发表机构
ELI ALPS, The Extreme Light Infrastructure ERIC; Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County; ELI Beamlines Facility, The Extreme Light Infrastructure ERIC（极端光基础设施 ELI ALPS; 马里兰大学巴尔的摩分校计算机科学和电气工程系; 极端光基础设施 ELI Beamlines 设施）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究探讨机器学习作为下一代超快科学装置使能层的机遇与挑战，提出含多环节的装置级数字架构，结合ELI三大设施案例，论证其可支持实时诊断等多种工作流程。
AI 中文摘要
超快科学正从一系列专用激光实验快速发展为大科学装置级的数据密集型研究事业。高重复频率飞秒与阿秒光源、同步多维诊断技术以及日益非线性的激光-物质相互作用，如今产生的异构数据流，其规模、速度与复杂性常超出传统人工工作流程的处理能力。本章探讨机器学习如何成为下一代超快科学装置的使能层，重点关注极端光设施（ELI）生态系统。我们讨论人工智能辅助实验的科学驱动因素，提出涵盖采集、摄入、存储、分析、机器学习、自适应反馈及用户界面的大科学装置级数字架构，并回顾ELI ALPS、ELI Beamlines与ELI-NP的代表性案例。核心论点是，机器学习不应仅被视为离线数据分析工具；相反，当受物理认知约束并嵌入可靠数据基础设施时，它可支持实时诊断、代理建模、异常检测、实验优化及逐步自主发现工作流程。
英文摘要
Ultrafast science is rapidly evolving from a collection of specialized laser experiments into a facility-scale, data-intensive research endeavour. High-repetition-rate femtosecond and attosecond sources, synchronized multidimensional diagnostics, and increasingly nonlinear laser-matter interactions now generate heterogeneous data streams whose volume, speed, and complexity often exceed the capacity of conventional manual workflows. This chapter examines how machine learning can become an enabling layer for next-generation ultrafast facilities, with emphasis on the Extreme Light Infrastructure (ELI) ecosystem. We discuss the scientific drivers for artificial-intelligence-assisted experimentation, propose a facility-scale digital architecture spanning acquisition, ingestion, storage, analytics, machine learning, adaptive feedback, and user interfaces, and review representative examples from ELI ALPS, ELI Beamlines, and ELI-NP. The central thesis is that machine learning should not be treated merely as an offline data-analysis tool; rather, when constrained by physical insight and embedded in robust data infrastructure, it can support real-time diagnostics, surrogate modeling, anomaly detection, experimental optimization, and progressively autonomous discovery workflows.
Comments25 pages, 3 figures, 2 tables
