Galaxies OBserved as Low-luminosity Identified Nebulae (GOBLIN): a catalog of 43,000 high-probability dwarf galaxy candidates in the UNIONS survey

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Main Authors: Heesters, Nick, Chemaly, David, Müller, Oliver, Sola, Elisabeth, Fabbro, Sébastien, Ferreira, Ashley, McConnachie, Alan W., Magnier, Eugene, Hudson, Michael J., Chambers, Kenneth, Hammer, François, Sanchez-Janssen, Ruben
Format: Preprint
Published: 2025
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author Heesters, Nick
Chemaly, David
Müller, Oliver
Sola, Elisabeth
Fabbro, Sébastien
Ferreira, Ashley
McConnachie, Alan W.
Magnier, Eugene
Hudson, Michael J.
Chambers, Kenneth
Hammer, François
Sanchez-Janssen, Ruben
author_facet Heesters, Nick
Chemaly, David
Müller, Oliver
Sola, Elisabeth
Fabbro, Sébastien
Ferreira, Ashley
McConnachie, Alan W.
Magnier, Eugene
Hudson, Michael J.
Chambers, Kenneth
Hammer, François
Sanchez-Janssen, Ruben
contents The detection of low surface brightness galaxies beyond the Local Group poses significant observational challenges, yet these faint systems are fundamental to our understanding of dark matter, hierarchical galaxy formation, and cosmic structure. Their abundance and distribution provide crucial tests for cosmological models, particularly regarding the small-scale predictions of $Λ$CDM. We present a systematic detection framework for dwarf galaxy candidates in Ultraviolet Near Infrared Optical Northern Survey (UNIONS) data covering 4,861 deg$^{2}$. Our pipeline preprocesses UNIONS gri-band data through binning, artifact removal, and stellar masking, then employs MTObjects (MTO) for low surface brightness detection. After parameter cuts and cross-matching, we obtain $\sim$360 candidates per deg$^{2}$, totaling $\sim$1.5 million candidates forming our GOBLIN (Galaxies OBserved as Low-luminosity Identified Nebulae) catalog. We fine-tuned the deep learning model Zoobot, pre-trained on Galaxy Zoo labels, for classification. Training data came from visual inspection of literature candidates with probability labels from expert assessments, capturing consensus and uncertainty. Applied to all MTO objects, our method identifies 42,965 dwarf candidates with probability $>$ 0.8, including 23,072 with probability $>$ 0.9. High-probability candidates correlate spatially with massive galaxies (log$(M_{*}/M_{\odot}) \geq$ 10) within 120 Mpc. While some of these objects may have been previously identified in other surveys, we present this extensive catalog of candidates, including their positions, structural parameter estimates, and classification probabilities, as a resource for the community to enable studies of galaxy formation, evolution, and the distribution of dwarf galaxies in different environments.
format Preprint
id arxiv_https___arxiv_org_abs_2505_18307
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Galaxies OBserved as Low-luminosity Identified Nebulae (GOBLIN): a catalog of 43,000 high-probability dwarf galaxy candidates in the UNIONS survey
Heesters, Nick
Chemaly, David
Müller, Oliver
Sola, Elisabeth
Fabbro, Sébastien
Ferreira, Ashley
McConnachie, Alan W.
Magnier, Eugene
Hudson, Michael J.
Chambers, Kenneth
Hammer, François
Sanchez-Janssen, Ruben
Astrophysics of Galaxies
The detection of low surface brightness galaxies beyond the Local Group poses significant observational challenges, yet these faint systems are fundamental to our understanding of dark matter, hierarchical galaxy formation, and cosmic structure. Their abundance and distribution provide crucial tests for cosmological models, particularly regarding the small-scale predictions of $Λ$CDM. We present a systematic detection framework for dwarf galaxy candidates in Ultraviolet Near Infrared Optical Northern Survey (UNIONS) data covering 4,861 deg$^{2}$. Our pipeline preprocesses UNIONS gri-band data through binning, artifact removal, and stellar masking, then employs MTObjects (MTO) for low surface brightness detection. After parameter cuts and cross-matching, we obtain $\sim$360 candidates per deg$^{2}$, totaling $\sim$1.5 million candidates forming our GOBLIN (Galaxies OBserved as Low-luminosity Identified Nebulae) catalog. We fine-tuned the deep learning model Zoobot, pre-trained on Galaxy Zoo labels, for classification. Training data came from visual inspection of literature candidates with probability labels from expert assessments, capturing consensus and uncertainty. Applied to all MTO objects, our method identifies 42,965 dwarf candidates with probability $>$ 0.8, including 23,072 with probability $>$ 0.9. High-probability candidates correlate spatially with massive galaxies (log$(M_{*}/M_{\odot}) \geq$ 10) within 120 Mpc. While some of these objects may have been previously identified in other surveys, we present this extensive catalog of candidates, including their positions, structural parameter estimates, and classification probabilities, as a resource for the community to enable studies of galaxy formation, evolution, and the distribution of dwarf galaxies in different environments.
title Galaxies OBserved as Low-luminosity Identified Nebulae (GOBLIN): a catalog of 43,000 high-probability dwarf galaxy candidates in the UNIONS survey
topic Astrophysics of Galaxies
url https://arxiv.org/abs/2505.18307