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4.4 Non-generic region near infinity [023P]

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4.4 Non-generic region near infinity

Next, we need to move up one dimension, and produce some ansatz metric on X=X¯∖D1∪D2X=\bar{X}\setminus D_{1}\cup D_{2} in the region near infinity close to D1∖D2D_{1}\setminus D_{2}, corresponding in the logarithmic coordinate to x1≫|x2|+1x_{1}\gg|x_{2}|+1, including in particular the region with x2=O⁡(1),x1≫1x_{2}=O(1),x_{1}\gg 1. Pick an auxiliary smooth Hermitian metric on X¯\bar{X}, such that the normal vector field to D1⊂X¯D_{1}\subset\bar{X} is tangent to D2D_{2} along Y=D1∩D2Y=D_{1}\cap D_{2}. Then normal geodesic flow identifies a tubular neighbourhood of D1D_{1} with the normal bundle of D1D_{1}, and the error caused by the failure of holomorphicity is exponentially suppressed in the log coordinates. We can thus regard the potential ϕT​Y\phi_{TY} of the Tian-Yau metric on D1∖D2D_{1}\setminus D_{2} as a function on its tubular neighbourhood, via pullback.

To match with the asymptote (29) in the region 1≪x2≪x11\ll x_{2}\ll x_{1}, we are motivated to consider the local ansatz potential near D1∖D2D_{1}\setminus D_{2}

ϕD1=v0​x~1n+2n+a​(d1d2)nn−1​x~1n−2n⁡(n−1)​ϕT​Y+∑k≥2ak​x~1n+2n−k​nn−1​(d1​x2d2)k​nn−1.\phi_{D_{1}}=v_{0}\tilde{x}_{1}^{\frac{n+2}{n}}+a(\frac{d_{1}}{d_{2}})^{\frac{n}{n-1}}\tilde{x}_{1}^{\frac{n-2}{n(n-1)}}\phi_{TY}+\sum_{k\geq 2}a_{k}\tilde{x}_{1}^{\frac{n+2}{n}-\frac{kn}{n-1}}(\frac{d_{1}x_{2}}{d_{2}})^{\frac{kn}{n-1}}. (31)

Here we make a fixed choice of a positive valued smooth function on the Tian-Yau space matching with x2x_{2} outside a compact set, still denoted as x2x_{2}, so that when x2=O⁡(1)x_{2}=O(1) the expression ϕD1\phi_{D_{1}} remains smooth. The convergence of the series is valid for x2≪x1x_{2}\ll x_{1}. Of course, the ad hoc choice means that the ansatz needs to be corrected later by more refined terms.

The local geometry should be imagined as a fibration of Tian-Yau metrics with slowly changing size depending on the logarithmic variable x1x_{1}. Consider x~1\tilde{x}_{1} around a given large value x1′≫1x_{1}^{\prime}\gg 1. The dominant terms in d​dc​ϕD1dd^{c}\phi_{D_{1}} are

ωx1′=a​(d1d2)n/(n−1)​x1′n−2n⁡(n−1)​d​dc​ϕT​Y+2​(n+2)​v0n2​d22​x1′−n−2n​−14​π​d​log⁡ξ′∧d​log⁡ξ′¯.\omega_{x_{1}^{\prime}}=a(\frac{d_{1}}{d_{2}})^{n/(n-1)}x_{1}^{\prime\frac{n-2}{n(n-1)}}dd^{c}\phi_{TY}+\frac{2(n+2)v_{0}}{n^{2}d_{2}^{2}}x_{1}^{\prime-\frac{n-2}{n}}\frac{\sqrt{-1}}{4\pi}d\log\xi^{\prime}\wedge d\overline{\log\xi^{\prime}}. (32)

Up to taking a finite cover (to do with taking fractional powers of ξ′\xi^{\prime}), this model metric describes the product of the Tian-Yau metric with length scale O⁡(ρ)O(\rho) corresponding to the harmonic radius scale, and a cylinder of circle length scale O⁡(x1′2−n2​n)O(x_{1}^{\prime\frac{2-n}{2n}}) corresponding to the injectivity scale.

We can now set up the local Hölder norms in the nongeneric region x2≪x1x_{2}\ll x_{1} (The case of x1≪x2x_{1}\ll x_{2} is completely similar). When x2=O⁡(1),x1≫1x_{2}=O(1),x_{1}\gg 1, we unwind the S1S^{1} factor of the cylinder to pass to the local universal cover. On O⁡(ρ)O(\rho) neighbourhoods, we can use the local product metric (32) to define the local Hölder seminorm and the Ck,αC^{k,\alpha}-norms, as in (26)(27).

