pith. machine review for the scientific record. sign in

arxiv: 2402.14631 · v11 · submitted 2024-02-22 · 🧮 math.CV · math.DG· math.PR

Recognition: unknown

Equidistribution for Random Polynomials and Systems of Random Holomorphic Sections

Authors on Pith no claims yet
classification 🧮 math.CV math.DGmath.PR
keywords randomholomorphicequidistributionsectionspolynomialssystemslinemanifolds
0
0 comments X
read the original abstract

This article addresses an equidistribution problem concerning the zeros of systems of random holomorphic sections of positive line bundles on compact K\"{a}hler manifolds and random polynomials on $\mathbb{C}^{m}$ in the setting of the weighted pluripotential theory. For random polynomials, we consider non-orthonormal bases and prove an equidistribution result which is more general than the ones acquired before for non-discrete probability measures. More precisely, our result demonstrates that the equidistribution holds true even when the random coefficients in the basis representation are not independent and identically distributed (i.i.d.), and moreover, they are not constrained to any particular probability distribution. For random holomorphic sections, by extending the concept of a sequence of asymptotically Bernstein-Markov measures introduced by Bayraktar, Bloom and Levenberg in their recent paper to the setting of holomorphic line bundles over compact Kahler manifolds, we derive a global equidistribution, variance estimate and expected distribution theorems related to the zeros of systems of random holomorphic sections for large tensor powers of a fixed holomorphic line bundle for any codimension k, generalizing a previous result of Bayraktar in his 2016 paper and giving also a positive answer to a question posed in the same paper, asking whether the equidistribution is true for non-homogeneous manifolds. For both random holomorphic polynomials on $\mathbb{C}^{m}$ and systems of random holomorphic sections, the variance estimation method detailed in another paper of the author with Bojnik is significant.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Edge-Efficient Image Restoration: Transformer Distillation into State-Space Models

    cs.CV 2026-05 unverdicted novelty 6.0

    Hybrid transformer-SSM networks found by multi-objective search run 1.17x to 3.4x faster on edge CPUs for image restoration tasks with competitive quality.