English

Minimum Spanning Trees of Random Geometric Graphs with Location Dependent Weights

Probability 2021-03-02 v1

Abstract

Consider~nn nodes~{Xi}1in\{X_i\}_{1 \leq i \leq n} independently distributed in the unit square~S,S, each according to a distribution~f.f. Nodes~XiX_i and~XjX_j are joined by an edge if the Euclidean distance~d(Xi,Xj)d(X_i,X_j) is less than~rn,r_n, the adjacency distance and the resulting random graph~GnG_n is called a random geometric graph~(RGG). We now assign a location dependent weight to each edge of~GnG_n and define~MSTnMST_n to be the sum of the weights of the minimum spanning trees of all components of~Gn.G_n. For values of~rnr_n above the connectivity regime, we obtain upper and lower bound deviation estimates for~MSTnMST_n and~L2L^2-convergence of~MSTnMST_n appropriately scaled and centred.

Keywords

Cite

@article{arxiv.2103.00764,
  title  = {Minimum Spanning Trees of Random Geometric Graphs with Location Dependent Weights},
  author = {Ghurumuruhan Ganesan},
  journal= {arXiv preprint arXiv:2103.00764},
  year   = {2021}
}

Comments

Accepted for publication in Bernoulli

R2 v1 2026-06-23T23:36:11.239Z