LOWER TAILS VIA RELATIVE ENTROPY

Gady Kozma*, Wojciech Samotij

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

We show that the naive mean-field approximation correctly predicts the leading term of the logarithmic lower tail probabilities for the number of copies of a given subgraph in G(n,p) and of arithmetic progressions of a given length in random subsets of the integers in the entire range of densities where the mean-field approximation is viable. Our main technical result provides sufficient conditions on the maximum degrees of a uniform hypergraph H that guarantee that the logarithmic lower tail probabilities for the number of edges, induced by a binomial random subset of the vertices of H, can be well approximated by considering only product distributions. This may be interpreted as a weak, probabilistic version of the hypergraph container lemma that is applicable to all sparser-than-average (and not only independent) sets.

Original languageEnglish
Pages (from-to)665-698
Number of pages34
JournalAnnals of Probability
Volume51
Issue number2
DOIs
StatePublished - 2023

Funding

FundersFunder number
Jesselson Foundation
Israel Science Foundation1145/18
UK Research and Innovation107289

    Keywords

    • Lower tail
    • random graph
    • subgraph counts

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