Online optimization of nonlinear lattice using a data-driven chaos indicator

TL;DR

This paper demonstrates an online optimization method for a storage ring using a data-driven chaos indicator that improves beam stability and injection efficiency.

Contribution

It introduces a novel data-driven chaos indicator (DDCI) for real-time optimization of nonlinear beam dynamics in a synchrotron.

Findings

Enlarged dynamic aperture after tuning sextupoles.

Improved injection efficiency.

Validated the effectiveness of DDCI in a real accelerator.

Abstract

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.