Proposition 5.31.2.752BA1321BFA Let $\theta $ be a smooth real $(1,1)$-form, let $\omega $ be a Hermitian form, and let $u\in \mathrm{PSH}(X,\theta )\cap L^\infty (X)$. There are smooth functions $v_ j$ and positive numbers $\varepsilon _ j\downarrow 0$ such that
5.31 Gluing with a small curvature error78243032B1A1
78243032B1A1
The overlap estimate allows local regularizations to be glued by a regularized maximum. Small corrections near the boundary of each chart make the corresponding local branch irrelevant there, while convexity of the regularized maximum preserves a common lower curvature bound. The curvature error is measured by the Hermitian form $\omega $.
For an integer $N\geq 1$, choose independent real random variables $Z_1,\ldots ,Z_ N$ with a common smooth even probability density supported in $[-1,1]$, and define
As a convolution, $M_\tau $ is smooth. It is convex and increasing in every argument, and, with $\mathbf1=(1,\ldots ,1)$, it satisfies
for $t\in \mathbb R^ N$ and $c\in \mathbb R$. If $t_ i<\max _{j\ne i}t_ j-2\tau $, then the $i$-th argument can be removed without changing the value. Moreover, $M_\tau (t)$ is nondecreasing in $\tau $, because it is a convex even function of $\tau $, the distribution of each $Z_ i$ being symmetric.
The second identity expresses invariance under translations. If smooth real functions $f_ i$, $1\leq i\leq N$, satisfy $\mathrm{dd}^{\mathrm{c}}f_ i\geq -\gamma $ for a common smooth real $(1,1)$-form $\gamma $, then
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5.31.1
Indeed, in the chain rule the first partial derivatives of $M_\tau $ are nonnegative and, by the translation identity, sum to one, while the real Hessian of the convex function $M_\tau $ contributes a semipositive $(1,1)$-form.
Proof. For fixed $\epsilon >0$, we first glue the local convolutions of $u$ by a regularized maximum, obtaining smooth functions that decrease to $u$ and have curvature error $2\epsilon \omega $; a diagonal sequence then proves the proposition.
Step 1: local regularizations. Fix $\epsilon >0$. By continuity of $\theta $, we can choose finitely many nested coordinate neighborhoods $V_ i\Subset W_ i\Subset U_ i$, with the $V_ i$ covering $X$, and smooth quadratic functions $r_ i$ such that
To do so, freeze the coefficients of $\theta $ at the center of a chart, add a small positive constant form, and shrink the coordinate neighborhood. Then $p_ i=u+r_ i$ is a bounded plurisubharmonic function on $U_ i$; let $p_{i,\delta }$ be its convolution in the coordinates of $U_ i$.
On an overlap, express both $p_ i$ and $p_ j$ in the coordinates of $U_ j$. Their difference is the smooth function $r_ i-r_ j$, so the difference of their convolutions in these coordinates tends uniformly to $r_ i-r_ j$. By corollary 5.30.3, changing the coordinates in which $p_ i$ is convolved introduces another uniformly vanishing error. Thus, on the intersections of the closures of the $W_ i$,
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5.31.3
Step 2: gluing. Choose functions $\eta _ i\in C^\infty (U_ i,[-1,0])$ that vanish on $V_ i$ and equal $-1$ near the boundary of $W_ i$, and a constant $C\geq 1$ with $\mathrm{dd}^{\mathrm{c}}\eta _ i\geq -C\omega $. The cover, the functions $r_ i,\eta _ i$ and the constant $C$ may depend on $\epsilon $; they are fixed while $\delta $ tends to zero. Set
Each of these functions satisfies $\mathrm{dd}^{\mathrm{c}}f_{i,\delta }\geq -\theta -2\epsilon \omega $. Every boundary point of $W_ i$ lies in some $V_ j$, and there $\eta _ j=0$ while $\eta _ i=-1$. By (5.31.3), for all small $\delta $,
on a neighborhood of that boundary point. Since the cover is finite, this separation holds uniformly.
Let $\tau (\delta )\downarrow 0$ as $\delta \downarrow 0$, with $\tau (\delta )<\epsilon /(8C)$, and define the value at each point as the regularized maximum $M_{\tau (\delta )}$ of the functions $f_{i,\delta }$ for those $i$ with the point in $W_ i$. A branch disappears only near the boundary of its $W_ i$, where it lies below another branch by more than $2\tau $. By the removal property of $M_\tau $, these local formulas therefore define a global smooth function $\psi _{\epsilon ,\delta }$, and (5.31.1) gives
At every point there is a branch with $\eta _ i=0$, and $p_{i,\delta }\geq p_ i$; hence $\psi _{\epsilon ,\delta }\geq u$. For fixed $\epsilon $, the local convolutions decrease with $\delta $, and the regularized maximum decreases when both its arguments and $\tau $ decrease. Its pointwise limit is
Thus $\psi _{\epsilon ,\delta }\downarrow u$ as $\delta \downarrow 0$, and also in $L^1$.
Step 3: a diagonal sequence. Take $\epsilon _ j\downarrow 0$ and put $v_ j=\psi _{\epsilon _ j,\delta _ j}+2^{-j}$, where $\delta _ j$ is chosen so small that
The second requirement can be met because $v_{j-1}\geq u+2^{-j+1}$. Indeed, as $\delta \downarrow 0$, the continuous functions $\psi _{\epsilon _ j,\delta }+2^{-j}-v_{j-1}$ decrease pointwise to a function bounded above by $-2^{-j}$. Their sets of nonnegative values are decreasing compact sets with empty intersection, so one of them is empty. The resulting sequence $(v_ j)$ decreases, converges to $u$ in $L^1$, and stays above $u$. Its pointwise limit is $(\theta +2\epsilon _ k\omega )$-plurisubharmonic for every $k$, hence $\theta $-plurisubharmonic, and it equals $u$ almost everywhere; by lemma 5.24.3, it equals $u$ everywhere. Taking $\varepsilon _ j=2\epsilon _ j$ proves the proposition. $\square$
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