Analysis of eigenvalues and eigenvectors of polymer particles: random normal modes

K. Fukui , B.G. Sumpter , D.W. Noid , C. Yang , R.E. Tuzun
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引用次数: 5

Abstract

We investigate the density of vibrational states g(ω) for 6000 atom polymer particles involving all 18,000 degrees of freedom. The particles are efficiently generated using a molecular dynamics-based computational algorithm and a molecular mechanics method. The density of states spectrum g(ω) clearly shows two distinguishable frequency regions in the polymer system: high (760<ω<1240cm−1) and low (0<ω<350cm−1) frequency modes. By calculating the level-spacing distributions, we find the distribution of the low eigenfrequency corresponds to that of a Wigner distribution. In contrast, Poisson behavior is found for the high frequency region. The eigenvectors for the two regions are analyzed by using a random walk method and Stewart's perturbation theory, both indicate random character for the eigenvectors of the low frequency modes. The random character of the eigenvectors should have ramifications to most types of spectroscopy since transformations of the transition operator to random normal coordinates will cause a widespread mixing, i.e., no selection rules.

聚合物粒子的特征值和特征向量分析:随机正态模
我们研究了6000个原子聚合物粒子的振动态密度g(ω),涉及所有18000个自由度。使用基于分子动力学的计算算法和分子力学方法有效地生成粒子。态密度谱g(ω)清楚地显示了聚合物体系中两个可区分的频率区域:高频率模式(760<ω<1240cm−1)和低频率模式(0<ω<350cm−1)。通过计算电平间距分布,我们发现低特征频率的分布与维格纳分布相对应。相反,在高频区发现了泊松行为。利用随机游走法和Stewart摄动理论分析了这两个区域的特征向量,两者都表明了低频模态特征向量的随机性。特征向量的随机特性应该对大多数类型的光谱学产生影响,因为转换算子到随机正态坐标的转换将导致广泛的混合,即没有选择规则。
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