Linear variance conjecture for zero-free probability generating functions

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Let X∈{0,…,n}X\in\{0,\ldots,n\} be a random variable with p0pn>0p_0p_n>0 and probability generating function fXf_X. Let δ>0\delta>0 and R⩾1R\geqslant1. If every zero ζ\zeta of fXf_X satisfies

∣arg⁡(ζ)∣⩾δ,|\operatorname{arg}(\zeta)|\geqslant\delta,

and

R−1⩽∣ζ∣⩽R,R^{-1}\leqslant|\zeta|\leqslant R,

then Linear variance conjecture.

Var⁡(X)=ΩR,δ(n).\operatorname{Var}(X)=\Omega_{R,\delta}(n).

The conjecture asserts that, under these zero-location restrictions, the variance is essentially as large as possible; the source states that it remains of independent interest and motivates the paper's work.

References

Primary source

Marcus Michelen and Julian Sahasrabudhe, “Anti-concentration of random variables from zero-free regions”, arXiv:2102.07699 (2022).

Additional references

2 papers in this index state this conjecture (2019–2021). The statement above is taken from the most recent of them; the others are arXiv:1906.02602.

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