Random Structures and Algorithms · 2016 · 41 citations · 20 references
Spectral TheoryGraph SparsityEngineeringNetwork AnalysisEducationRandom GraphStructural Graph TheoryRandom GraphsStochastic GeometryDiscrete MathematicsSpectral GapProbabilistic Graph TheoryPhysicsProbability TheoryRandom EdgeNormalized LaplacianNetwork ScienceGraph TheoryRandom MatrixExtremal Graph Theory
We study how the spectral gap of the normalized Laplacian of a random graph changes when an edge is added to or removed from the graph. There are known examples of graphs where, perhaps counter-intuitively, adding an edge can decrease the spectral gap, a phenomenon that is analogous to Braess's paradox in traffic networks. We show that this is often the case in random graphs in a strong sense. More precisely, we show that for typical instances of Erdős-Rényi random graphs G(n, p) with constant edge density , the addition of a random edge will decrease the spectral gap with positive probability, strictly bounded away from zero. To do this, we prove a new delocalization result for eigenvectors of the Laplacian of G(n, p), which might be of independent interest. © 2016 Wiley Periodicals, Inc. Random Struct. Alg., 50, 584–611, 2017
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