Physics Supernova: AI Agent Matches Elite Gold Medalists at IPhO 2025

• URL: http://arxiv.org/abs/2509.01659v1
• Date: Mon, 01 Sep 2025 17:59:13 GMT
• Title: Physics Supernova: AI Agent Matches Elite Gold Medalists at IPhO 2025
• Authors: Jiahao Qiu, Jingzhe Shi, Xinzhe Juan, Zelin Zhao, Jiayi Geng, Shilong Liu, Hongru Wang, Sanfeng Wu, Mengdi Wang,
• Abstract summary: We introduce Physics Supernova, an AI system with superior physics problem-solving abilities.<n>Supernova attains 23.5/30 points, ranking 14th of 406 contestants and surpassing the median performance of human gold medalists.<n>These results show that principled tool integration within agent systems can deliver competitive improvements.
• Score: 55.8464246603186
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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