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URLhttps://doi.org/10.18429/JACoW-IPAC2025-WEPS102
TitleReconstructing wake functions using Haissinski distributions from multiple bunch charges
Authors
  • S. Funkner, A. Mochihashi, A. Mueller, E. Bründermann, F. Donoso, G. Niehues, J. Steinmann, M. Schwarz
    Karlsruhe Institute of Technology
AbstractAccurate knowledge of wake functions is crucial in accelerator physics, serving as the cornerstone for understanding intra-bunch interactions and for controlling or mitigating instabilities that limit accelerator performance. Haissinski distributions, which describe the steady-state longitudinal bunch density, are intrinsically determined by the wake function experienced by the bunch. While these distributions are typically computed from a given wake function, we investigate the inverse problem: extracting the wake function directly from measured Haissinski distributions. In this theoretical work, we introduce a novel method to reconstruct wake functions by utilizing Haissinski distributions obtained at multiple bunch charges. By combining these profiles into an overdetermined system, we address challenges posed by the inverse problem, which is sensitive to noise and discretization errors. Here, our preliminary results suggest that the use of regularization techniques may help achieve more stable reconstructions of the wake function.
Paperdownload: WEPS102.pdf
CiteBibTeX, LaTeX, Text/Word, RIS, EndNote
Conference16th International Particle Accelerator Conference
Series
LocationTaipei, Taiwan
Date01-06 Jun 2025
PublisherJACoW Publishing, Geneva, Switzerland
Editorial Board* Ming-Chyuan Lin - National Synchrotron Radiation Research Center * Yoichi Sato - KEK * Jui-Che Huang - National Synchrotron Radiation Research Center * David Button - Australian Nuclear Science and Technology Organisation * Ping-Shun Chuang - National Synchrotron Radiation Research Center
Online ISBN978-3-95450-248-6
Online ISSN2673-5490
Received28 May 2025
Revised03 June 2025
Accepted04 June 2025
Issued05 November 2025
DOI10.18429/JACoW-IPAC2025-WEPS102
Pages2419-2422