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Random Structures and Algorithms
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Random Structures and Algorithms
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Law of the iterated logarithm for random graphs

Authors: Asaf Ferber; Daniel Montealegre; Van Vu;

Law of the iterated logarithm for random graphs

Abstract

AbstractA milestone in probability theory is the law of the iterated logarithm (LIL), proved by Khinchin and independently by Kolmogorov in the 1920s, which asserts that for iid random variables with mean 0 and variance 1In this paper we prove that LIL holds for various functionals of random graphs and hypergraphs models. We first prove LIL for the number of copies of a fixed subgraph H. Two harder results concern the number of global objects: perfect matchings and Hamiltonian cycles. The main new ingredient in these results is a large deviation bound, which may be of independent interest. For random k‐uniform hypergraphs, we obtain the Central Limit Theorem and LIL for the number of Hamilton cycles.

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Keywords

Eulerian and Hamiltonian graphs, small subgraphs, Edge subsets with special properties (factorization, matching, partitioning, covering and packing, etc.), Random graphs (graph-theoretic aspects), central limit theorem, distribution, Enumeration in graph theory, Hypergraphs, Hamilton cycles, perfect matchings

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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!
2
Average
Average
Average
hybrid