论文标题
准蒙特卡洛方法的数字网和序列
Digital Nets and Sequences for Quasi-Monte Carlo Methods
论文作者
论文摘要
准蒙特卡罗方法是提高蒙特卡洛方法效率的一种方式。数字网和序列是准蒙特卡洛方法中使用的低差异点集之一。本文介绍了与数字网和序列有关的三个新结果：实施随机数字网，找到炒数字网的差异的分布，并通过进化计算获得更高的数字网质量。最后，提供了拼命和非撞击数字网的应用。
Quasi-Monte Carlo methods are a way of improving the efficiency of Monte Carlo methods. Digital nets and sequences are one of the low discrepancy point sets used in quasi-Monte Carlo methods. This thesis presents the three new results pertaining to digital nets and sequences: implementing randomized digital nets, finding the distribution of the discrepancy of scrambled digital nets, and obtaining better quality of digital nets through evolutionary computation. Finally, applications of scrambled and non-scrambled digital nets are provided.
