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. https://doi.org/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. https://doi.org/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 = {Mon May 06 00:00:00 EDT 2019},
month = {Mon May 06 00:00:00 EDT 2019}
}
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https://doi.org/10.1103/PhysRevAccelBeams.22.054601
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