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Upper Tail Behavior of the Number of Triangles in Random Graphs with Constant Average Degree

  • Shirshendu Ganguly,
  • Ella Hiesmayr,
  • Kyeongsik Nam

摘要

Let N be the number of triangles in an Erdős–Rényi graph \({\mathcal {G}}(n,p)\) G ( n , p ) on n vertices with edge density \(p=d/n,\) p = d / n , where \(d>0\) d > 0 is a fixed constant. It is well known that N weakly converges to the Poisson distribution with mean \({d^3}/{6}\) d 3 / 6 as \(n\rightarrow \infty \) n . We address the upper tail problem for N,  namely, we investigate how fast k must grow, so that \({\mathbb {P}}(N\ge k)\) P ( N k ) is not well approximated anymore by the tail of the corresponding Poisson variable. Proving that the tail exhibits a sharp phase transition, we essentially show that the upper tail is governed by Poisson behavior only when \(k^{1/3} \log k< (\frac{3}{\sqrt{2}} - {o(1)})^{2/3} \log n\) k 1 / 3 log k < ( 3 2 - o ( 1 ) ) 2 / 3 log n (sub-critical regime) as well as pin down the tail behavior when \(k^{1/3} \log k> (\frac{3}{\sqrt{2}} + {o(1)})^{2/3} \log n\) k 1 / 3 log k > ( 3 2 + o ( 1 ) ) 2 / 3 log n (super-critical regime). We further prove a structure theorem, showing that the sub-critical upper tail behavior is dictated by the appearance of almost k vertex-disjoint triangles whereas in the supercritical regime, the excess triangles arise from a clique like structure of size approximately \((6k)^{1/3}\) ( 6 k ) 1 / 3 . This settles the long-standing upper-tail problem in this case, answering a question of Aldous, complementing a long sequence of works, spanning multiple decades and culminating in Harel et al. (Duke Math J 171(10):2089–2192, 2022), which analyzed the problem only in the regime \(p\gg \frac{1}{n}.\) p 1 n . The proofs rely on several novel graph theoretical results which could have other applications.