Image-Based Multi-Survey Classification of Light Curves with a Pre-Trained Vision Transformer
Daniel Moreno-Cartagena, Guillermo Cabrera-Vives, Alejandra M. Muñoz Arancibia, Pavlos Protopapas, Francisco Förster +8 more
7/15/2025
astro-ph.IMcs.CV
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Abstract
We explore the use of Swin Transformer V2, a pre-trained vision Transformer, for photometric classification in a multi-survey setting by leveraging light curves from the Zwicky Transient Facility (ZTF) and the Asteroid Terrestrial-impact Last Alert System (ATLAS). We evaluate different strategies for integrating data from these surveys and find that a multi-survey architecture which processes them jointly achieves the best performance. These results highlight the importance of modeling survey-specific characteristics and cross-survey interactions, and provide guidance for building scalable classifiers for future time-domain astronomy.
