Schneider's support conjecture for mixed Hessian measures

Fix an open convex set ΩRn\Omega\subseteq\mathbb{R}^n, and let Conv(Ω)\operatorname{Conv}(\Omega) be the set of proper convex functions ff on Rn\mathbb{R}^n with Ωdomf\Omega\subseteq\mathop{\mathrm{dom}} f. For fConv(Ω)f\in\operatorname{Conv}(\Omega) and xΩx\in\Omega, let L(f,x)L(f,x) be the largest convex subset of Ω\Omega on which ff is affine and that has xx in its relative interior, and set Lˉ(f,x)=span{L(f,x)x}\bar L(f,x)=\operatorname{span}\{L(f,x)-x\}. A point xΩx\in\Omega is (f1,,fn)(f_1,\ldots,f_n)-extreme if

dim(Lˉ(fI,x))I\dim\big(\bar L(f_I,x)^\perp\big)\geq |I|

for every I[n]I\subseteq[n].

Schneider's conjecture. For f1,,fnConv(Ω)f_1,\ldots,f_n\in\operatorname{Conv}(\Omega), the mixed Hessian measure satisfies

suppHf1,,fn=cl{xΩ:x is (f1,,fn)-extreme}.\mathop{\mathrm{supp}} \mathrm{H}_{f_1,\ldots,f_n}=\mathop{\mathrm{cl}}\big\{x\in\Omega:x\text{ is }(f_1,\ldots,f_n)\text{-extreme}\big\}.

This is the convex-function analogue of Schneider's conjectural support characterization for mixed area measures. The source presents it as a transcription of that conjecture, and no resolution is supplied.

Sources & referencesView supporting material

Primary source

Ramon van Handel and Shouda Wang, “On Minkowski's monotonicity problem”, arXiv:2507.20082 (2025).

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