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arXiv 1003.3301math.MGcond-mat.softcond-mat.stat-mech
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一种密集堆积发现方法

A method for dense packing discovery

Yoav Kallus, Veit Elser, Simon Gravel

摘要:

尽可能密集地填充粒子系统的问题是离散几何领域的基础,也是材料和生物科学中的一个强大模型。随着填充问题从解析构造的解决方案范围内撤退,进行\textit{de novo}(从头开始)搜索密集填充的有效数值方法的重要性变得至关重要。在本文中,我们使用\textit{divide and concur}框架,发展了一个通用的搜索法的周期约束问题的解决方案,我们把它应用到发现密集周期包装。该方法的一个重要特点是将晶胞参数与组态空间定义中的其他填充变量相结合。我们提出的方法导致了[arXiv:0910.5226]中报道的最密集的已知四面体堆积的改进。在这里,我们使用的方法来重现dennies已知的晶格球包装和最知名的晶格接吻安排分别在14和11维(第一个这样的数字证据,他们的最优性,在这些方面)。对于非球形粒子,我们报告了一个新的密度为$ϕ=128/219\approx0.5845$的规则四维单形的稠密堆积,并具有与已知的四面体堆积类似的结构。

英文摘要:

The problem of packing a system of particles as densely as possible is foundational in the field of discrete geometry and is a powerful model in the material and biological sciences. As packing problems retreat from the reach of solution by analytic constructions, the importance of an efficient numerical method for conducting \textit{de novo} (from-scratch) searches for dense packings becomes crucial. In this paper, we use the \textit{divide and concur} framework to develop a general search method for the solution of periodic constraint problems, and we apply it to the discovery of dense periodic packings. An important feature of the method is the integration of the unit cell parameters with the other packing variables in the definition of the configuration space. The method we present led to improvements in the densest-known tetrahedron packing which are reported in [arXiv:0910.5226]. Here, we use the method to reproduce the densest known lattice sphere packings and the best known lattice kissing arrangements in up to 14 and 11 dimensions respectively (the first such numerical evidence for their optimality in some of these dimensions). For non-spherical particles, we report a new dense packing of regular four-dimensional simplices with density $ϕ=128/219\approx0.5845$ and with a similar structure to the densest known tetrahedron packing.

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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