Variance-based anti-concentration conjecture for edge counts in Ramsey graphs

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Let C,c>0C,c>0 be fixed constants. Let GG be an nn-vertex CC-Ramsey graph, meaning that GG has no clique or independent set of size Clog⁡nC\log n. Let kk satisfy

cn≤k≤(1−c)n,cn\le k\le (1-c)n,

and let XX be the number of edges induced by a uniformly random kk-vertex subset of GG.

Variance-based anti-concentration conjecture. For every x∈Zx\in\mathbb{Z},

Pr⁡(X=x)=O\originalleft(1Var⁡X\aftergroup\originalright).\Pr(X=x)=O\mathopen{}\mathclose\bgroup\originalleft(\frac{1}{\sqrt{\operatorname{Var} X}}\aftergroup\egroup\originalright).

This would give an optimal point-probability bound in terms of the variance, as suggested by Chebyshev's inequality. The statement is presented as an interesting open direction for Ramsey graphs.

References

Primary source

Matthew Kwan and Lisa Sauermann, “An algebraic inverse theorem for the quadratic Littlewood-Offord problem, and an application to Ramsey graphs”, arXiv:1909.02089 (2020).

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