Concavity conjecture for entropy along normalized sums of log-concave variables

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Let XX and YY be independent copies of a log-concave random variable, and let λ∈[0,1]\lambda\in[0,1]. Define

f(λ)=S(λX+1−λY).f(\lambda)=\mathcal{S}(\sqrt{\lambda}X+\sqrt{1-\lambda}Y).

Concavity conjecture. The function ff is concave on [0,1][0,1]. This conjecture proposes a stronger form of regularity for entropy under normalized sums of independent identically distributed log-concave variables. The source gives no evidence of resolution.

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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