Erratum: Genetic algorithm enhanced by machine learning in dynamic aperture optimization [Phys. Rev. Accel. Beams21, 054601 (2018)]

IF 1.5 3区物理与天体物理 Q3 PHYSICS, NUCLEAR

Physical Review Accelerators and Beams Pub Date : 2024-04-02 DOI:10.1103/physrevaccelbeams.27.049901

Yongjun Li, Weixing Cheng, Li Hua Yu, Robert Rainer

引用次数: 0

Abstract

DOI:https://doi.org/10.1103/PhysRevAccelBeams.27.049901

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勘误：动态光圈优化中机器学习增强的遗传算法 [Phys. Rev. Accel. Beams21, 054601 (2018)]

DOI:https://doi.org/10.1103/PhysRevAccelBeams.27.049901

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Physical Review Accelerators and Beams Physics and Astronomy-Surfaces and Interfaces

CiteScore

3.90

自引率

23.50%

发文量

158

审稿时长

23 weeks

期刊介绍： Physical Review Special Topics - Accelerators and Beams (PRST-AB) is a peer-reviewed, purely electronic journal, distributed without charge to readers and funded by sponsors from national and international laboratories and other partners. The articles are published by the American Physical Society under the terms of the Creative Commons Attribution 3.0 License. It covers the full range of accelerator science and technology; subsystem and component technologies; beam dynamics; accelerator applications; and design, operation, and improvement of accelerators used in science and industry. This includes accelerators for high-energy and nuclear physics, synchrotron-radiation production, spallation neutron sources, medical therapy, and intense-beam applications.