Original manuscripts are sought to the special issue on "Future Control Systems and Machine Learning at High Power Laser Facilities" of High Power Laser Science and Engineering (HPL).
The scope of this special issue is to highlight the cutting-edge engineering, computational and experimental developments supporting the next generation of high power laser facilities and enabling a paradigm shift in the design and analysis of high power laser experiments. The topics invited for inclusion are, but not limited to:
Andreas Döpp, MPQ, Germany
Matthew Streeter, Queen's University Belfast, U. K.
Scott Feister, California State University Channel Islands, USA
Hyung Taek Kim, Advanced Photonics Research Institute (APRI), GIST, Korea
Co-ordinating Editor: Charlotte Palmer, Topical Editor, High Power Laser Science and Engineering
Submission deadline: 31 August 2022
Manuscripts should be submitted via the online submission system at: http://mc03.manuscriptcentral.com/clp-hpl. Please select "Special Issue on Future Control Systems and Machine Learning at High Power Laser Facilities" from the drop-down menu under "Manuscript Type" when submitting manuscript.
HPL is an open access journal co-published by Chinese Laser Press and Cambridge University Press. It seeks to uncover the underlying science and engineering in the fields of high energy density physics, high power lasers, advanced laser technology and applications, and laser components. Articles in HPL are freely available to all readers worldwide via journals.cambridge.org/hpl&researching.cn/hpl.