The extended Stanley inequality for minimum positions of subsets

From papers

Let P=(X,)P=(X,\prec) be a poset with X=n|X|=n elements. Fix a nonempty subset AXA\subseteq X, and let ff be chosen uniformly from the set of linear extensions of PP. Write fmin(A)=min{f(x):xA}f_{\min}(A)=\min\{f(x):x\in A\}. Extended Stanley inequality. For 2kn12\leq k\leq n-1,

P[fmin(A)=k]2P[fmin(A)=k1]P[fmin(A)=k+1].{\mathbb{P}}[f_{\min}(A)=k]^2\geq {\mathbb{P}}[f_{\min}(A)=k-1]\cdot {\mathbb{P}}[f_{\min}(A)=k+1].

This extends Stanley's log-concavity inequality from the position of a single element to the minimum position attained on an arbitrary nonempty subset. The source presents it as a proposed extension; its resolution is not specified here.

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Sources & referencesView supporting material

Primary source

Swee Hong Chan and Igor Pak, “Correlation inequalities for linear extensions”, arXiv:2211.16637 (2024).

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