MCViNE --一个面向对象的蒙特卡罗中子射线追迹模拟软件包
MCViNE -- An object oriented Monte Carlo neutron ray tracing simulation package
摘要：
MCViNE（Monte-Carlo VIrtual Neutron Experiment）是一个多功能的蒙特卡罗（MC）中子射线追踪程序，为研究人员提供了用于执行反映真实中子散射实验的计算机建模和模拟的工具。通过采用现代软件工程实践，例如使用复合和访问者设计模式来表示和访问中子散射体，并使用递归算法进行多次散射，MCViNE足够灵活，可以处理复杂的中子散射问题，包括例如复杂检测器系统的中子检测，以及各种样品和样品环境中的单次和多次散射事件。此外，MCViNE可以利用广泛用于仪器设计和优化的基于线性链的MC射线跟踪包中的仿真组件，以及基于NumPy的组件，使原型变得有用且易于开发。这些发展使我们能够进行详细的模拟的中子散射实验与非平凡的样品在飞行时间非弹性仪器在Sputterus中子源。粉末和单晶样品与各种散射内核，包括内核的声子和磁振子散射，这样的模拟的例子。通过精确再现实验结果的模拟，可以打开和关闭散射机制，以确定它们如何对测量的散射强度做出贡献，从而提高我们对基础物理的理解。
英文摘要：
MCViNE (Monte-Carlo VIrtual Neutron Experiment) is a versatile Monte Carlo (MC) neutron ray-tracing program that provides researchers with tools for performing computer modeling and simulations that mirror real neutron scattering experiments. By adopting modern software engineering practices such as using composite and visitor design patterns for representing and accessing neutron scatterers, and using recursive algorithms for multiple scattering, MCViNE is flexible enough to handle sophisticated neutron scattering problems including, for example, neutron detection by complex detector systems, and single and multiple scattering events in a variety of samples and sample environments. In addition, MCViNE can take advantage of simulation components in linear-chain-based MC ray tracing packages widely used in instrument design and optimization, as well as NumPy-based components that make prototypes useful and easy to develop. These developments have enabled us to carry out detailed simulations of neutron scattering experiments with non-trivial samples in time-of-flight inelastic instruments at the Spallation Neutron Source. Examples of such simulations for powder and single-crystal samples with various scattering kernels, including kernels for phonon and magnon scattering, are presented. With simulations that closely reproduce experimental results, scattering mechanisms can be turned on and off to determine how they contribute to the measured scattering intensities, improving our understanding of the underlying physics.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
