Image-Based Multi-Survey Classification of Light Curves with a Pre-Trained Vision Transformer
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | , , , , , , , , , , , , |
|---|---|
| Format: | Preprint |
| Publié: |
2025
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866913943529717760 |
|---|---|
| author | Moreno-Cartagena, Daniel Cabrera-Vives, Guillermo Arancibia, Alejandra M. Muñoz Protopapas, Pavlos Förster, Francisco Catelan, Márcio Bayo, A. Estévez, Pablo A. Sánchez-Sáez, P. Bauer, Franz E. Pavez-Herrera, M. Hernández-García, L. Rojas, Gonzalo |
| author_facet | Moreno-Cartagena, Daniel Cabrera-Vives, Guillermo Arancibia, Alejandra M. Muñoz Protopapas, Pavlos Förster, Francisco Catelan, Márcio Bayo, A. Estévez, Pablo A. Sánchez-Sáez, P. Bauer, Franz E. Pavez-Herrera, M. Hernández-García, L. Rojas, Gonzalo |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_11711 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Image-Based Multi-Survey Classification of Light Curves with a Pre-Trained Vision Transformer Moreno-Cartagena, Daniel Cabrera-Vives, Guillermo Arancibia, Alejandra M. Muñoz Protopapas, Pavlos Förster, Francisco Catelan, Márcio Bayo, A. Estévez, Pablo A. Sánchez-Sáez, P. Bauer, Franz E. Pavez-Herrera, M. Hernández-García, L. Rojas, Gonzalo Instrumentation and Methods for Astrophysics Computer Vision and Pattern Recognition 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. |
| title | Image-Based Multi-Survey Classification of Light Curves with a Pre-Trained Vision Transformer |
| topic | Instrumentation and Methods for Astrophysics Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2507.11711 |