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English(EN) Variational Continuation for Double Pendulum Periodic Orbits

新方法利用机器学习寻找动力学系统中的周期轨道

研究人员开发了一种新的基于Hessian的方法,用于数值延拓动力学系统中的周期轨道,利用傅里叶级数参数化轨道,并使用自动微分实现雅可比矩阵的自动化。这种无需积分器的方法可以有效地识别轨道族的分岔和交点。该方法通过成功延拓双摆的周期振荡得到了验证,揭示了之前未被记录的、两个质量块永不同时静止的周期轨道。 AI

影响 这项研究展示了机器学习技术(特别是自动微分)在推进复杂动力学系统研究方面的新颖应用。

排序理由 该集群包含一篇详细介绍新计算方法的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.LG 阅读 →

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新方法利用机器学习寻找动力学系统中的周期轨道

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该集群包含一篇详细介绍新计算方法的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Leo Yao, Ziming Liu, Max Tegmark ·

    变分延拓法用于双摆周期轨道

    arXiv:2609.05337v1 Announce Type: new Abstract: We present a Hessian-based approach to numerically continue periodic orbits in dynamical systems. A loop (periodic orbit candidate) is parametrized as a Fourier series; a loss function is defined based on the deviation of the loop f…