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Application of Quantum Monte Carlo Methods to Molecular Potential Energy Surfaces

机译:量子蒙特卡罗方法在分子势能面中的应用

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摘要

Various computational methods have been used to generate potential energy surfaces, which can help us simulate and interpret how atoms or molecules behave during a chemical reaction. For accurate work, ab initio wavefunction methods have traditionally been used, which have some disadvantages. For example, highly accurate methods scale poorly with system size ( n7 or higher) and are mostly not well parallelized for calculations with multiple processors. One alternative method that has more favorable scaling with system size and is well parallelized is a computational technique called quantum Monte Carlo (QMC). QMC methods scale with the number of electrons as n3 and have been found to scale almost linearly with the number of processors, even beyond 500,000 cores. However, despite the favorable scaling towards large systems, the cost of QMC methods is relatively expensive for small systems. Small systems nevertheless make important benchmarks necessary for the new methods to gain acceptance. Thus, it was determined to study QMC methods in a few benchmark systems in order to assess its accuracy and routine applicability.;It was found that QMC methods can be very accurate comparing well with experimental measurements and other high-level ab initio methods. Benchmark calculations with QMC produced realistic spectroscopic parameters for CO and N2. However, for small system sizes, they are relatively very expensive to perform with the cost being orders of magnitude higher than traditional methods. Consequently, their use in small systems will likely most often be restricted to only a few geometrical points of interest, unlike traditional methods. Nevertheless, deep insight into the electronic structure of a system can be obtained.
机译:已经使用了各种计算方法来生成势能面,这可以帮助我们模拟和解释原子或分子在化学反应过程中的行为。为了精确地工作,传统上使用从头算起波函数方法,这具有一些缺点。例如,高度精确的方法无法随着系统大小(n7或更高)进行扩展,并且对于使用多个处理器进行的计算而言,并行性通常不佳。具有更好的系统规模缩放比例并且很好地并行化的一种替代方法是称为量子蒙特卡洛(QMC)的计算技术。 QMC方法按电子数量n3进行缩放,并且已发现其与处理器数量几乎成线性比例,甚至超过500,000个核。然而,尽管有利地扩展到大型系统,但是对于小型系统,QMC方法的成本相对昂贵。尽管如此,小型系统还是为新方法获得认可所必需的重要基准。因此,决定在一些基准系统中研究QMC方法,以评估其准确性和常规适用性。发现QMC方法与实验测量值和其他高级从头算方法相比,可以非常准确。使用QMC进行基准计算得出了CO和N2的实际光谱参数。但是,对于较小的系统大小,它们的执行成本相对较高,且成本要比传统方法高几个数量级。因此,与传统方法不同,它们在小型系统中的使用很可能经常会被限制为仅关注几个几何点。然而,可以获得对系统的电子结构的深入了解。

著录项

  • 作者

    Powell, Andrew Douglas.;

  • 作者单位

    Missouri University of Science and Technology.;

  • 授予单位 Missouri University of Science and Technology.;
  • 学科 Chemistry.
  • 学位 Ph.D.
  • 年度 2017
  • 页码 104 p.
  • 总页数 104
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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