El Agente Potente: High-Throughput Agentic Atomistic Simulations
Foundational machine-learning interatomic potentials (MLIPs) are transforming atomistic simulations by achieving near-ab initio accuracy across large chemical spaces at a fraction of the computational cost. A central challenge in using these tools for high-throughput property calculations is translating high-level scientific intent into adaptive simulation campaigns without compromising workflow rigour. We introduce El Agente Potente, an agentic system that combines typed execution graphs with a complementary coding mode for MLIPs-driven atomistic simulations. Typed execution graphs provide structured and provenance-aware execution for standardized workflows, with large language models (L...
| Authors | Tsz Wai Ko, Jiaru Bai, Thomas Swanick et al. |
|---|---|
| Primary category | cs.AI |
| Published | 13 September 2026 |
| Last updated at source | 13 September 2026 |
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