[ascl:2407.015]
AstroCLIP: Multimodal contrastive pretraining for astronomical data
Lanusse, Francois;
Parker, Liam;
Golkar, Siavash;
Cranmer, Miles;
Bietti, Alberto;
Eickenberg, Michael;
Krawezik, Geraud;
McCabe, Michael;
Ohana, Ruben;
Pettee, Mariel;
Regaldo-Saint Blancard, Bruno;
Tesileanu, Tiberiu;
Cho, Kyunghyun;
Ho, Shirley;
Polymathic AI Collaboration
AstroCLIP performs contrastive pre-training between two different kinds of astronomical data modalities (multi-band imaging and optical spectra) to yield a meaningful embedding space which captures physical information about galaxies and is shared between both modalities. The embeddings can be used as the basis for competitive zero- and few-shot learning on a variety of downstream tasks, including similarity search, redshift estimation, galaxy property prediction, and morphology classification.