论文标题
KDSOURCE，一种使用内核密度估计来生成蒙特卡洛粒子源的工具
KDSource, a tool for the generation of Monte Carlo particle sources using kernel density estimation
论文作者
论文摘要
蒙特卡洛辐射传输模拟显然有助于改善核系统的设计。当执行横梁内或屏蔽模拟时，由于必须将粒子跟踪到远离原始源或屏蔽后面的区域，因此出现了复杂性，通常缺乏足够的统计数据。已经报告了克服此问题（例如使用粒子列表或生成合成源）的不同可能性。在这项工作中，我们通过使用自适应多元内核密度估计器（KDE）方法提出了一种新方法。这个概念是在KDSource中实现的，Kdsource是一种通用工具，用于建模，优化和采样KDE来源，可提供方便的用户界面。该方法的基本特性是在已知密度分布的分析问题中研究的。此外，该工具还用于对中子束建模的两个蒙特卡洛模拟中，这与实验结果显示了很好的一致性。
Monte Carlo radiation transport simulations have clearly contributed to improve the design of nuclear systems. When performing in-beam or shielding simulations a complexity arises due to the fact that particles must be tracked to regions far from the original source or behind the shielding, often lacking sufficient statistics. Different possibilities to overcome this problem such as using particle lists or generating synthetic sources have already been reported. In this work we present a new approach by using the adaptive multivariate kernel density estimator (KDE) method. This concept was implemented in KDSource, a general tool for modelling, optimizing and sampling KDE sources, which provides a convenient user interface. The basic properties of the method were studied in an analytical problem with a known density distribution. Furthermore, the tool was used in two Monte Carlo simulations that modelled neutron beams, which showed good agreement with experimental results.
