Plasma GraphRAG: Physics-Grounded Parameter Selection for Gyrokinetic Simulations
Accurate parameter selection is fundamental to gyrokinetic plasma simulations, yet current practices rely heavily on manual literature reviews, leading to inefficiencies and inconsistencies. We introduce Plasma GraphRAG, a novel framework that integrates Graph Retrieval-Augmented Generation (GraphRAG) with large language models (LLMs) for automated, physics-grounded parameter range identification. By constructing a domain-specific knowledge graph from curated plasma literature and enabling structured retrieval over graph-anchored entities and relations, Plasma GraphRAG enables LLMs to generate accurate, context-aware recommendations. Extensive evaluations across five metrics, comprehensiv...
| Authors | Ruichen Zhang, Feda AlMuhisen, Chenguang Wan et al. |
|---|---|
| Primary category | physics.plasm-ph |
| Published | 7 April 2026 |
| Last updated at source | 7 April 2026 |
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