JACoW is a publisher in Geneva, Switzerland that publishes the proceedings of accelerator conferences held around the world by an international collaboration of editors.
@unpublished{caliari:hb2023-wea1c2,
author = {C. Caliari and O. Boine-Frankenheim and A. Oeftiger},
title = {{Design of a Proof-of-Principle Experiment for the DLMN Method to Identify Magnetic Field Errors}},
% booktitle = {Proc. HB'23},
booktitle = {Proc. ICFA Adv. Beam Dyn. Workshop High-Intensity High-Brightness Hadron Beams (HB'23)},
eventdate = {2023-10-09/2023-10-13},
language = {english},
intype = {presented at the},
series = {ICFA Advanced Beam Dynamics Workshop on High-Intensity and High-Brightness Hadron Beams},
number = {68},
venue = {Geneva, Switzerland},
publisher = {JACoW Publishing, Geneva, Switzerland},
month = {04},
year = {2024},
note = {presented at HB'23 in Geneva, Switzerland, unpublished},
abstract = {{Magnetic field errors limit the beam intensity in synchrotrons as they excite nonsystematic resonances, reduce dynamic aperture, and may result in beam loss due to space charge induced resonance crossing. Methods to establish a field error model from beam-based measurements are therefore a valuable tool for realistic limitation and improvement studies. We report on the implementation of a proof-of-principle experiment in the GSI synchrotron SIS18 to identify both linear and non-linear field errors. The goal is to demonstrate the Deep Lie Map Network (DLMN) technique, a proposed data-driven approach based on (unstructured) turn-by-turn BPM data. Established identification procedures in the literature are based on orbit or tune response matrices, or resonance driving terms. While they sequentially build a field error model for subsequent accelerator sections, the DLMN approach could save valuable beam time by detecting field errors in parallel. We underline the potential of the DLMN method via detailed simulation studies to infer gradient and sextupole errors. The outline of a proof-of-principle experiment is discussed upon first experimental experience.}},
}