DiscoverPhysics: Benchmarking LLMs for Out-of-the-Box Scientific Thinking
Frontier LLMs now perform strongly across a wide range of physics evaluations, but it is hard to disentangle genuine reasoning from recall of established science. We introduce DiscoverPhysics, an interactive benchmark that asks a LLM agent to discover the laws of motion of a simulated world whose physics deliberately deviates from our own. We construct 22 worlds governed by, among others, screened and fractional-power gravity, multi-species couplings, hidden dark-matter-like particles, non-coordinate-free physics, and time-varying interactions. Each world is generated on demand by an N-body simulator, for which the agent proposes several rounds of experiments, observes raw trajectory data...
| Authors | Matt L. Wiemann, Lindsay M. Smith, Peter Melchior et al. |
|---|---|
| Primary category | stat.ML |
| Published | 25 May 2026 |
| Last updated at source | 31 August 2026 |
Connected in the knowledge graph
- AgentNativeResearchLab/discoverphysics-gpt5.6-sol-araDataset · cited by
- AgentNativeResearchLab/discoverphysics-gpt5.5-araDataset · cited by
- AgentNativeResearchLab/discoverphysics-grok4.5-araDataset · cited by
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- AgentNativeResearchLab/discoverphysics-opus4.8-max-araDataset · cited by
- AgentNativeResearchLab/discoverphysics-glm5.2-araDataset · cited by
Models and datasets referencing this paper
- AgentNativeResearchLab/discoverphysics-kimi-k2.7-araDataset
- AgentNativeResearchLab/discoverphysics-opus4.8-max-araDataset
- AgentNativeResearchLab/discoverphysics-gemini3.1-pro-araDataset
- AgentNativeResearchLab/discoverphysics-fable-araDataset
- AgentNativeResearchLab/discoverphysics-gpt5.5-araDataset
- AgentNativeResearchLab/discoverphysics-glm5.2-araDataset
- AgentNativeResearchLab/discoverphysics-gpt5.6-sol-araDataset
- AgentNativeResearchLab/discoverphysics-grok4.5-araDataset
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