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Topics in the numerical analysis of ordinary differential equations: Molecular dynamics and chemical kinetics.

机译:常微分方程数值分析的主题:分子动力学和化学动力学。

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摘要

This thesis consists of four independent chapters. The first three chapters develop and investigate some simple test problems for molecular dynamics simulations. Each of the chapters examines a deterministic system that approximates a stochastic process in some limit. The motivation is to provide systems which can be used to evaluate the ability of numerical methods to correctly compute statistical properties of systems. The last chapter presents an algorithm for the integration of the equations of chemical kinetics.; The first chapter considers two Hamiltonian systems of small numbers of particles interacting on compact domains. The ability of different numerical integrators to reproduce the statistical features of the system is investigated. It is observed that symplectic methods reproduce statistics quite well, whereas step-and-project methods produce erroneous statistical information. An analysis based on Markov chain models is presented.; The second chapter considers a deterministic system of many particles interacting on a finite interval. It is shown that a tracer particle in this system has a trajectory that converges to a stationary Gaussian process. Numerical experiments are performed on a modification of this system using the Symplectic Euler method. The method is observed to reproduce the same stochastic limit.; In the third chapter, it is shown how stationary Gaussian processes, particularly the Ornstein-Uhlenbeck process, can be approximated by deterministic systems with random data. Such processes are obtained as the limit of a sequence of uncoupled oscillator systems. Weak convergence is proven on C[0, T] and the convergence of a wide variety of long-term averages is also shown to hold.; In the last chapter, an adaptive algorithm for the model reduction of chemical systems is presented. The algorithm works in tandem with a numerical integrator to reduce the complexity of the system as the kinetic equations are being solved. It allows some systems to be integrated more quickly than with straightforward integration.
机译:本文由四个独立的章节组成。前三章为分子动力学模拟开发并研究了一些简单的测试问题。每章均探讨了确定性系统,该系统在一定程度上近似了随机过程。动机是提供可用于评估数值方法正确计算系统统计特性的能力的系统。最后一章提出了一种化学动力学方程积分的算法。第一章考虑了两个哈密顿体系,它们具有在紧凑域上相互作用的少量粒子。研究了不同数值积分器重现系统统计特征的能力。可以看出,辛方法很好地再现了统计信息,而分步计划方法则产生了错误的统计信息。提出了基于马尔可夫链模型的分析。第二章考虑了在有限间隔内相互作用的许多粒子的确定性系统。结果表明,该系统中的示踪粒子的轨迹收敛到平稳的高斯过程。使用辛欧拉方法对该系统的修改进行了数值实验。观察到该方法再现了相同的随机极限。在第三章中,显示了如何通过具有随机数据的确定性系统来近似平稳的高斯过程,尤其是Ornstein-Uhlenbeck过程。这样的过程被获得为解耦振荡器系统序列的极限。在 C [0, T ]上证明了弱收敛,并且各种长期平均值的收敛也被证明是有效的。在最后一章中,提出了一种用于化学系统模型简化的自适应算法。该算法与数值积分器协同工作,以解决动力学方程时降低系统的复杂性。与直接集成相比,它可以更快地集成某些系统。

著录项

  • 作者

    Tupper, Paul Frederick.;

  • 作者单位

    Stanford University.;

  • 授予单位 Stanford University.;
  • 学科 Mathematics.
  • 学位 Ph.D.
  • 年度 2002
  • 页码 122 p.
  • 总页数 122
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 数学;
  • 关键词

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