The case of 1≪x2≪x11\ll x_{2}\ll x_{1} is already covered by section 4.1. If we had used the local product metric (32) as reference metric, it would lead to an equivalent definition of local Hölder norms up to uniform equivalence. Notice that within O⁡(ρ)O(\rho) neighbourhoods the values of x1,x2x_{1},x_{2} do not vary drastically, so expressions like O⁡(x1α​x2β)O(x_{1}^{\alpha}x_{2}^{\beta}) are not sensitive to the choice of points in the O⁡(ρ)O(\rho) neighbourhood, except when x2=O⁡(1)x_{2}=O(1), in which case we use a slightly abusive convention that O⁡(x2β)O(x_{2}^{\beta}) stands for O⁡(1)O(1) in this region.

We start by observing the derivative bounds of basic functions, which can be read off using the leading order metric ansatz, remembering that the Tian-Yau metric is well approximated by the Calabi ansatz except when x2=O⁡(1)x_{2}=O(1), and that the x1′x_{1}^{\prime}-dependence in ωx1′\omega_{x_{1}^{\prime}} introduces scaling factors.

Lemma 4.7.

In the region {x2≤x1,and ​x1≫1}\{x_{2}\leq x_{1},\text{and }x_{1}\gg 1\},

‖d​x1‖k,α,l​o​c=O⁡(x1n−22​n),‖d​x2‖k,α,l​o​c=O⁡(x1−n−22​n​(n−1)​x2n−22​(n−1)),\left\lVert dx_{1}\right\rVert_{k,\alpha,loc}=O(x_{1}^{\frac{n-2}{2n}}),\quad\left\lVert dx_{2}\right\rVert_{k,\alpha,loc}=O(x_{1}^{-\frac{n-2}{2n(n-1)}}x_{2}^{\frac{n-2}{2(n-1)}}),
d​dc​(x1−d1d2​x2)=0,‖d​dc​x2‖k,α,l​o​c=O⁡(x2−1n−1​x1−n−2n⁡(n−1)).dd^{c}(x_{1}-\frac{d_{1}}{d_{2}}x_{2})=0,\quad\left\lVert dd^{c}x_{2}\right\rVert_{k,\alpha,loc}=O(x_{2}^{-\frac{1}{n-1}}x_{1}^{-\frac{n-2}{n(n-1)}}).
Lemma 4.8.

For x2≪x1x_{2}\ll x_{1}, the Tian-Yau potential satisfies the bound

|ϕT​Y|=O⁡(x2n(n−1)),|d​ϕT​Y|=O⁡(x1−n−22​n​(n−1)​x2n2​(n−1)),|\phi_{TY}|=O(x_{2}^{\frac{n}{(n-1)}}),\quad|d\phi_{TY}|=O(x_{1}^{-\frac{n-2}{2n(n-1)}}x_{2}^{\frac{n}{2(n-1)}}),
‖d​dc​ϕT​Y‖k,α,l​o​c=O⁡(x1−n−2n⁡(n−1)).\left\lVert dd^{c}\phi_{TY}\right\rVert_{k,\alpha,loc}=O(x_{1}^{-\frac{n-2}{n(n-1)}}).

The following lemma quantifies the approximation of the local ansatz potential ϕD1\phi_{D_{1}} by the model product metric:

Lemma 4.9.

(Metric deviation) For x1′≫1x_{1}^{\prime}\gg 1, then in the region with |x1−x1′|≤x1′n−22​(n−1)|x_{1}-x_{1}^{\prime}|\leq x_{1}^{\prime\frac{n-2}{2(n-1)}} and |x2|≪x1′|x_{2}|\ll x_{1}^{\prime}, the metric deviation between d​dc​ϕD1dd^{c}\phi_{D_{1}} and the local product metric (32) satisfies the local Ck,αC^{k,\alpha} estimate on O⁡(ρ)O(\rho) neighbourhoods around a given point:

‖d​dc​ϕD1−ωx1′‖k,α,l​o​c=O⁡((x2x1)n2​(n−1))\left\lVert dd^{c}\phi_{D_{1}}-\omega_{x_{1}^{\prime}}\right\rVert_{k,\alpha,loc}=O((\frac{x_{2}}{x_{1}})^{\frac{n}{2(n-1)}})
Proof.

