计算机科学
步伐
激光器
元数据
数据管理
控制(管理)
自动化
软件
数据科学
数据库
人工智能
万维网
操作系统
工程类
物理
地理
机械工程
光学
大地测量学
作者
Scott Feister,K. Cassou,S. J. D. Dann,A. Döpp,Philippe Gauron,A. J. Gonsalves,Archis Joglekar,Victoria K. Marshall,O. Neveu,Hans-Peter Schlenvoigt,M. J. V. Streeter,C. A. J. Palmer
摘要
Abstract The next generation of high-power lasers enables repetition of experiments at orders of magnitude higher frequency than what was possible using the prior generation. Facilities requiring human intervention between laser repetitions need to adapt in order to keep pace with the new laser technology. A distributed networked control system can enable laboratory-wide automation and feedback control loops. These higher-repetition-rate experiments will create enormous quantities of data. A consistent approach to managing data can increase data accessibility, reduce repetitive data-software development and mitigate poorly organized metadata. An opportunity arises to share knowledge of improvements to control and data infrastructure currently being undertaken. We compare platforms and approaches to state-of-the-art control systems and data management at high-power laser facilities, and we illustrate these topics with case studies from our community.
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