Meir H Shachar, M Giselle Fernández-Godino, Charles F Jekel, Harshitha Menon, Dane M Sterbentz, Yue Hao, Kevin A Korner, Robert N Rieben, Daniel A White, Jonathan L Belof, William J Schill, Ismael D Boureima, Nathan K Brown
{"title":"Multiagent design assistant for the simulation of inertial fusion energy.","authors":"Meir H Shachar, M Giselle Fernández-Godino, Charles F Jekel, Harshitha Menon, Dane M Sterbentz, Yue Hao, Kevin A Korner, Robert N Rieben, Daniel A White, Jonathan L Belof, William J Schill, Ismael D Boureima, Nathan K Brown","doi":"10.1103/c6jc-fnkm","DOIUrl":null,"url":null,"abstract":"<p><p>Inertial fusion energy promises nearly unlimited, clean power, if it can be achieved. However, the design and engineering of fusion systems requires controlling and manipulating matter at extreme energies and timescales; the shock physics and radiation transport governing the physical behavior under these conditions are complex, requiring the development, calibration, and use of predictive multiphysics codes to navigate the highly nonlinear and multifaceted design landscape. We hypothesize that artificial intelligence reasoning models can be combined with physics codes and emulators to autonomously design fusion fuel capsules. In this article we construct a multiagent system where natural language is utilized to explore the complex physics regimes around fusion energy. The agentic system is capable of executing a high-order multiphysics inertial fusion computational code. We demonstrate the capacity of the multiagent design assistant to translate natural-language design goals into simulation execution, physics-emulator construction, analysis, and iterative refinement of capsule-geometry parameters, ultimately achieving simulated ignition within the computational design workflow.</p>","PeriodicalId":48698,"journal":{"name":"Physical Review E","volume":"114 2-2","pages":"025303"},"PeriodicalIF":2.5000,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physical Review E","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1103/c6jc-fnkm","RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PHYSICS, FLUIDS & PLASMAS","Score":null,"Total":0}
引用次数: 0
Abstract
Inertial fusion energy promises nearly unlimited, clean power, if it can be achieved. However, the design and engineering of fusion systems requires controlling and manipulating matter at extreme energies and timescales; the shock physics and radiation transport governing the physical behavior under these conditions are complex, requiring the development, calibration, and use of predictive multiphysics codes to navigate the highly nonlinear and multifaceted design landscape. We hypothesize that artificial intelligence reasoning models can be combined with physics codes and emulators to autonomously design fusion fuel capsules. In this article we construct a multiagent system where natural language is utilized to explore the complex physics regimes around fusion energy. The agentic system is capable of executing a high-order multiphysics inertial fusion computational code. We demonstrate the capacity of the multiagent design assistant to translate natural-language design goals into simulation execution, physics-emulator construction, analysis, and iterative refinement of capsule-geometry parameters, ultimately achieving simulated ignition within the computational design workflow.
期刊介绍:
Physical Review E (PRE), broad and interdisciplinary in scope, focuses on collective phenomena of many-body systems, with statistical physics and nonlinear dynamics as the central themes of the journal. Physical Review E publishes recent developments in biological and soft matter physics including granular materials, colloids, complex fluids, liquid crystals, and polymers. The journal covers fluid dynamics and plasma physics and includes sections on computational and interdisciplinary physics, for example, complex networks.