- Physical Review Journals
All JournalsPhysics Magazine

Physical Review Accelerators and Beams

Reuse & Permissions

It is not necessary to obtain permission to reuse this article or its components as it is available under the terms of the Creative Commons Attribution 4.0 International license. This license permits unrestricted use, distribution, and reproduction in any medium, provided attribution to the author(s) and the published article's title, journal citation, and DOI are maintained. Please note that some figures may have been included with permission from other third parties. It is your responsibility to obtain the proper permission from the rights holder directly for these figures.

Export citation

Export citation

Choose format for download:

Download Citation
  • Open Access

Application of deep learning methods for online beam optics and coupling feedback in synchrotron light sources

Liyuan Tan, Shouzhi Xuan, Yihao Gong, Xinzhong Liu, and Xu Wu

Shunqiang Tian* and Wenzhi Zhang

  • *Contact author: tiansq@sari.ac.cn
PDF

Phys. Rev. Accel. Beams 28, 084601 – Published 25 August, 2025

DOI: https://doi.org/10.1103/l1gf-558m

Abstract

This paper presents a beam optics and coupling feedback system for storage rings during operation, integrating deep learning methods with turn-by-turn (TBT) beam position monitor data. A deep learning network has been applied to extract phase advance and betatron coupling information implicit in TBT data. Subsequently, these data were fed into a multilayer neural network for rapid modeling and correction. The simulation data and sampled spectrum data from the Shanghai Synchrotron Radiation Facility (SSRF) were used to create training datasets for the network. The efficacy of this feedback system has been successfully demonstrated at the SSRF, enabling continuous monitoring and correction during each injection cycle. This method reduces optical distortion to less than 1% after correction, effectively suppresses optical and coupling distortion caused by insertion device movements during storage ring operation, and ensures robust performance under various operational conditions.

View figure in article

Physics Subject Headings (PhySH)

Article Text

References (27)

