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Can the Euclidean minimum spanning tree (MST) of n points in \R^d be computed in time close to the lower bound of \Omega(n \log n) [GKFS96]?
Uncertain, pending investigation.
Several algorithms have been developed for general graphs with arbitrary edge weights. Chazelle presented an O(m \alpha(m,n) \log \alpha(m,n))-time algorithm [Cha97], and then an O(m \alpha(m,n))-time algorithm [Cha00b], where \alpha(m,n) is the functional inverse of Ackermann’s function, and n and m are the number of vertices and edges respectively in the graph. Pettie and Ramachandran have since given an optimal algorithm for the graph setting [PR02], whose running time is an unknown function between \Omega(m) and O(m \alpha(m,n)). In particular, when m = \Omega(n \log n), \alpha(m,n) = O(1) and these time bounds are all linear in the number of edges, m.
But in the geometric setting, the graph is complete, so a time bound linear in the number of edges, m, is quadratic in the number of points, n. And indeed the best upper bounds for the Euclidean MST approach quadratic for large d, e.g., [CK95].
This problem is intimately related to the bichromatic closest pair problem [AESW91].
minimum spanning tree; shortest paths
J. O’Rourke, 2 Aug. 2001; E. Demaine, 7 July 2002.
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