Physics Supernova: AI Agent Matches Elite Gold Medalists at IPhO 2025
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arXiv
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| Autori principali: | , , , , , , , , |
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| Natura: | Preprint |
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2025
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| _version_ | 1866915474488426496 |
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| author | Qiu, Jiahao Shi, Jingzhe Juan, Xinzhe Zhao, Zelin Geng, Jiayi Liu, Shilong Wang, Hongru Wu, Sanfeng Wang, Mengdi |
| author_facet | Qiu, Jiahao Shi, Jingzhe Juan, Xinzhe Zhao, Zelin Geng, Jiayi Liu, Shilong Wang, Hongru Wu, Sanfeng Wang, Mengdi |
| contents | Physics provides fundamental laws that describe and predict the natural world. AI systems aspiring toward more general, real-world intelligence must therefore demonstrate strong physics problem-solving abilities: to formulate and apply physical laws for explaining and predicting physical processes. The International Physics Olympiad (IPhO)--the world's most prestigious physics competition--offers a rigorous benchmark for this purpose. We introduce Physics Supernova, an AI agent system with superior physics problem-solving abilities that match elite IPhO gold medalists. In IPhO 2025 theory problems, Physics Supernova attains 23.5/30 points, ranking 14th of 406 contestants and surpassing the median performance of human gold medalists. We extensively analyzed Physics Supernova's capabilities and flexibility across diverse physics tasks. These results show that principled tool integration within agent systems can deliver competitive improvements in solving challenging science problems. The codes are available at https://github.com/CharlesQ9/Physics-Supernova. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_01659 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Physics Supernova: AI Agent Matches Elite Gold Medalists at IPhO 2025 Qiu, Jiahao Shi, Jingzhe Juan, Xinzhe Zhao, Zelin Geng, Jiayi Liu, Shilong Wang, Hongru Wu, Sanfeng Wang, Mengdi Artificial Intelligence Physics provides fundamental laws that describe and predict the natural world. AI systems aspiring toward more general, real-world intelligence must therefore demonstrate strong physics problem-solving abilities: to formulate and apply physical laws for explaining and predicting physical processes. The International Physics Olympiad (IPhO)--the world's most prestigious physics competition--offers a rigorous benchmark for this purpose. We introduce Physics Supernova, an AI agent system with superior physics problem-solving abilities that match elite IPhO gold medalists. In IPhO 2025 theory problems, Physics Supernova attains 23.5/30 points, ranking 14th of 406 contestants and surpassing the median performance of human gold medalists. We extensively analyzed Physics Supernova's capabilities and flexibility across diverse physics tasks. These results show that principled tool integration within agent systems can deliver competitive improvements in solving challenging science problems. The codes are available at https://github.com/CharlesQ9/Physics-Supernova. |
| title | Physics Supernova: AI Agent Matches Elite Gold Medalists at IPhO 2025 |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2509.01659 |