ScalingStacks

5. A variational approach [01D7]

Original official author HTML, exact retained edition. Historical TeX conversion verdicts remain unchanged. Cited-edition alignment and mathematical self-containment are not assessed.

Complete original source context · Original author HTML

5. A variational approach

We shall present a unified approach to solving the complex and non-Archimedean Monge-Ampère equations in any dimension. The method goes back to Alexandrov’s work in convex geometry [Ale38]. It was adapted to the complex case in [BBGZ13] and to the non-Archimedean analogue in [BFJ15].

The general strategy is to construct an energy functional

E:PSH0⁡(Lan)→𝐑E:\operatorname{PSH}^{0}({L^{\mathrm{an}}})\to{\mathbf{R}}

whose derivative is the Monge-Ampère operator, E′=MAE^{\prime}=\operatorname{MA}, in the sense that

dd​t​E​(ϕ+t​f)|t=0=∫Xanf​MA⁡(ϕ),\frac{d}{dt}E(\phi+tf)|_{t=0}=\int_{{X^{\mathrm{an}}}}f\operatorname{MA}(\phi),

for every continuous semipositive metric ϕ∈PSH0⁡(Lan)\phi\in\operatorname{PSH}^{0}({L^{\mathrm{an}}}) and every smooth/model function ff on Xan{X^{\mathrm{an}}}.

Grant the existence of this functional for the moment. Given a measure μ\mu on Xan{X^{\mathrm{an}}}, consider the functional Fμ:PSH0⁡(Lan)→𝐑F_{\mu}:\operatorname{PSH}^{0}({L^{\mathrm{an}}})\to{\mathbf{R}} defined by

Fμ​(ϕ)=E⁡(ϕ)−∫ϕ​μ.\ F_{\mu}(\phi)=E(\phi)-\int\phi\,\mu.

Suppose we can find ϕ∈PSH0⁡(Lan)\phi\in\operatorname{PSH}^{0}({L^{\mathrm{an}}}) that maximizes FμF_{\mu}. Since the derivative of FμF_{\mu} is equal to Fμ′=MA−μF_{\mu}^{\prime}=\operatorname{MA}-\mu, we then have 0=Fμ′​(ϕ)=MA⁡(ϕ)−μ0=F_{\mu}^{\prime}(\phi)=\operatorname{MA}(\phi)-\mu as required.

Now, there are at least three problems with this approach:

  • (1)

    There is a priori no reason why a maximizer should exist in PSH0⁡(Lan)\operatorname{PSH}^{0}({L^{\mathrm{an}}}). We resolve this by introducing a larger space PSH⁡(Lan)\operatorname{PSH}({L^{\mathrm{an}}}) with suitable compactness properties and find a maximizer there.

  • (2)

    Granted the existence of a maximizer ϕ∈PSH⁡(Lan)\phi\in\operatorname{PSH}({L^{\mathrm{an}}}), we are maximizing over a convex set rather than a vector space, so there is no reason why Fμ′​(ϕ)=0F_{\mu}^{\prime}(\phi)=0. Compare maximizing the function f⁡(x)=x2f(x)=x^{2} on the real interval [−1,1][-1,1]: the maximum is not at a critical point.

  • (3)

    In the end we want to show that—after all—the maximizer is continuous, that is, ϕ∈C0​(Lan)\phi\in C^{0}({L^{\mathrm{an}}}).

We shall discuss how to address (1) and (2) in the next two sections. The continuity result in (3) requires a priori capacity estimates due to Kołodziej, and will not be discussed in these notes.

Original mathematics by the credited authors. Source-backed reader collection; mathematical self-containment is not assessed.