GOBLIN. dwarf galaxy candidates in UNIONS

With ~4000deg^2^ in g, r and i, this amounts to ~1.5 million candidates that form our GOBLIN (Galaxies OBserved as Low-luminosity Identified Nebulae) catalog. For the final classification of these candidates, we fine-tuned the deep learning model Zoobot, which was pre- trained based on labels from the Galaxy Zoo project. We created our training dataset by visually inspecting dwarf galaxy candidates from existing literature catalogs within our survey area and assigning probability labels based on averaged expert assessments.

This approach captures both consensus and uncertainty among experts. Applied to all detected MTO objects, our method identifies 42965 dwarf galaxy candidates with probability scores >0.8, of which 23072 have probabilities exceeding 0.9. The spatial distribution of high-probability candidates reveals a correlation with the locations of massive galaxies (log(M*/M_{sun}_)>=10) within 120Mpc.

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.