arXiv · 1508.04039
The sum of squared logarithms inequality in arbitrary dimensions
Abstract
We prove the \emph{sum of squared logarithms inequality} (SSLI) which states that for nonnegative vectors $x, y \in \mathbb{R}^n$ whose elementary symmetric polynomials satisfy $e_k(x)\le e_k(y)$ (for $1\le k < n$) and $e_n(x)=e_n(y)$, the inequality $\sum_i (\log x_i)^2 \le \sum_i (\log y_i)^2$ holds. Our proof of this inequality follows by a suitable extension to the complex plane. In particular, we show that the function $f\colon M\subseteq \mathbb{C}^n\to \mathbb{R}$ with $f(z)=\sum_i(\log z_i)^2$ has nonnegative partial derivatives with respect to the elementary symmetric polynomials of $z$. This property leads to our proof. We conclude by providing applications and wider connections of the SSLI.
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Lev Borisov, Patrizio Neff, Suvrit Sra, Christian Thiel. 2015-08-17. The sum of squared logarithms inequality in arbitrary dimensions. https://arxiv.org/abs/1508.04039
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