Central limit theorem for the principal eigenvalue and eigenvector of Chung–Lu random graphs
| Autor: | Rajat Subhra Hazra, Pierfrancesco Dionigi, Diego Garlaschelli, Michel Mandjes, Frank Den Hollander |
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| Rok vydání: | 2023 |
| Předmět: |
Statistical Mechanics (cond-mat.stat-mech)
Computer Networks and Communications Statistical Physics Probability (math.PR) FOS: Physical sciences Disordered Systems and Neural Networks (cond-mat.dis-nn) Mathematical Physics (math-ph) Condensed Matter - Disordered Systems and Neural Networks Computer Science Applications Artificial Intelligence FOS: Mathematics Random Graph 60B20 60C05 60K35 Spectral Graph Theory Mathematics - Probability Condensed Matter - Statistical Mechanics Mathematical Physics Central Limit Theorem Information Systems |
| Zdroj: | Journal of Physics: Complexity, 4(1):015008. IOP Publishing |
| ISSN: | 2632-072X |
| DOI: | 10.1088/2632-072x/acb8f7 |
| Popis: | A Chung–Lu random graph is an inhomogeneous Erdős–Rényi random graph in which vertices are assigned average degrees, and pairs of vertices are connected by an edge with a probability that is proportional to the product of their average degrees, independently for different edges. We derive a central limit theorem for the principal eigenvalue and the components of the principal eigenvector of the adjacency matrix of a Chung–Lu random graph. Our derivation requires certain assumptions on the average degrees that guarantee connectivity, sparsity and bounded inhomogeneity of the graph. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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