Researchers combine multi-agent LLMs with latent foundation models to autonomously explore PDE solution spaces for flow physics simulations. The approach uses LFMs as surrogate simulators, enabling agents to efficiently query parameter configurations at negligible cost, addressing limitations of traditional computationally expensive lab and numerical simulation approaches.
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Agentic Exploration of PDE Spaces using Latent Foundation Models for Parameterized Simulations
Multi-agent LLMs use latent foundation models as efficient surrogate simulators to autonomously explore PDE parameter spaces, replacing expensive physics simulations with near-zero-cost AI-driven queries.
Tuesday, April 14, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.AIBY sys://pipeline
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