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Random Structures and Algorithms
Article . 2008 . Peer-reviewed
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Eigenvalues of Euclidean random matrices

Authors: Charles Bordenave;

Eigenvalues of Euclidean random matrices

Abstract

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

Keywords

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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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
23
Top 10%
Top 10%
Average
Green
bronze