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The Minimum Spanning Tree Constant in Geometrical Probability and Under the Independent Model; A Unified Approach

机译:几何概率和独立模型下的最小生成树常数;统一方法

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摘要

Given n uniformly and independently points in the d dimensional cube of unit volume, it is well established that the length of the minimum spanning tree on these n points is asymptotic to /3MsT(d)n(d-l)/d,where the constant PMST(d) depends only on the dimension d. It has been a major open problem to determine the constant 3MST(d). In this paper we obtain an exact expression of the constant MST(d) as a series expansion. Truncating the expansion after a finite number of terms yields a sequence of lower bounds; the first 3 terms give a lower bound which is already very close to the empirically estimated value of the constant. Our proof technique unifies the derivation for the MST asymptotic behavior for the Euclidean and the independent model.
机译:给定单位体积d维立方体中的n个独立且均匀的点,可以很好地确定,这n个点上的最小生成树的长度渐近于/ 3MsT(d)n(dl)/ d,其中PMST恒定(d)仅取决于尺寸d。确定常数3MST(d)是一个主要的开放问题。在本文中,我们获得了常数MST(d)作为级数展开的精确表达式。在有限数量的项之后截断扩展会产生一系列下界;前三个项给出一个下限,该下限已经非常接近常数的经验估计值。我们的证明技术统一了欧氏方程和独立模型的MST渐近行为的推导。

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