AI自动发现符合观测的宇宙暴胀模型，支持自然语言探索
DeepInflation: an AI agent for research and model discovery of inflation
- 用大语言模型+符号回归+知识库构建多智能体系统
- 成功找到与最新观测数据一致的简单暴胀势能模型
- 适合科研人员和非专家通过对话探索暴胀理论
我们提出DeepInflation，一个用于暴胀宇宙学研究与模型发现的AI代理。基于多智能体架构，该系统融合大型语言模型（LLMs）、符号回归（SR）引擎和检索增强生成（RAG）知识库，能够自动探索并验证海量暴胀势能，同时确保输出基于已有理论文献。我们证明，DeepInflation可成功发现与最新观测（以ACT DR6结果为例）一致的、简单的单场慢滚暴胀势能模型，或任意给定的 $n_s$ 与 $r$ 值，并为冷门暴胀情景提供准确的理论背景。该代理展示了宇宙学中自主科学发现引擎的新范式，使研究人员及非专家均可通过自然语言探索暴胀景观。代码已开源：https://github.com/pengzy-cosmo/DeepInflation。
原文摘要 · Abstract (English)
We present DeepInflation, an AI agent designed for research and model discovery in inflationary cosmology. Built upon a multi-agent architecture, DeepInflation integrates Large Language Models (LLMs) with a symbolic regression (SR) engine and a retrieval-augmented generation (RAG) knowledge base. This framework enables the agent to automatically explore and verify the vast landscape of inflationary potentials while grounding its outputs in established theoretical literature. We demonstrate that DeepInflation can successfully discover simple and viable single-field slow-roll inflationary potentials consistent with the latest observations (with the ACT DR6 results taken as an example) or any given $n_s$ and $r$, and provide accurate theoretical context for obscure inflationary scenarios. DeepInflation serves as a prototype for a new generation of autonomous scientific discovery engines in cosmology, which enables researchers and non-experts alike to explore the inflationary landscape using natural language. This agent is available at https://github.com/pengzy-cosmo/DeepInflation.
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