Using a Neural Network Control Policy for Rapid Switching Between Beam Parameters in an FEL

A.L. Edelen, S.G. Biedron, J.P. Edelen, S.V. Milton, P.J.M. van der Slot

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Abstract

FEL user facilities often must accommodate requests for a variety of beam parameters. This usually requires skilled operators to tune the machine, reducing the amount of available time for users. In principle, a neural network control policy that is trained on a broad range of operating states could be used to quickly switch between these requests without substantial need for human intervention.
We present preliminary results from an ongoing study in which a neural network control policy is investigated for rapid switching between beam parameters in a
compact THz FEL.
Original languageEnglish
Title of host publicationProceedings of the 38th International Free Electron Laser Conference (FEL 2017)
Place of PublicationSanta Fe, New Mexico
Pages406-409
DOIs
Publication statusPublished - 20 Aug 2017
Event38th International Free Electron Laser Conference, FEL 2017 - Santa Fe Community Convention Center (SFCCC), Santa Fe, United States
Duration: 20 Aug 201725 Aug 2017
Conference number: 38
http://www.lanl.gov/conferences/free-electron-laser/

Conference

Conference38th International Free Electron Laser Conference, FEL 2017
Abbreviated titleFEL
CountryUnited States
CitySanta Fe
Period20/08/1725/08/17
Internet address

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Free electron lasers
Neural networks
Switches

Cite this

Edelen, A. L., Biedron, S. G., Edelen, J. P., Milton, S. V., & van der Slot, P. J. M. (2017). Using a Neural Network Control Policy for Rapid Switching Between Beam Parameters in an FEL. In Proceedings of the 38th International Free Electron Laser Conference (FEL 2017) (pp. 406-409). [WEP031] Santa Fe, New Mexico. https://doi.org/10.18429/JACoW-FEL2017-WEP031
Edelen, A.L. ; Biedron, S.G. ; Edelen, J.P. ; Milton, S.V. ; van der Slot, P.J.M. / Using a Neural Network Control Policy for Rapid Switching Between Beam Parameters in an FEL. Proceedings of the 38th International Free Electron Laser Conference (FEL 2017). Santa Fe, New Mexico, 2017. pp. 406-409
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abstract = "FEL user facilities often must accommodate requests for a variety of beam parameters. This usually requires skilled operators to tune the machine, reducing the amount of available time for users. In principle, a neural network control policy that is trained on a broad range of operating states could be used to quickly switch between these requests without substantial need for human intervention.We present preliminary results from an ongoing study in which a neural network control policy is investigated for rapid switching between beam parameters in acompact THz FEL.",
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Edelen, AL, Biedron, SG, Edelen, JP, Milton, SV & van der Slot, PJM 2017, Using a Neural Network Control Policy for Rapid Switching Between Beam Parameters in an FEL. in Proceedings of the 38th International Free Electron Laser Conference (FEL 2017)., WEP031, Santa Fe, New Mexico, pp. 406-409, 38th International Free Electron Laser Conference, FEL 2017, Santa Fe, United States, 20/08/17. https://doi.org/10.18429/JACoW-FEL2017-WEP031

Using a Neural Network Control Policy for Rapid Switching Between Beam Parameters in an FEL. / Edelen, A.L.; Biedron, S.G.; Edelen, J.P.; Milton, S.V.; van der Slot, P.J.M.

Proceedings of the 38th International Free Electron Laser Conference (FEL 2017). Santa Fe, New Mexico, 2017. p. 406-409 WEP031.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Edelen AL, Biedron SG, Edelen JP, Milton SV, van der Slot PJM. Using a Neural Network Control Policy for Rapid Switching Between Beam Parameters in an FEL. In Proceedings of the 38th International Free Electron Laser Conference (FEL 2017). Santa Fe, New Mexico. 2017. p. 406-409. WEP031 https://doi.org/10.18429/JACoW-FEL2017-WEP031