We will ignore all exponentially small errors coming from identifying tubular neighbourhoods with normal bundles. We compute d​dc​ϕD1dd^{c}\phi_{D_{1}} by the Leibniz rule:

d​dc​x~1n+2n=2​(n+2)n2​x~1n+2n−2​−14​π​d22​d​log⁡ξ′∧d​log⁡ξ′¯,dd^{c}\tilde{x}_{1}^{\frac{n+2}{n}}=\frac{2(n+2)}{n^{2}}\tilde{x}_{1}^{\frac{n+2}{n}-2}\frac{\sqrt{-1}}{4\pi d_{2}^{2}}d\log\xi^{\prime}\wedge d\overline{\log\xi^{\prime}},
d​dc​(x~1n−2n⁡(n−1)​ϕT​Y)=n−2n⁡(n−1)​(n−2n⁡(n−1)−1)​x~1n−2n⁡(n−1)−2​ϕT​Y​−14​π​d22​d​log⁡ξ′∧d​log⁡ξ′¯+n−2n⁡(n−1)​x~1n−2n⁡(n−1)−1​(d​x~1∧dc​ϕT​Y+d​ϕT​Y∧dc​x~1)+x~1n−2n⁡(n−1)​d​dc​ϕT​Y.\begin{split}&dd^{c}(\tilde{x}_{1}^{\frac{n-2}{n(n-1)}}\phi_{TY})=\frac{n-2}{n(n-1)}(\frac{n-2}{n(n-1)}-1)\tilde{x}_{1}^{\frac{n-2}{n(n-1)}-2}\phi_{TY}\frac{\sqrt{-1}}{4\pi d_{2}^{2}}d\log\xi^{\prime}\wedge d\overline{\log\xi^{\prime}}\\ &+\frac{n-2}{n(n-1)}\tilde{x}_{1}^{\frac{n-2}{n(n-1)}-1}(d\tilde{x}_{1}\wedge d^{c}\phi_{TY}+d\phi_{TY}\wedge d^{c}\tilde{x}_{1})+\tilde{x}_{1}^{\frac{n-2}{n(n-1)}}dd^{c}\phi_{TY}.\end{split}

and similarly with d​dc​(x~1n+2n−k​nn−1​x2k​nn−1)dd^{c}(\tilde{x}_{1}^{\frac{n+2}{n}-\frac{kn}{n-1}}x_{2}^{\frac{kn}{n-1}}).

Comparing v0​d​dc​x~1n+2nv_{0}dd^{c}\tilde{x}_{1}^{\frac{n+2}{n}} and the term 2​(n+2)​v0n2​d22​x1′−n−2n​−14​π​d​log⁡ξ′∧d​log⁡ξ′¯\frac{2(n+2)v_{0}}{n^{2}d_{2}^{2}}x_{1}^{\prime-\frac{n-2}{n}}\frac{\sqrt{-1}}{4\pi}d\log\xi^{\prime}\wedge d\overline{\log\xi^{\prime}}, the deviation is of order O⁡(|x2|+|x1−x1′|x1′)O(\frac{|x_{2}|+|x_{1}-x_{1}^{\prime}|}{x_{1}^{\prime}}). Notice for n≥3n\geq 3, we have n2​(n−1)<1\frac{n}{2(n-1)}<1 and so |x2|x1′≤(x2x1)n2​(n−1)\frac{|x_{2}|}{x_{1}^{\prime}}\leq\left(\frac{x_{2}}{x_{1}}\right)^{\frac{n}{2(n-1)}}. For |x1−x1′|≤x1′n−22​(n−1)|x_{1}-x_{1}^{\prime}|\leq x_{1}^{\prime\frac{n-2}{2(n-1)}}, the error O⁡(|x1−x1′|x1′)=O⁡(x1−n2​(n−1))O(\frac{|x_{1}-x_{1}^{\prime}|}{x_{1}^{\prime}})=O(x_{1}^{-\frac{n}{2(n-1)}}), which is absorbed into O⁡((x2x1)n2​(n−1))O((\frac{x_{2}}{x_{1}})^{\frac{n}{2(n-1)}}).

Using the lemmas, we can estimate the terms appearing in d​dc​(x~1n−2n⁡(n−1)​ϕT​Y)dd^{c}(\tilde{x}_{1}^{\frac{n-2}{n(n-1)}}\phi_{TY}) in the local Ck,αC^{k,\alpha}-norms:

‖ϕT​Y​x1n−2n⁡(n−1)−2​d​log⁡ξ′∧d​log⁡ξ′¯‖k,α,l​o​c=O⁡(x2n(n−1)​x1n−2n⁡(n−1)−2​x1n−2n)=O⁡((x2x1)nn−1).\left\lVert\phi_{TY}x_{1}^{\frac{n-2}{n(n-1)}-2}d\log\xi^{\prime}\wedge d\overline{\log\xi^{\prime}}\right\rVert_{k,\alpha,loc}=O(x_{2}^{\frac{n}{(n-1)}}x_{1}^{\frac{n-2}{n(n-1)}-2}x_{1}^{\frac{n-2}{n}})=O((\frac{x_{2}}{x_{1}})^{\frac{n}{n-1}}).

