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

Jiahao Qiu, Jingzhe Shi, Xinzhe Juan, Zelin Zhao, Jiayi Geng, Shilong Liu, Hongru WANG, Sanfeng Wu, Mengdi Wang

Keywords: Agent, Physics, International Physics Olympiad

TL;DR: We propose Physics Supernova, an AI agent system provided with specialized tools to achieve superior physics problem-solving abilities, and attain elite gold medalist level performance on International Physics Olympiad 2025 theory problems.

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.

Submission Number: 43