The norm conjecture for entropy of projections of symmetric log-concave vectors

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Let XX be a symmetric log-concave random vector in Rn\mathbb{R}^n. For v∈Rnv\in\mathbb{R}^n, define

NX(v)={eS(⟨v,X⟩)v≠0,0v=0.N_X(v)= \begin{cases} e^{\mathcal{S}(\langle v,X\rangle)} & v\ne 0,\\ 0 & v=0. \end{cases}

The norm conjecture. The function NXN_X defines a norm on Rn\mathbb{R}^n. This would give a geometric formulation of entropy inequalities for one-dimensional projections of symmetric log-concave random vectors. The source does not provide evidence that the conjecture has been resolved.

References

Primary source

Keith Ball, Piotr Nayar and Tomasz Tkocz, “A reverse entropy power inequality for log-concave random vectors”, arXiv:1509.05926 (2015).

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