JACoW logo

Joint Accelerator Conferences Website

The Joint Accelerator Conferences Website (JACoW) is an international collaboration that publishes the proceedings of accelerator conferences held around the world.


https://doi.org/10.18429/JACoW-IPAC2021-MOPAB041
Title Convergence Map with Action-Angle Variables Based on Square Matrix for Nonlinear Lattice Optimization
Authors
  • L.H. Yu, Y. Hidaka, F. Plassard, V.V. Smaluk
    BNL, Upton, New York, USA
  • Y. Hao
    FRIB, East Lansing, Michigan, USA
Abstract We apply square matrix method to obtain in high speed a "convergence map", which is similar but different from frequency map. The convergence map is obtained from solving nonlinear dynamical equation by iteration of perturbation method and study the convergence. The map provides information about the stability border of dynamical aperture. We compare the map with frequency map from tracking. The result indicates the new method may be applied in nonlinear lattice optimization, taking the advantage of the high speed (about 10~50 times faster) to explore x, y and the off-momentum phase space.
Paper download MOPAB041.PDF [0.770 MB / 4 pages]
Export download ※ BibTeX LaTeXText/WordRISEndNote
Conference IPAC2021
Series International Particle Accelerator Conference (12th)
Location Campinas, SP, Brazil
Date 24-28 May 2021
Publisher JACoW Publishing, Geneva, Switzerland
Editorial Board Liu Lin (LNLS, Campinas, Brazil); John M. Byrd (ANL, Lemont, IL, USA); Regis Neuenschwander (LNLS, Campinas, Brazil); Renan Picoreti (LNLS, Campinas, Brazil); Volker R. W. Schaa (GSI, Darmstadt, Germany)
Online ISBN 978-3-95450-214-1
Online ISSN 2673-5490
Received 09 May 2021
Accepted 26 May 2021
Issue Date 18 August 2021
DOI doi:10.18429/JACoW-IPAC2021-MOPAB041
Pages 182-185
Copyright
Creative Commons CC logoPublished by JACoW Publishing under the terms of the Creative Commons Attribution 3.0 International license. Any further distribution of this work must maintain attribution to the author(s), the published article's title, publisher, and DOI.