Homemath.PRarXiv:2605.29962

Gaussian Multiplicative Chaos for i.i.d. matrices

math.PRmath-phmath.MP2026-05v1license

Abstract

We consider N×NN\times N matrices XX with independent, identically distributed entries, and prove that the sequence of measures det(Xz)γE[det(Xz)γ]\frac{ | \det (X-z)|^\gamma}{\mathbb{E}[ | \det (X-z)|^\gamma]} converge to the Gaussian Multiplicative Chaos in the full subcritical regime γ(0,22)\gamma \in (0, 2 \sqrt{2}) as NN \to \infty. Our result holds for both symmetry classes and in particular is new even for real Ginibre matrices, and is the first such convergence for any non-invariant ensemble of random matrices. We also establish the asymptotics for the KK-point function of det(Xz)| \det (X-z)| at any collection of mesoscopically separated points ziz_i. Our methods are analytic and probabilistic in nature, relying in part on the dynamical approach based on Dyson Brownian motion.

Comments: 80 pages

Cite

@article{arxiv.2605.29962,
  title  = {Gaussian Multiplicative Chaos for i.i.d. matrices},
  author = {Giorgio Cipolloni and Benjamin Landon},
  journal= {arXiv preprint arXiv:2605.29962},
  year   = {2026}
}