  1. X. Liu, S. Tian, X. Wu, M. Wang, Z. Zhao, and B. Feng, Feedforward compensation of the insertion devices effects in the SSRF storage ring, Nucl. Sci. Tech. 33, 70 (2022).
  2. C. Du, J. Wang, D. Ji, and S. Tian, Studies of round beam at HEPS storage ring by driving linear difference coupling resonance, Nucl. Instrum. Methods Phys. Res., Sect. A 976, 164264 (2020).
  3. Y. Gong, S. Tian, X. Liu, S. X. L. Tan, and L. Mao, Highly coupled off-resonance lattice design in diffraction-limited light sources, Nucl. Sci. Tech. 35, 163 (2024).
  4. X. Wu, S. Tian, Q. Zhang, and W. Zhang, Operation stability improvement for synchrotron light sources by tune feedback system, High Power Laser Part. Beams 32, 045107 (2020).
  5. J. Safranek, Experimental determination of storage ring optics using orbit response measurements, Nucl. Instrum. Methods Phys. Res., Sect. A 388, 27 (1997).
  6. X. Huang, Linear optics and coupling correction with closed orbit modulation, Phys. Rev. Accel. Beams 24, 072805 (2021).
  7. X. Huang and X. Yang, Correction of storage ring optics with an improved closed-orbit modulation method, Phys. Rev. Accel. Beams 26, 052802 (2023).
  8. C.-X. Wang, V. Sajaev, and C.-Y. Yao, Phase advance and β function measurements using model-independent analysis, Phys. Rev. ST Accel. Beams 6, 104001 (2003).
  9. X. Huang, S. Y. Lee, E. Prebys, and R. Tomlin, Application of independent component analysis to Fermilab booster, Phys. Rev. ST Accel. Beams 8, 064001 (2005).
  10. X. Yang and X. Huang, A method for simultaneous linear optics and coupling correction for storage rings with turn-by-turn beam position monitor data, Nucl. Instrum. Methods Phys. Res., Sect. A 828, 97 (2016).
  11. A. Langner, G. Benedetti, M. Carlà, U. Iriso, Z. Martí, J. C. de Portugal, and R. Tomás, Utilizing the N beam position monitor method for turn-by-turn optics measurements, Phys. Rev. Accel. Beams 19, 092803 (2016).
  12. A. Wegscheider, A. Langner, R. Tomás, and A. Franchi, Analytical N beam position monitor method, Phys. Rev. Accel. Beams 20, 111002 (2017).
  13. F. V. der Veken, M. Giovannozzi, E. Maclean, C. Montanari, and G. Valentino, Using machine learning to improve dynamic aperture estimates, in Proceedings of the IPAC-21, International Particle Accelerator Conference No. 12 (JACoW, Geneva, Switzerland, 2021), pp. 134–137, 10.18429/JACoW-IPAC2021-MOPAB028.
  14. A. Edelen, N. Neveu, M. Frey, Y. Huber, C. Mayes, and A. Adelmann, Machine learning for orders of magnitude speedup in multiobjective optimization of particle accelerator systems, Phys. Rev. Accel. Beams 23, 044601 (2020).
  15. A. Ivanov and I. Agapov, Physics-based deep neural networks for beam dynamics in charged particle accelerators, Phys. Rev. Accel. Beams 23, 074601 (2020).
  16. S. C. Leemann, S. Liu, A. Hexemer, M. A. Marcus, C. N. Melton, H. Nishimura, and C. Sun, Demonstration of machine learning-based model-independent stabilization of source properties in synchrotron light sources, Phys. Rev. Lett. 123, 194801 (2019).
  17. V. Kain, S. Hirlander, B. Goddard, F. M. Velotti, G. Z. Della Porta, N. Bruchon, and G. Valentino, Sample-efficient reinforcement learning for CERN accelerator control, Phys. Rev. Accel. Beams 23, 124801 (2020).
  18. R. Roussel, A. Edelen, C. Mayes, D. Ratner, J. P. Gonzalez-Aguilera, S. Kim, E. Wisniewski, and J. Power, Phase space reconstruction from accelerator beam measurements using neural networks and differentiable simulations, Phys. Rev. Lett. 130, 145001 (2023).
  19. E. Fol, R. Tomás, J. Coello de Portugal, and G. Franchetti, Detection of faulty beam position monitors using unsupervised learning, Phys. Rev. Accel. Beams 23, 102805 (2020).
  20. E. Fol, F. Carlier, J. C. de Portugal, A. Garcia-Tabares, and R. Tomás, Machine learning methods for optics measurements and corrections at LHC, in Proceedings of the 9th International Particle Accelerator Conference (IPAC-18), Vancouver, BC, Canada, 2018, International Particle Accelerator Conference No. 9 (JACoW, Geneva, Switzerland, 2018), pp. 1967–1970, 10.18429/JACoW-IPAC2018-WEPAF062.
  21. X. Xu, Y. Zhou, and Y. Leng, Machine learning based image processing technology application in bunch longitudinal phase information extraction, Phys. Rev. Accel. Beams 23, 032805 (2020).
  22. I. C. Hsu, The decoherence and recoherence of the betatron oscillation signal and an application, Part. Accel. 34, 43 (1990), https://cds.cern.ch/record/1108236/files/p43.pdf?version=1.
  23. I. M. Borchardt, E. Karantzoulis, H. Mais, and G. Ripken, Calculation of beam envelopes in storage rings and transport systems in the presence of transverse space charge effects and coupling, Z. Phys. C 39, 339 (1988).
  24. M. Vanwelde, C. Hernalsteens, S. Bogacz, S. Machida, and N. Pauly, Review of coupled betatron motion parametrizations and applications to strongly coupled lattices (2022), https://api.semanticscholar.org/CorpusID:253080515.
  25. M. Borland, elegant: A flexible SDDS-compliant code for accelerator simulation, Argonne Nat. Lab., Argonne, IL, Report No. LS-287, 2000, https://cds.cern.ch/record/511027.
  26. X. Wu, S. Tian, X. Liu, W. Zhang, and Z. Zhao, Design and commissioning of the new SSRF storage ring lattice with asymmetric optics, Nucl. Instrum. Methods Phys. Res., Sect. A 1025, 166098 (2022).
  27. L. Zhan, L. Zhao, J. Liu, S. Liu, and Q. An, Design and testing of a bunch-by-bunch beam position transverse feedback processor, Nucl. Instrum. Methods Phys. Res., Sect. A 902, 62 (2018).

Outline

Information

Phys. Rev. Accel. Beams 28, 084601– Published 25 August, 2025
  • Received 22 November 2024
  • Accepted 16 July 2025
Crossmark - Check for updates button
Creative Commons Logo

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.

Published by the American Physical Society

Sign In to Your Journals Account

Filter

Filter

Article Lookup

Enter a citation