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Title: Online storage ring optimization using dimension-reduction and genetic algorithms

Abstract

Particle storage rings are a rich application domain for online optimization algorithms. The Cornell Electron Storage Ring (CESR) has hundreds of independently powered magnets, making it a high-dimensional test-problem for algorithmic tuning. We investigate algorithms that restrict the search space to a small number of linear combinations of parameters (“knobs”) which contain most of the effect on our chosen objective (the vertical emittance), thus enabling efficient tuning. We report experimental tests at CESR that use dimension-reduction techniques to transform an 81-dimensional space to an 8-dimensional one which may be efficiently minimized using one-dimensional parameter scans. We also report an experimental test of a multiobjective genetic algorithm using these knobs that results in emittance improvements comparable to state-of-the-art algorithms, but with increased control over orbit errors.

Authors:
; ; ; ; ;
Publication Date:
Research Org.:
Cornell Univ., Ithaca, NY (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1511077
Alternate Identifier(s):
OSTI ID: 1612011
Grant/Contract Number:  
SC0013571
Resource Type:
Published Article
Journal Name:
Physical Review Accelerators and Beams
Additional Journal Information:
Journal Name: Physical Review Accelerators and Beams Journal Volume: 22 Journal Issue: 5; Journal ID: ISSN 2469-9888
Publisher:
American Physical Society (APS)
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; Physics

Citation Formats

Bergan, W. F., Bazarov, I. V., Duncan, C. J. R., Liarte, D. B., Rubin, D. L., and Sethna, J. P. Online storage ring optimization using dimension-reduction and genetic algorithms. United States: N. p., 2019. Web. doi:10.1103/PhysRevAccelBeams.22.054601.
Bergan, W. F., Bazarov, I. V., Duncan, C. J. R., Liarte, D. B., Rubin, D. L., & Sethna, J. P. Online storage ring optimization using dimension-reduction and genetic algorithms. United States. doi:10.1103/PhysRevAccelBeams.22.054601.
Bergan, W. F., Bazarov, I. V., Duncan, C. J. R., Liarte, D. B., Rubin, D. L., and Sethna, J. P. Mon . "Online storage ring optimization using dimension-reduction and genetic algorithms". United States. doi:10.1103/PhysRevAccelBeams.22.054601.
@article{osti_1511077,
title = {Online storage ring optimization using dimension-reduction and genetic algorithms},
author = {Bergan, W. F. and Bazarov, I. V. and Duncan, C. J. R. and Liarte, D. B. and Rubin, D. L. and Sethna, J. P.},
abstractNote = {Particle storage rings are a rich application domain for online optimization algorithms. The Cornell Electron Storage Ring (CESR) has hundreds of independently powered magnets, making it a high-dimensional test-problem for algorithmic tuning. We investigate algorithms that restrict the search space to a small number of linear combinations of parameters (“knobs”) which contain most of the effect on our chosen objective (the vertical emittance), thus enabling efficient tuning. We report experimental tests at CESR that use dimension-reduction techniques to transform an 81-dimensional space to an 8-dimensional one which may be efficiently minimized using one-dimensional parameter scans. We also report an experimental test of a multiobjective genetic algorithm using these knobs that results in emittance improvements comparable to state-of-the-art algorithms, but with increased control over orbit errors.},
doi = {10.1103/PhysRevAccelBeams.22.054601},
journal = {Physical Review Accelerators and Beams},
number = 5,
volume = 22,
place = {United States},
year = {2019},
month = {5}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1103/PhysRevAccelBeams.22.054601

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