Capturing star formation activity from compressed photometric images of galaxies
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arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866908473322635264 |
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| author | Oh, Kyuseok Turp, M. Dennis |
| author_facet | Oh, Kyuseok Turp, M. Dennis |
| contents | We present a novel approach for classifying star-forming galaxies using photometric images. By utilizing approximately $124,000$ optical color composite images and spectroscopic data of nearby galaxies at $0.01<z<0.06$ from the Sloan Digital Sky Survey, along with follow-up spectroscopic line measurements from the OSSY catalog, and leveraging the Vision Transformer machine-learning technique, we demonstrate that galaxy images in JPEG format alone can be directly used to determine whether star-forming activity dominates the galaxy, bypassing traditional spectroscopic analyses such as emission-line diagnostic diagrams. We anticipate that this method holds significant potential for application in current and future large-scale surveys, such as Euclid, the Dark Energy Survey (DES), and the Legacy Survey of Space and Time (LSST). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_23019 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Capturing star formation activity from compressed photometric images of galaxies Oh, Kyuseok Turp, M. Dennis Astrophysics of Galaxies We present a novel approach for classifying star-forming galaxies using photometric images. By utilizing approximately $124,000$ optical color composite images and spectroscopic data of nearby galaxies at $0.01<z<0.06$ from the Sloan Digital Sky Survey, along with follow-up spectroscopic line measurements from the OSSY catalog, and leveraging the Vision Transformer machine-learning technique, we demonstrate that galaxy images in JPEG format alone can be directly used to determine whether star-forming activity dominates the galaxy, bypassing traditional spectroscopic analyses such as emission-line diagnostic diagrams. We anticipate that this method holds significant potential for application in current and future large-scale surveys, such as Euclid, the Dark Energy Survey (DES), and the Legacy Survey of Space and Time (LSST). |
| title | Capturing star formation activity from compressed photometric images of galaxies |
| topic | Astrophysics of Galaxies |
| url | https://arxiv.org/abs/2507.23019 |