor_disturbance  
merging major_disturbance Primarily obvious tidal tails and similar features
merging merger Primarily "dramatic" ongoing mergers
clumps yes Not recommended; we are building clump-specific models
clumps no Not recommended; we are building clump-specific models

 

For convenience, we have also copied over some useful MER catalogue columns. The schema for the full MER catalogue is here. Additionally, Euclid also makes available many other tables with e.g. photometric redshifts, estimated masses, etc. These are documented here. All fluxes are in micro-janskies (uJy).

 

segmentation_area Number of pixels included in SourceExtractor++ mask of galaxy (0.1 arcsec/pixel). 
flux_segmentation Total VIS flux inside the segmentation mask above.
mag_segmentation As above, converted to magnitude. ```mag = -2.5*log10(flux[muJy])+23.9```. Not technically in MER catalogue.
flux_detection_total VIS flux measured within a Kron aperture in the detection image. FLUX_AUTO in SourceExtractor.
flux_vis_1fwhm_aper VIS flux within an aperture of radius 1 FWHM. 
mumax_minus_mag A star/galaxy diagnostic. The morphology catalogue uses the recommended filter MUMAX_MINUS_MAG>=-2.6 to reject stars.
mu_max Peak surface brightness above the background in the detection band (directly from SExtractor)
ellipticity A parametrization of how stretched an object is in the detection band (VIS, here), computed from the minor and major axes of the object itself (directly from SExtractor). [I assume this is the major/minor axis ratio]
kron_radius Major semi-axis (in pixels) of the elliptical aperture used for total (Kron) aperture photometry on the detection image

 

2. Images

We are sharing the original cutout images as shown to Galaxy Zoo volunteers. The images are named like {tile_index}_{object_id}.jpg, where the negative sign ('-') in object id is replaced with 'NEG' to avoid path issues. You can construct the file paths from the morphology catalogue. For example:

df['file_loc'] = df['tile_index'].astype(str) + '_' + df['object_id'].astype(str).str.replace('-', 'NEG') + '_.jpg'
 
Each ZIP has images of every galaxy. There are three ZIP files, one for each image processing version. Volunteers were shown all three versions. The model predictions are made using the first version (the colour composite).
 
Fig 3 in the Q1 visual morphology paper shows an example galaxy in all three versions.
 

The VIS+Y images are composites with VIS in the blue channel and Y in the red channel (and the median of VIS and Y in the green channel, but this isn't visible). They use an arcinsh stretch, with the stretch designed to balance the contribution from each band.

The VIS only images are black-and-white, and also use an arcsinh stretch.

The VIS LSB images use a more complicated stretch to highlight LSB features.

Full details of the image processing are in the Q1 visual morphology paper.

Files

morphology_catalogue.csv

Files (698.7 MB)

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md5:652e4546c63085c37539a9e9664f64e2
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Additional details

Dates

Available
2025-03-19
Initial public release

Software

Programming language
Python