Near-minimal spanning trees: A scaling exponent in probability models
We study the relation between the minimal spanning tree (MST) on many random points and the “near-minimal” tree which is optimal subject to the constraint that a proportion δ of its edges must be different from those of the MST. Heuristics suggest that, regardless of details of the probability model...
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Published in | Annales de l'I.H.P. Probabilités et statistiques Vol. 44; no. 5; pp. 962 - 976 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Institut Henri Poincaré
01.10.2008
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Abstract | We study the relation between the minimal spanning tree (MST) on many random points and the “near-minimal” tree which is optimal subject to the constraint that a proportion δ of its edges must be different from those of the MST. Heuristics suggest that, regardless of details of the probability model, the ratio of lengths should scale as 1+Θ(δ2). We prove this scaling result in the model of the lattice with random edge-lengths and in the Euclidean model. |
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AbstractList | We study the relation between the minimal spanning tree (MST) on many random points and the “near-minimal” tree which is optimal subject to the constraint that a proportion δ of its edges must be different from those of the MST. Heuristics suggest that, regardless of details of the probability model, the ratio of lengths should scale as 1+Θ(δ2). We prove this scaling result in the model of the lattice with random edge-lengths and in the Euclidean model. |
Author | Lelarge, Marc Aldous, David J. Bordenave, Charles |
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SubjectTerms | 05C80 60K35 68W40 Combinatorial optimization Continuum percolation Disordered lattice Local weak convergence Minimal spanning tree Poisson point process Probabilistic analysis of algorithms Random geometric graph |
Title | Near-minimal spanning trees: A scaling exponent in probability models |
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