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Zeros distribution of gaussian entire functions (1401.2776v1)

Published 13 Jan 2014 in math.CV

Abstract: In this paper we consider a random entire function of the form $f(z,\omega )=\sum\nolimits_{n=0}{+\infty}\xi_n(\omega )a_nzn,$ where $\xi_n(\omega )$ are independent standard\break complex gaussian random variables and $a_n\in\mathbb{C}$ satisfy the relations\break $\varlimsup\limits_{n\to+\infty}\sqrt[n]{|a_n|}=0$ and $ #{n\colon a_n\neq0}=+\infty.$ We investigate asymptotic properties of the probability $P_0(r)=P{\omega\colon f(z,\omega )$ has no zeros inside $r\mathbb{D}}.$ Denote $ p_0(r)=\ln-P_0(r),\ N(r)=#{n\colon \ln (|a_n|rn)>0},$ $ s(r)=\sum_{n=0}{+\infty}\ln+(|a_n|r{n}). $ Assuming that $a_0\neq0$ we prove that $ 0\leq\varliminf_{r\to+\infty,\ r\notin E}\frac{\ln(p_0(r)- s(r))}{\ln s(r)},\ \varlimsup_{r\to+\infty,\ r\notin E}\frac{\ln(p_0(r)- s(r))}{\ln s(r)}\leq\frac12, $ $ \lim\limits_{r\to+\infty,\ r\notin E}\frac{\ln(p_0(r)- s(r))}{\ln N(r)}=1. $ where $E$ is a set of finite logarithmic measure. Remark that the previous inequalities are sharp. Also we give an answer to open question from \cite[p. 119]{nishry 5}.

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