Newtonian Event-Chain Monte Carlo and Collision Prediction with Polyhedral Particles
Newtonian Event-Chain Monte Carlo and Collision Prediction with Polyhedral Particles
复制标题
牛顿事件链蒙特卡罗和多面体粒子的碰撞预测
DOI：
10.1021/acs.jctc.1c00311
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发表时间：
2021
影响因子：
5.5
通讯作者：
Engel, Michael
中科院分区：
文献类型：
--
作者：
Klement, Marco;Lee, Sangmin;Anderson, Joshua A.;Engel, Michael
多面体纳米晶体是纳米结构材料的构建块，在催化和等离子体中找到应用。合成工作和自组装实验得到了预测相平衡的计算机模拟的帮助。目前大多数模拟采用蒙特卡罗方法，产生随机动态。集体和相关的配置更新的替代方案，承诺更高的计算效率和生成具有现实动力学的轨迹。一个这样的替代方案涉及事件链更新，最近已被提议用于球形粒子。在这方面的贡献，我们开发和应用事件链蒙特卡罗硬凸多面体。我们的模拟利用了一种改进的计算几何算法XenoSweep，它以一种特别简单的方式预测扫描碰撞。我们实现牛顿事件链的开源通用粒子模拟工具包HOOMD-blue的串行和并行模拟。与最先进的Monte Carlo相比，对于近似球形多面体，加速倍数在10倍之间，对于高度非球形多面体，加速倍数在2倍之间。最后，我们将牛顿事件链算法应用于两类硬多面体的多步成核问题，验证了算法的有效性。
Polyhedral nanocrystals are building blocks for nanostructured materials that find applications in catalysis and plasmonics. Synthesis efforts and self-assembly experiments have been assisted by computer simulations that predict phase equilibria. Most current simulations employ Monte Carlo methods, which generate stochastic dynamics. Collective and correlated configuration updates are alternatives that promise higher computational efficiency and generate trajectories with realistic dynamics. One such alternative involves event-chain updates and has recently been proposed for spherical particles. In this contribution, we develop and apply event-chain Monte Carlo for hard convex polyhedra. Our simulation makes use of an improved computational geometry algorithm XenoSweep, which predicts sweep collision in a particularly simple way. We implement Newtonian event chains in the open-source general-purpose particle simulation toolkit HOOMD-blue for serial and parallel simulation. The speedup over state-of-the-art Monte Carlo is between a factor of 10 for nearly spherical polyhedra and a factor of 2 for highly aspherical polyhedra. Finally, we validate the Newtonian event-chain algorithm by applying it to a current research problem, the multistep nucleation of two classes of hard polyhedra.