# The variance of the $\ell_p^n$-norm of the Gaussian vector, and Dvoretzky's theorem

## TL;DR

This paper provides a complete characterization of the variance of the $ ext{l}_p^n$-norm of Gaussian vectors for all $p$, revealing two transition points and implications for Dvoretzky's theorem.

## Contribution

It fully determines the variance of the $ ext{l}_p^n$-norm of Gaussian vectors across all $p$, including the logarithmic regime, and identifies two key transition points.

## Key findings

- Variance behavior changes at two transition points in $p$.
- Complete characterization of variance for all $p$ in relation to Gaussian vectors.
- Implications for random Dvoretzky's theorem in $ ext{l}_p^n$ spaces.

## Abstract

Let $n$ be a large integer, and let $G$ be the standard Gaussian vector in $R^n$. Paouris, Valettas and Zinn (2015) showed that for all $p\in[1,c\log n]$, the variance of the $\ell_p^n$--norm of $G$ is equivalent, up to a constant multiple, to $\frac{2^p}{p}n^{2/p-1}$, and for $p\in[C\log n,\infty]$, $\mathbb{Var}\|G\|_p\simeq (\log n)^{-1}$. Here, $C,c>0$ are universal constants. That result left open the question of estimating the variance for $p$ logarithmic in $n$. In this note, we resolve the question by providing a complete characterization of $\mathbb{Var}\|G\|_p$ for all $p$. We show that there exist two transition points (windows) in which behavior of $\mathbb{Var}\|G\|_p$, viewed as a function of $p$, significantly changes. We also discuss some implications of our result in context of random Dvoretzky's theorem for $\ell_p^n$.