ScalingStacks

Remark 5.1 . [00AQ]

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Remark 5.1.

(Semipositivity, convexity, nefness) It is tempting to characterize the semipositivity condition on ‖⋅‖\left\lVert\cdot\right\rVert, in terms of differential conditions on Δ𝒳\Delta_{\mathcal{X}}, just like convex functions are characterised by the positivity of its Hessian matrix. We speculate that semipositivity should imply that for suitable choices of hℒh_{\mathcal{L}} and rIr_{I}, the curvature form −d​dc​log⁡ht1/2-dd^{c}\log h_{t}^{1/2} can be made positive up to small errors. In the t→0t\to 0 limit, the formula (13) then suggests that on each open face Int​(ΔJ)\text{Int}(\Delta_{J}),

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    The Hessian D2​ϕ≥0D^{2}\phi\geq 0, namely ϕ\phi is convex;

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    The gradient satisfies that 𝒟J​(x,‖⋅‖)∈H1,1​(EJ)\mathcal{D}_{J}(x,\left\lVert\cdot\right\rVert)\in H^{1,1}(E_{J}) lies in the nef cone.

Do these two conditions completely characterize semipositive metrics with ϕ=ϕ∘r𝒳\phi=\phi\circ r_{\mathcal{X}}? If yes, it would naturally explain why (15) defines a measure, instead of just a signed measure.

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