Thin-shell theory for rotationally invariant random simplices

Abstract

For fixed functions G,H:[0,∞)[0,∞), consider the rotationally invariant probability density on Rn of the form \[ μn(ds) = 1Zn G(\|s\|2)\, e - n H( \|s\|2) ds. \] We show that when n is large, the Euclidean norm \|Yn\|2 of a random vector Yn distributed according to μn satisfies a Gaussian thin-shell property: the distribution of \|Yn\|2 concentrates around a certain value s0, and the fluctuations of \|Yn\|2 are approximately Gaussian with the order 1/n. We apply this thin shell property to the study of rotationally invariant random simplices, simplices whose vertices consist of the origin as well as independent random vectors Y1n,…,Ypn distributed according to μn. We show that the logarithmic volume of the resulting simplex exhibits highly Gaussian behavior, providing a generalizing and unifying setting for the objects considered in Grote-Kabluchko-Th\"ale [Limit theorems for random simplices in high dimensions, ALEA, Lat. Am. J. Probab. Math. Stat. 16, 141--177 (2019)]. Finally, by relating the volumes of random simplices to random determinants, we show that if An is an n × n random matrix whose entries are independent standard Gaussian random variables, then there are explicit constants c0,c1∈(0,∞) and an absolute constant C∈(0,∞) such that \[ s ∈ R | P [ det(An) - (n-1)! - c0 12 n + c1 < s ] - ∫-∞s e - u2/2 du 2 π | < C3/2n, \] sharpening the 1/1/3 + o(1)n bound in Nguyen and Vu [Random matrices: Law of the determinant, Ann. Probab. 42 (1) (2014), 146--167].

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