在变形体上使用梯度极点定位坐点,适应性地显示为点云
A Georgiou1, H Vandecasteele2, J M Bello-Rivas3
1Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA.
Chaos (Woodbury, N.Y.)
|December 4, 2023
概括
这项研究引入了一种新的方法,用于在高维动态系统中通过在未知的多元体上使用梯度极点来找到坐点. 该技术有效地将这些关键点定位在复杂的表面上,有助于动态系统分析.
科学领域:
- 动态系统和混沌理论
- 计算化学的计算化学
- 不同几何学微分几何学
背景情况:
- 稳定状态对于理解动态系统至关重要.
- 由于时间尺度的分离,高维系统经常简化为低维的多元体.
- 定位坐点对于分析系统动态和稳定性至关重要.
研究的目的:
- 开发一种有效的方法来定位高维动态系统中的点和其他固定点.
- 为了应对分析在未知,低维多元体上演变的系统的挑战.
- 提供一种技术,使探索沿着相关的系统轨迹产生偏见.
主要方法:
- 在适应性样本的点云上利用梯度极点,定义未知的里曼的多元体.
- 采用多重学习来在飞行中发现局部坐标.
- 需要了解单个最小值和在任意点周围采样能力.
主要成果:
- 在一个球体上映的Müller-Brown潜力上证明了有效性.
- 成功地在未知的表面上定位了位点.
- 与详尽的方法相比,提供了更有效地探索状态空间.
结论:
- 拟议的方法提供了一种有效的方法,用于在复杂的动态系统中找到点.
- 这种技术对于在先验未知的多元体上演变的系统尤其有用.
- 该方法对分析化学反应路径和其他复杂现象有前途.
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