Inequalities Concerning Maximum Modulus and Zeros of Random Entire Functions
英文摘要：
Let $f_ω(z)=\sum\limits_{j=0}^{\infty}χ_j(ω) a_j z^j$ be a random entire function, where $χ_j(ω)$ are independent and identically distributed random variables defined on a probability space $(Ω, \mathcal{F}, μ)$. In this paper, we first define a family of random entire functions, which includes Gaussian, Rademacher, Steinhaus entire functions. Then, we prove that, for almost all functions in the family and for any constant $C>1$, there exist a constant $r_0=r_0(ω)$ and a set $E\subset [e, \infty)$ of finite logarithmic measure such that, for $r>r_0$ and $r\notin E$, $$ |\log M(r, f)- N(r,0, f_ω)|\le (C/A)^{\frac1{B}}\log^{\frac1{B}}\log M(r,f) +\log\log M(r, f), \qquad a.s. $$ where $A, B$ are constants, $M(r, f)$ is the maximum modulus, and $N(r, 0, f)$ is the weighted counting-zero function of $f$. As a by-product of our main results, we prove Nevanlinna's second main theorem for random entire functions. Thus, the characteristic function of almost all functions in the family is bounded above by a weighed counting function, rather than by two weighted counting functions in the classical Nevanlinna theory. For instance, we show that, for almost all Gaussian entire functions $f_ω$ and for any $ε>0$, there is $r_0$ such that, for $r>r_0$, $$ T(r, f) \le N(r,0, f_ω)+(\frac12+ε) \log T(r, f). $$
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
