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Main Authors: Li, Yongjun, Song, Minghao
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2604.16180
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author Li, Yongjun
Song, Minghao
author_facet Li, Yongjun
Song, Minghao
contents We report the experimental implementation of a Data-Driven Chaos Indicator (DDCI) [Y.~Li \emph{et al.}, Nucl.\ Instrum.\ Methods Phys.\ Res.\ A \textbf{1024} (2022) 166060] for online optimization of the National Synchrotron Light Source II (NSLS-II) storage ring. The DDCI quantifies the predictability of electron beam dynamics using turn-by-turn beam position monitor data. A surrogate model of the one-turn map is first trained, and its out-of-sample predictive uncertainty is then employed as a measurable indicator of chaos. By tuning sextupole magnets to mitigate nonlinear effects, a clear enlargement of the dynamic aperture is achieved, accompanied by a corresponding improvement in injection efficiency.
format Preprint
id arxiv_https___arxiv_org_abs_2604_16180
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Online optimization of nonlinear lattice using a data-driven chaos indicator
Li, Yongjun
Song, Minghao
Accelerator Physics
We report the experimental implementation of a Data-Driven Chaos Indicator (DDCI) [Y.~Li \emph{et al.}, Nucl.\ Instrum.\ Methods Phys.\ Res.\ A \textbf{1024} (2022) 166060] for online optimization of the National Synchrotron Light Source II (NSLS-II) storage ring. The DDCI quantifies the predictability of electron beam dynamics using turn-by-turn beam position monitor data. A surrogate model of the one-turn map is first trained, and its out-of-sample predictive uncertainty is then employed as a measurable indicator of chaos. By tuning sextupole magnets to mitigate nonlinear effects, a clear enlargement of the dynamic aperture is achieved, accompanied by a corresponding improvement in injection efficiency.
title Online optimization of nonlinear lattice using a data-driven chaos indicator
topic Accelerator Physics
url https://arxiv.org/abs/2604.16180