A strong law of large numbers for real roots of random polynomials

We consider random polynomials $p_n(x)={\xi }_0+{\xi }_1+\cdots +{\xi }_n{x}^n$ whose coefficients are independent and identically distributed with zero mean, unit variance, and bounded $(2+\epsilon {)}^{th}$ moment (for some $\epsilon >0$), also known as the Kac polynomials. Let $N_n$ denote the number of real roots of $p_n$. In this paper, motivated by a question from Igor Pritsker, we prove that almost surely the following convergence holds: \begin{eqnarray*} \lim_{n\to\infty} \frac{N_n([-1,1])}{\log n} &=& \frac 1 π. \end{eqnarray*} This convergence could be viewed as a local strong law for the real roots. The main ingredient in the proof is a set of maximal inequalities that reduces the proof to proving convergence along lacunary subsequences, which in turn follows from a recent concentration estimate of Can–Nguyen.