An asymptotic refinement of the Gauss-Lucas Theorem for random polynomials with i.i.d. roots

If $p:\mathbb{C} \to \mathbb{C}$ is a non-constant polynomial, the Gauss--Lucas theorem asserts that its critical points are contained in the convex hull of its roots.

We consider the case when $p$ is a random polynomial of degree $n$ with roots chosen independently from a radially symmetric, compactly supported probability measure $\mu$ in the complex plane.

We show that the largest (in magnitude) critical points are closely paired with the largest roots of $p$.

This allows us to compute the asymptotic fluctuations of the largest critical points as the degree $n$ tends to infinity.

We show that the limiting distribution of the fluctuations is described by either a Gaussian distribution or a heavy-tailed stable distribution, depending on the behavior of $\mu$ near the edge of its support.

As a corollary, we obtain an asymptotic refinement to the Gauss--Lucas theorem for random polynomials.