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October 16, 2025Open Access

Entropy and functional forms of the dimensional Brunn--Minkowski inequality in Gauss space

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This research demonstrates the brunn-minkowski inequality for log-concave random vectors, revealing new insights.

The study shows a new form of the brunn-minkowski inequality for log-concave random vectors, highlighting its significance.
Key insight reveals that Gaussian relative entropy provides a novel perspective on previously established geometric inequalities.
The method employed includes Donsker–Varadhan duality, leading to functional forms of inequalities applicable to log-concave functions.
The findings may enable broader applications of Gaussian inequalities in higher dimensional convex analysis.

Aishwarya et al. (2025) studied this question.

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October 16, 2025Open Access

View Full Paper

Ask AI

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Authors

This research demonstrates the brunn-minkowski inequality for log-concave random vectors, revealing new insights.

The study shows a new form of the brunn-minkowski inequality for log-concave random vectors, highlighting its significance.
Key insight reveals that Gaussian relative entropy provides a novel perspective on previously established geometric inequalities.
The method employed includes Donsker–Varadhan duality, leading to functional forms of inequalities applicable to log-concave functions.
The findings may enable broader applications of Gaussian inequalities in higher dimensional convex analysis.

Aishwarya et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark