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arXiv 2102.05461cond-mat.softphysics.comp-ph
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稠密软物质系统的事件链蒙特卡罗模拟

Event-Chain Monte-Carlo Simulations of Dense Soft Matter Systems

Tobias A. Kampmann, David Müller, Clemens Franz Vorsmann, Lukas Paul Weise, Jan Kierfeld

摘要:

讨论了无排斥事件链蒙特卡罗算法及其在稠密软物质系统中的应用。事件链蒙特卡罗是标准局部马尔可夫链蒙特卡罗方案的替代方案,其基于细致平衡,例如众所周知的Metropolis-Hastings算法。事件链蒙特卡罗(英语:Event-chain Monte-Carlo)是一种马尔可夫链蒙特卡罗方法,它使用所谓的提升移动来实现全局平衡而没有拒绝(最大全局平衡)。它最初是为硬球系统开发的,但适用于许多软物质系统,特别适合于具有硬核相互作用的致密软物质系统,与局部蒙特卡罗模拟相比,它提供了显着的性能增益。该算法可以推广到处理软相互作用和三粒子相互作用,因为它们自然出现,例如,在珠弹簧模型的聚合物弯曲刚度。我们目前的结果为聚合物熔体,事件链算法可以用于一个有效的初始化。然后,我们移动到大型系统的半柔性聚合物,形成有吸引力的相互作用束,可以作为模型系统的肌动蛋白丝在细胞骨架。事件链算法表明,这些系统形成的网络束粗类似于泡沫。最后,我们提出的结果液晶系统中,事件链算法可以平衡的大型系统包含额外的胶体磁盘非常有效,这揭示了磁盘的并行链。

英文摘要:

We discuss the rejection-free event-chain Monte-Carlo algorithm and several applications to dense soft matter systems. Event-chain Monte-Carlo is an alternative to standard local Markov-chain Monte-Carlo schemes, which are based on detailed balance, for example the well-known Metropolis-Hastings algorithm. Event-chain Monte-Carlo is a Markov chain Monte-Carlo scheme that uses so-called lifting moves to achieve global balance without rejections (maximal global balance). It has been originally developed for hard sphere systems but is applicable to many soft matter systems and particularly suited for dense soft matter systems with hard core interactions, where it gives significant performance gains compared to a local Monte-Carlo simulation. The algorithm can be generalized to deal with soft interactions and with three-particle interactions, as they naturally arise, for example, in bead-spring models of polymers with bending rigidity. We present results for polymer melts, where the event-chain algorithm can be used for an efficient initialization. We then move on to large systems of semiflexible polymers that form bundles by attractive interactions and can serve as model systems for actin filaments in the cytoskeleton. The event chain algorithm shows that these systems form networks of bundles which coarsen similar to a foam. Finally, we present results on liquid crystal systems, where the event-chain algorithm can equilibrate large systems containing additional colloidal disks very efficiently, which reveals the parallel chaining of disks.

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。

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