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The Central Limit Theorem and Berry--Esseen bound for logarithmic law of random determinants

Song-Hao Liu, Qi-Man Shao, Jing-Yu Xu

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Source: arXiv

Published: Sep 10, 2026

arXiv: 2609.11688

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Source abstract

Let A=(An)n≥2A=(A_n)_{n\ge2} be a triangular array of random matrices, where An=(aij)1≤i,j≤nA_n=(a_{ij})_{1\le i,j\le n} is an n×nn\times n random matrix with independent real entries satisfying Eaij=0\mathbb E a_{ij}=0 and Eaij2=1\mathbb Ea_{ij}^2=1, and put Ln=log⁡∣det⁡An∣\mathcal L_n=\log|\det A_n| and Wnd(An):=Ln−12log⁡(n−1)!12log⁡n,Wne(An):=Ln−ELn12log⁡n. W_n^{\mathrm d}(A_n):=\frac{\mathcal L_n - \frac12\log(n-1)!}{\sqrt{\frac12\log n}},\quad W_n^{\mathrm e}(A_n):= \frac{\mathcal L_n-\mathbb E \mathcal L_n}{\sqrt{\frac12\log n}}. We prove that Wnd(An)⇒N(0,1)W_n^{\mathrm d}(A_n) \Rightarrow \mathcal N(0,1), whenever the family {∣aij∣4log⁡(e+∣aij∣)}n≥2;1≤i,j≤n\left\{\frac{|a_{ij}|^{4}}{\sqrt{\log(e+|a_{ij}|)}} \right\}_{n\geq 2;1\leq i,j\leq n} is uniformly integrable. If, in addition, the entries have uniformly bounded densities, then Wne(An)⇒N(0,1)W_n^{\mathrm e}(A_n) \Rightarrow \mathcal N(0,1) whenever the family {∣aij∣4log⁡(e+∣aij∣)}n≥2;1≤i,j≤n\left\{\frac{|a_{ij}|^{4}}{\log(e+|a_{ij}|)}\right\}_{n\geq 2;1\leq i,j\leq n} is uniformly integrable. These two conditions are optimal at the level of universal moment assumptions. We further establish the corresponding Berry--Esseen bounds, and show that for 0<δ≤120<δ\le\tfrac12, if sup⁡nmax⁡1≤i,j≤nE∣aij∣4{log⁡(e+∣aij∣)}1/2−δ<∞\sup\limits_{n}\max\limits_{1\le i,j\le n}\mathbb E \frac{|a_{ij}|^4} {\{\log(e+|a_{ij}|)\}^{1/2-δ}}<\infty, then dK(Wnd(An),N(0,1))≤C(log⁡n)−δ.\begin{align*} d_{\mathrm K}(W_n^{\mathrm d}(A_n),\mathcal N(0,1))\le C(\log n)^{-δ}. \end{align*} For 0<γ≤10<γ\le1, if sup⁡nmax⁡1≤i,j≤nE∣aij∣4{log⁡(e+∣aij∣)}1−γ<∞\sup\limits_{n}\max\limits_{1\le i,j\le n}\mathbb E \frac{|a_{ij}|^4} {\{\log(e+|a_{ij}|)\}^{1-γ}}<\infty and the entries have uniformly bounded densities, then dK(Wne(An),N(0,1))≤C(log⁡n)−γ.\begin{align*} d_{\mathrm K}(W_n^{\mathrm e}(A_n),\mathcal N(0,1))\le C(\log n)^{-γ}. \end{align*} When δ=1/2δ= 1/2 and γ=1γ= 1, the bounds (log⁡n)−1/2(\log n)^{-1/2} and (log⁡n)−1(\log n)^{-1} are optimal, respectively. Our results improve the earlier Central Limit Theorem by \cite{BaoPanZhou2015} and the Berry--Esseen bound by \cite{NguyenVu2014}.

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The Central Limit Theorem and Berry--Esseen bound for logarithmic law of random determinants — Mathematical Frontier Network