
arXiv: math/0606624
AbstractWe study the spectral measure of large Euclidean random matrices. The entries of these matrices are determined by the relative position of n random points in a compact set Ωn of ℝd. Under various assumptions, we establish the almost sure convergence of the limiting spectral measure as the number of points goes to infinity. The moments of the limiting distribution are computed, and we prove that the limit of this limiting distribution as the density of points goes to infinity has a nice expression. We apply our results to the adjacency matrix of the geometric graph. © 2008 Wiley Periodicals, Inc. Random Struct. Alg., 2008
Random matrices (algebraic aspects), spatial point process, Graphs and linear algebra (matrices, eigenvalues, etc.), Euclidean distance matrix, Probability (math.PR), Random graphs (graph-theoretic aspects), random matrix, spectral measure, random geometric graphs, 15A52 (Primary) 60F99, 05C50 (Secondary), FOS: Mathematics, Point processes (e.g., Poisson, Cox, Hawkes processes), General theory of distance geometry, Mathematics - Probability
Random matrices (algebraic aspects), spatial point process, Graphs and linear algebra (matrices, eigenvalues, etc.), Euclidean distance matrix, Probability (math.PR), Random graphs (graph-theoretic aspects), random matrix, spectral measure, random geometric graphs, 15A52 (Primary) 60F99, 05C50 (Secondary), FOS: Mathematics, Point processes (e.g., Poisson, Cox, Hawkes processes), General theory of distance geometry, Mathematics - Probability
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