Journal article
Galaxy Zoo: Cosmic Dawn–morphological classifications for over 41 000 galaxies in the Euclid Deep Field North from the Hawaii Two-0 Cosmic Dawn survey
- Abstract:
- We present morphological classifications of over 41 000 galaxies out to across 6 deg2 of the Euclid Deep Field North (EDFN) from the Hawaii Twenty Square Degree (H20) survey, a part of the wider Cosmic Dawn survey. Galaxy Zoo citizen scientists play a crucial role in the examination of large astronomical data sets through crowdsourced data mining of extragalactic imaging. This iteration, Galaxy Zoo: Cosmic Dawn (GZCD), saw tens of thousands of volunteers and the deep learning foundation model Zoobot collectively classify objects in ultra-deep multiband Hyper Suprime-Cam (HSC) imaging down to a depth of . Here, we present the details and general analysis of this iteration, including the use of Zoobot in an active learning cycle to improve both model performance and volunteer experience, as well as the discovery of 51 new gravitational lenses in the EDFN. We also announce the public data release of the classifications for over 45 000 subjects, including more than 41 000 galaxies (median of ), along with their associated image cut-outs. This data set provides a valuable opportunity for follow-up imaging of objects in the EDFN as well as acting as a truth set for training deep learning models for application to ground-based surveys like that of the Ultraviolet Near-Infrared Optical Northern Survey (UNIONS) collaboration and the newly operational Vera C. Rubin Observatory.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 4.5MB, Terms of use)
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- Publisher copy:
- 10.1093/mnras/staf2250
Authors
+ National Science Foundation
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- Funder identifier:
- 10.13039/100000001
- Grant:
- IIS-2334033
+ Danish National Research Foundation
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- Funder identifier:
- https://ror.org/00znyv691
- Grant:
- DNRF140
- Publisher:
- Oxford University Press
- Journal:
- Monthly Notices of the Royal Astronomical Society More from this journal
- Volume:
- 546
- Issue:
- 3
- Pages:
- staf2250
- Article number:
- staf2250
- Publication date:
- 2025-12-22
- Acceptance date:
- 2025-12-17
- DOI:
- EISSN:
-
1365-2966
- ISSN:
-
0035-8711
- Language:
-
English
- Keywords:
- Source identifiers:
-
3760450
- Deposit date:
-
2026-02-14
- ARK identifier:
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- Copyright date:
- 2025
- Licence:
- CC Attribution (CC BY)
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