Image-Based Multi-Survey Classification of Light Curves with a Pre-Trained Vision Transformer

• URL: http://arxiv.org/abs/2507.11711v1
• Date: Tue, 15 Jul 2025 20:30:21 GMT
• Title: Image-Based Multi-Survey Classification of Light Curves with a Pre-Trained Vision Transformer
• Authors: Daniel Moreno-Cartagena, Guillermo Cabrera-Vives, Alejandra M. Muñoz Arancibia, Pavlos Protopapas, Francisco Förster, Márcio Catelan, A. Bayo, Pablo A. Estévez, P. Sánchez-Sáez, Franz E. Bauer, M. Pavez-Herrera, L. Hernández-García, Gonzalo Rojas,
• Abstract summary: We explore the use of Swin Transformer V2, a pre-trained vision Transformer, for photometric classification in a multi-survey setting.<n>We evaluate different strategies for integrating data from the Zwicky Transient Facility (ZTF) and the Asteroid Terrestrial-impact Last Alert System (ATLAS)
• Score: 31.76431580841178
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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