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unusual facts about Minimum spanning tree


Minimum spanning tree

Alan M. Frieze showed that given a complete graph on n vertices, with edge weights that are independent identically distributed random variables with distribution function F satisfying F'(0) > 0, then as n approaches +∞ the expected weight of the MST approaches \zeta(3)/F'(0), where \zeta is the Riemann zeta function.



see also

Euclidean minimum spanning tree

The simplest algorithm to find an EMST in two dimensions, given n points, is to actually construct the complete graph on n vertices, which has n(n-1)/2 edges, compute each edge weight by finding the distance between each pair of points, and then run a standard minimum spanning tree algorithm (such as the version of Prim's algorithm or Kruskal's algorithm) on it.

Since there are O(n) edges, this requires O(n log n) time using any of the standard minimum spanning tree algorithms such as Borůvka's algorithm, Prim's algorithm, or Kruskal's algorithm.