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Pessimal packing shapes

机译:最小包装形状

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We address the question of which convex shapes, when packed as densely as possible under certain restrictions, fill the least space and leave the most empty space. In each different dimension and under each different set of restrictions, this question is expected to have a different answer or perhaps no answer at all. As the problem of identifying global minima in most cases appears to be beyond current reach, in this paper we focus on local minima. We review some known results and prove these new results: in two dimensions, the regular heptagon is a local minimum of the double-lattice packing density, and in three dimensions, the directional derivative (in the sense of Minkowski addition) of the double-lattice packing density at the point in the space of shapes corresponding to the ball is in every direction positive.
机译:我们要解决的问题是,在某些限制下尽可能密集地填充哪些凸形时,它们会填充最少的空间并留下最大的空白空间。在每个不同的维度上以及每个不同的限制条件下,这个问题的答案都可能不同,或者根本没有答案。由于在大多数情况下识别全局最小值的问题似乎超出了当前范围,因此在本文中,我们重点关注局部最小值。我们回顾了一些已知的结果并证明了这些新结果:在二维中,正七边形是双晶堆积密度的局部最小值,在三维中,正六边形是双晶堆积密度的局部导数(在Minkowski加法意义上)在与球相对应的形状空间中,该点处的点阵堆积密度在每个方向上均为正。

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