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arXiv 2610.13596math.FAmath.PR
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具有不同协方差矩阵的高斯不等式——异方差高斯Brunn-Minkowski不等式

Gaussian inequalities with different covariance matrices - the Heterovariant Gaussian Brunn-Minkowski inequality

Technion-Israel Institute of Technology(以色列理工学院);University of Birmingham(伯明翰大学);Institute of Science Tokyo(东京科学大学)

Emanuel Milman, Shohei Nakamura, Hiroshi Tsuji

AI总结:

本文建立涉及不同协方差矩阵的异方差高斯Brunn-Minkowski不等式,融合两类已有高斯不等式,推导双线性版本及高斯混合相关不等式,证明基于前期的高斯正反Brascamp-Lieb不等式。

摘要:

我们针对原点对称凸集 $K,L \subset \mathbb{R}^n$ 以及 $p,\lambda \in (0,1)$,建立了如下新颖的异方差高斯Brunn-Minkowski不等式(涉及一般协方差矩阵 $\Sigma_1,\Sigma_2,\Gamma$):当 $\Gamma \leq \Sigma_1 \sharp_p \Sigma_2$(即 $\Sigma_1,\Sigma_2$ 的 $p$-几何均值)时,有 $\gamma_{\Sigma_1}(K)^{1-p} \gamma_{\Sigma_2}(L)^p \le \left( \left( \frac{1-p}{1-\lambda} \right)^{1-p} \left( \frac{p}{\lambda} \right)^p \right)^{n} \gamma_{\Gamma}((1-\lambda) K + \lambda L)$。该不等式可直接推导出Eskenazis-Moschidis的维度高斯Brunn-Minkowski不等式(通过取 $\Sigma_1 = \Sigma_2 = \Gamma$ 并对 $p$ 优化)以及Cordero-Erausquin-Fradelizi-Maurey的强高斯(B)-定理(通过取 $K=L$、$p=\lambda$ 且协方差为对角矩阵),将二者融合为一个统一表述。实际上,该不等式适用于高斯重心在原点的凸集,还揭示了强高斯(B)-定理的新双线性版本(涉及两个凸集);特别地,对所有 $a,b > 0$ 和 $\lambda \in [0,1]$,有 $\gamma(a K)^{1-\lambda} \gamma(b L)^{\lambda} \leq \gamma \left ( a^{1-\lambda} b^\lambda \left ((1-\lambda) K + \lambda L \right) \right )$。更一般的异方差双线性(B)-定理版本将伸缩替换为一般线性变换,另一版本则得到近期建立的高斯共轭Rogers-Shephard不等式的异方差形式。通过对协方差矩阵取平均,我们得到高斯混合的维度Brunn-Minkowski和共轭Rogers-Shephard不等式。证明基于我们前期工作中建立的高斯正反Brascamp-Lieb不等式。

英文摘要:

We establish the following novel heterovariant Gaussian Brunn-Minkowski inequality (involving general covariance matrices $Σ_1,Σ_2,Γ$) for origin-symmetric convex sets $K,L \subset \mathbb{R}^n$ and $p,λ\in (0,1)$: \[ γ_{Σ_1}(K)^{1-p} γ_{Σ_2}(L)^p \le \left( \left( \frac{1-p}{1-λ} \right)^{1-p} \left( \frac{p}λ \right)^p \right)^{n} γ_Γ((1-λ) K + λL) , \] whenever $Γ\leq Σ_1 \sharp_p Σ_2$, the $p$-geometric mean of $Σ_1,Σ_2$. This immediately implies both the dimensional Gaussian Brunn-Minkowski inequality of Eskenazis-Moschidis (by using $Σ_1 = Σ_2 = Γ$ and optimizing over $p$) and the strong Gaussian (B)-theorem of Cordero-Erausquin-Fradelizi-Maurey (by using $K=L$, $p=λ$ and diagonal covariances), fusing them into a single unified statement. In fact, the inequality applies to convex sets whose appropriate Gaussian barycenter is at the origin. Furthermore, it reveals a new *bilinear* version of the strong Gaussian (B)-theorem (involving *two* convex sets); in particular, for all $a,b > 0$ and $λ\in [0,1]$: \[ γ(a K)^{1-λ} γ(b L)^λ \leq γ\left ( a^{1-λ} b^λ\left ((1-λ) K + λL \right) \right ) . \] A more general heterovariant version of the (bilinear) (B)-theorem replaces dilation by general linear transformations. A different version yields a heterovariant form of the recently established Gaussian conjugate Rogers-Shephard inequality. By averaging these Gaussian inequalities with respect to the covariance matrices, we obtain dimensional Brunn-Minkowski and conjugate Rogers-Shephard inequalities for Gaussian mixtures. The proofs are based on the Gaussian Forward-Reverse Brascamp-Lieb inequality established in our previous work.

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