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

Fuente: arXiv
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Main Authors: O'Rourke, Sean, Williams, Noah
Format: Preprint
Published: 2024
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author O'Rourke, Sean
Williams, Noah
author_facet O'Rourke, Sean
Williams, Noah
contents 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 probably measure $μ$ 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 $μ$ near the edge of its support. As a corollary, we obtain an asymptotic refinement to the Gauss--Lucas theorem for random polynomials.
format Preprint
id arxiv_https___arxiv_org_abs_2409_09538
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle An asymptotic refinement of the Gauss-Lucas Theorem for random polynomials with i.i.d. roots
O'Rourke, Sean
Williams, Noah
Probability
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 probably measure $μ$ 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 $μ$ near the edge of its support. As a corollary, we obtain an asymptotic refinement to the Gauss--Lucas theorem for random polynomials.
title An asymptotic refinement of the Gauss-Lucas Theorem for random polynomials with i.i.d. roots
topic Probability
url https://arxiv.org/abs/2409.09538