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arXiv 1806.06210nlin.CD
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Fermi-Pasta-Ulam模型中的记忆效应

Memory effects in the Fermi-Pasta-Ulam Model

Graziano Amati, Hugues Meyer, Tanja Schilling

摘要:

用数值和解析方法研究了强非线性Fermi-Pasta Ulam模型在热平衡下的中间散射函数。从分子动力学模拟,我们区分两个极限制度,作为系统的行为作为一个理想气体在高温下和作为一个谐波链低激发。在中等温度下,ISF以非平凡的方式弛豫到平衡。然后,我们解析计算任意高阶的ISF的泰勒系数(两体相互作用的特定简单形状允许我们推导出这些的迭代方案)。递推结果与数值计算结果符合得很好。通过估计散射函数的完全级数展开,我们可以在一定的温度范围内重建其粗粒度的动力学。这是由一个记忆依赖的广义朗之万方程(GLE),它可以通过投影算子技术。此外,通过分析ISF的第一系列系数,我们可以提取一个参数相关联的动力学记忆效应的强度。

英文摘要:

We study the Intermediate Scattering Function (ISF) of the strongly-nonlinear Fermi-Pasta Ulam Model at thermal equilibrium, using both numerical and analytical methods. From the molecular dynamics simulations we distinguish two limit regimes, as the system behaves as an ideal gas at high temperature and as a harmonic chain for low excitations. At intermediate temperatures the ISF relaxes to equilibrium in a nontrivial fashion. We then calculate analytically the Taylor coefficients of the ISF to arbitrarily high orders (the specific, simple shape of the two-body interaction allows us to derive an iterative scheme for these.) The results of the recursion are in good agreement with the numerical ones. Via an estimate of the complete series expansion of the scattering function, we can reconstruct within a certain temperature range its coarse-grained dynamics. This is governed by a memory-dependent Generalized Langevin Equation (GLE), which can be derived via projection operator techniques. Moreover, by analyzing the first series coefficients of the ISF, we can extract a parameter associated to the strength of the memory effects in the dynamics.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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