DeepInflation: An AI Agent for Research and Model Discovery of Inflation

DeepInflation: ИИ-агент для исследования инфляции и поиска моделей
Ze-Yu Peng, Hao-Shi Yuan, Qi Lai, Qing-Yu Lan, Zhan-He Wang, Jun-Qian Jiang, Gen Ye, Jun Zhang, Yun-Song Piao
2026-05-08

DeepInflationinflationary cosmologyretrieval-augmented generationsingle-field slow-roll inflationsymbolic regression
Abstract 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 with a symbolic regression engine and a retrieval-augmented generation 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 .
1
DeepInflation discovers simple, viable single-field slow-roll inflationary potentials consistent with ACT DR6 observations or specified spectral-index and tensor-to-scalar-ratio values.
2
DeepInflation is a multi-agent AI framework combining large language models, symbolic regression, and retrieval-augmented generation for inflationary model discovery.
3
DeepInflation is presented as a prototype autonomous scientific-discovery engine enabling both researchers and non-experts to explore the inflationary landscape.
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The agent automatically explores and verifies inflationary potentials while grounding generated results in established theoretical literature.
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The system provides accurate theoretical context for obscure inflationary scenarios through natural-language interaction.

single-field slow-roll inflationary potentials

their discovery, exploration, and observational viability across the inflationary landscape

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2026-05-08
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Ze-Yu Peng
Hao-Shi Yuan
Qi Lai
Qing-Yu Lan
Zhan-He Wang
Jun-Qian Jiang
Gen Ye
Jun Zhang
Yun-Song Piao
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