推进用于宏观仿星器流的高分辨率空间和时间测量的技术
Advancing technologies for high-resolution spatial and temporal measurements of macroscopic stellarator flows
AI总结：
本文指出研究宏观流对仿星器平衡与动力学的影响对推进聚变先导工厂物理基础至关重要，呼吁社区以此为契机，结合AI/ML与工作流管理等新技术推动诊断与测量创新。
摘要：
仿星器与托卡马克代表了通过在极高温度下对高度电离气体（即等离子体）进行环向磁约束来实现聚变能的两种主流途径。增进我们对宏观流如何影响仿星器中的平衡与动力学的理解，缩小了重要的知识差距，并且对于推进仿星器作为聚变先导工厂（FPP）概念的物理基础是必要的。这对于美国公共和私营部门的仿星器设计项目尤为关键，在这些项目中，仿星器FPP概念几乎完全基于利用准对称性。借此提交，我们邀请社区考虑：改进对先进仿星器中流的物理理解的需求，如何能够作为诊断与测量创新的催化剂。这包括识别与正在进行的技术开发活动的协同作用，以及利用源自硬件改进和软件（例如AI/ML的应用以及工作流集成与管理）的新兴能力的机会。
英文摘要：
Stellarators, together with tokamaks, represent the two mainstream approaches to realizing fusion energy via toroidal magnetic confinement of highly ionized gases - plasmas - at extremely high temperatures. Improving our understanding of how macroscopic flows impact equilibrium and dynamics in stellarators closes a significant knowledge gap and is necessary to advance the physics basis of stellarators as a fusion pilot plant (FPP) concept. This is especially critical for the US stellarator design program, in both the public and private sectors, where stellarator FPP concepts are based almost exclusively on leveraging quasisymmetries. With this submission we invite the community to consider how the need for improving physics understanding of flows in advanced stellarators can serve as a catalyst for diagnostic and measurement innovation. This includes the identification of synergies with on-going technology development activities as well as opportunities to leverage new and emerging capabilities that may stem from hardware improvements and software, for example, application of AI/ML and workflow integration and management.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
