Geometric Large-Deviation-Type Principles for Mixed Measures

Abstract We study a geometric analogue of the large deviation principle for mixed measures associated with a class of $$\log $$ log -concave probability measures whose densities depend on the gauge of a convex body. For convex bodies in $$\mathbb {R}^n$$ R n , we prove a geometric large-deviation-type asymptotic for first-order mixed measures, in which the decay under dilation is governed by a natural inradius associated with the measure. In the planar case, we derive an explicit representation and prove a genuine logarithmic limit for second-order mixed measures. As an application, we prove a comparison theorem showing that asymptotic dominance under dilation forces inclusion between convex bodies.

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Publication Details

Journal
Journal of Geometric Analysis
Published
2026-10-26
DOI
https://doi.org/10.1007/s12220-026-02636-1
Primary Topic
Point processes and geometric inequalities
Type
article
Field-Weighted Citation Impact
0.00

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article

Geometric Large-Deviation-Type Principles for Mixed Measures

Artem Zvavitch, Malak Lafi
1 links
Journal of Geometric Analysis
Point processes and geometric inequalities
article

Geometric Large-Deviation-Type Principles for Mixed Measures

Artem Zvavitch, Malak Lafi
article en

Abstract

Abstract We study a geometric analogue of the large deviation principle for mixed measures associated with a class of $$\log $$ log -concave probability measures whose densities depend on the gauge of a convex body. For convex bodies in $$\mathbb {R}^n$$ R n , we prove a geometric large-deviation-type asymptotic for first-order mixed measures, in which the decay under dilation is governed by a natural inradius associated with the measure. In the planar case, we derive an explicit representation and prove a genuine logarithmic limit for second-order mixed measures. As an application, we prove a comparison theorem showing that asymptotic dominance under dilation forces inclusion between convex bodies.

Journal of Geometric AnalysisVol. 36(12)
Kent State University (US)
National Science Foundation, United States - Israel Binational Science Foundation, United States-Israel Binational Science Foundation, Directorate for Mathematical and Physical Sciences
Openalex Percentile: Top 86%
Point processes and geometric inequalities
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