Domain Adaptation in Application to Gravitational Lens Finding
The next decade is expected to see a tenfold increase in the number of strong gravitational lenses, driven by new wide-field imaging surveys. To discover these rare objects, efficient automated detection methods need to be developed. In this work, we assess the performance of three domain adaptation...
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| Format: | Article |
| Language: | English |
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IOP Publishing
2025-01-01
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| Series: | The Astrophysical Journal |
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| Online Access: | https://doi.org/10.3847/1538-4357/adee16 |
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| author | Hanna Parul Sergei Gleyzer Pranath Reddy Michael W. Toomey |
| author_facet | Hanna Parul Sergei Gleyzer Pranath Reddy Michael W. Toomey |
| author_sort | Hanna Parul |
| collection | DOAJ |
| description | The next decade is expected to see a tenfold increase in the number of strong gravitational lenses, driven by new wide-field imaging surveys. To discover these rare objects, efficient automated detection methods need to be developed. In this work, we assess the performance of three domain adaptation (DA) techniques—adversarial discriminative DA, Wasserstein distance guided representation learning (WDGRL), and supervised domain adaptation (SDA)—in enhancing lens-finding algorithms trained on simulated data when applied to observations from the Hyper Suprime-Cam Subaru Strategic Program. We find that WDGRL combined with an equivariant-neural-network-based encoder provides the best performance in an unsupervised setting and that SDA is able to enhance the model’s ability to distinguish between lenses and common similar-looking false positives, such as spiral galaxies, which is crucial for future lens surveys. |
| format | Article |
| id | doaj-art-b83b65bfd416471eb4dce5a22762fec1 |
| institution | Kabale University |
| issn | 1538-4357 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | The Astrophysical Journal |
| spelling | doaj-art-b83b65bfd416471eb4dce5a22762fec12025-08-25T05:51:24ZengIOP PublishingThe Astrophysical Journal1538-43572025-01-0199014710.3847/1538-4357/adee16Domain Adaptation in Application to Gravitational Lens FindingHanna Parul0https://orcid.org/0009-0007-3431-4269Sergei Gleyzer1https://orcid.org/0000-0002-6222-8102Pranath Reddy2https://orcid.org/0000-0002-6609-3495Michael W. Toomey3https://orcid.org/0000-0003-1205-4033LIRA, Observatoire de Paris, Université PSL, Sorbonne Université, Université Paris Cité , CY Cergy Paris Université, CNRS, 92190 Meudon, France ; hparul@crimson.ua.edu; Department of Physics & Astronomy, University of Alabama, Tuscaloosa, AL 35401, USADepartment of Physics & Astronomy, University of Alabama, Tuscaloosa, AL 35401, USAUniversity of Florida , Gainesville, FL 32611, USACenter for Theoretical Physics – a Leinweber Institute, Massachusetts Institute of Technology , Cambridge, MA 02139, USAThe next decade is expected to see a tenfold increase in the number of strong gravitational lenses, driven by new wide-field imaging surveys. To discover these rare objects, efficient automated detection methods need to be developed. In this work, we assess the performance of three domain adaptation (DA) techniques—adversarial discriminative DA, Wasserstein distance guided representation learning (WDGRL), and supervised domain adaptation (SDA)—in enhancing lens-finding algorithms trained on simulated data when applied to observations from the Hyper Suprime-Cam Subaru Strategic Program. We find that WDGRL combined with an equivariant-neural-network-based encoder provides the best performance in an unsupervised setting and that SDA is able to enhance the model’s ability to distinguish between lenses and common similar-looking false positives, such as spiral galaxies, which is crucial for future lens surveys.https://doi.org/10.3847/1538-4357/adee16Strong gravitational lensingAstronomy data analysis |
| spellingShingle | Hanna Parul Sergei Gleyzer Pranath Reddy Michael W. Toomey Domain Adaptation in Application to Gravitational Lens Finding The Astrophysical Journal Strong gravitational lensing Astronomy data analysis |
| title | Domain Adaptation in Application to Gravitational Lens Finding |
| title_full | Domain Adaptation in Application to Gravitational Lens Finding |
| title_fullStr | Domain Adaptation in Application to Gravitational Lens Finding |
| title_full_unstemmed | Domain Adaptation in Application to Gravitational Lens Finding |
| title_short | Domain Adaptation in Application to Gravitational Lens Finding |
| title_sort | domain adaptation in application to gravitational lens finding |
| topic | Strong gravitational lensing Astronomy data analysis |
| url | https://doi.org/10.3847/1538-4357/adee16 |
| work_keys_str_mv | AT hannaparul domainadaptationinapplicationtogravitationallensfinding AT sergeigleyzer domainadaptationinapplicationtogravitationallensfinding AT pranathreddy domainadaptationinapplicationtogravitationallensfinding AT michaelwtoomey domainadaptationinapplicationtogravitationallensfinding |