The cross terms have order

‖x1n−2n⁡(n−1)−1​d​log⁡ξ′∧dc​ϕT​Y‖k,α,l​o​c=O⁡(x1n−2n⁡(n−1)−1​x1n−22​n​x1−n−22​n​(n−1)​x2n2​(n−1))=O⁡((x2x1)n2​(n−1)).\left\lVert x_{1}^{\frac{n-2}{n(n-1)}-1}d\log\xi^{\prime}\wedge d^{c}\phi_{TY}\right\rVert_{k,\alpha,loc}=O(x_{1}^{\frac{n-2}{n(n-1)}-1}x_{1}^{\frac{n-2}{2n}}x_{1}^{-\frac{n-2}{2n(n-1)}}x_{2}^{\frac{n}{2(n-1)}})=O((\frac{x_{2}}{x_{1}})^{\frac{n}{2(n-1)}}).

So does its complex conjugate. The last error comes from the deviation between x~1n−2n⁡(n−1)​d​dc​ϕT​Y\tilde{x}_{1}^{\frac{n-2}{n(n-1)}}dd^{c}\phi_{TY} from x1′n−2n⁡(n−1)​d​dc​ϕT​Yx_{1}^{\prime\frac{n-2}{n(n-1)}}dd^{c}\phi_{TY}. This error is again of order O⁡(|x2|+|x1−x1′|x1′)O(\frac{|x_{2}|+|x_{1}-x_{1}^{\prime}|}{x_{1}^{\prime}}).

The remainder terms have leading order contribution d​dc​(x~1n+2n−2​nn−1​x22​nn−1).dd^{c}(\tilde{x}_{1}^{\frac{n+2}{n}-\frac{2n}{n-1}}x_{2}^{\frac{2n}{n-1}}). Its main contribution is x~1n+2n−2​nn−1​d​dc​x22​nn−1\tilde{x}_{1}^{\frac{n+2}{n}-\frac{2n}{n-1}}dd^{c}x_{2}^{\frac{2n}{n-1}}, which has magnitude O⁡((x2x1)nn−1)O((\frac{x_{2}}{x_{1}})^{\frac{n}{n-1}}). Combining all the errors, the deviation between d​dc​ϕD1dd^{c}\phi_{D_{1}} and the local product metric (32) has magnitude bounded by O⁡((x2x1)n2​(n−1)).O((\frac{x_{2}}{x_{1}})^{\frac{n}{2(n-1)}}). ∎

Lemma 4.10.

(Volume form error) In the region with x1≫1x_{1}\gg 1 and x2≪x1x_{2}\ll x_{1},

‖(d​dc​ϕD1)n−K0​−1n2​Ω∧Ω¯‖k,α,l​o​c=O⁡(x1−n(n−1)​e−c​x21/2).\left\lVert(dd^{c}\phi_{D_{1}})^{n}-K_{0}\sqrt{-1}^{n^{2}}\Omega\wedge\overline{\Omega}\right\rVert_{k,\alpha,loc}=O(x_{1}^{-\frac{n}{(n-1)}}e^{-cx_{2}^{1/2}}).
Proof.

The volume form error will be smaller than the metric deviation due to extra cancellation effects. Recall the computation of d​dc​ϕD1dd^{c}\phi_{D_{1}} from Lemma 4.9 above. Notice (d​dc​ϕD1)n(dd^{c}\phi_{D_{1}})^{n} is a volume form, so must take one d​log⁡ξ′d\log\xi^{\prime} and d​log⁡ξ′¯d\overline{\log\xi^{\prime}} from either a pair of cross derivative terms, or from a factor d​dc​x~1n+2n−k​nn−1dd^{c}\tilde{x}_{1}^{\frac{n+2}{n}-\frac{kn}{n-1}} for k≥0k\geq 0. The differentiation of ϕT​Y\phi_{TY} and the powers of x2x_{2} would only produce factors on D1∖D2D_{1}\setminus D_{2} without x~1\tilde{x}_{1} dependence. By thinking about all the possible ways to take wedge products contributing to (d​dc​ϕD1)n(dd^{c}\phi_{D_{1}})^{n}, we get an absolutely convergent series within x2≪x1x_{2}\ll x_{1}:

(d​dc​ϕD1)n≈∑k≥0x~1−k​nn−1​−1​d​log⁡ξ′∧d​log⁡ξ′¯∧ℐk,(dd^{c}\phi_{D_{1}})^{n}\approx\sum_{k\geq 0}\tilde{x}_{1}^{-\frac{kn}{n-1}}\sqrt{-1}d\log\xi^{\prime}\wedge d\overline{\log\xi^{\prime}}\wedge\mathcal{I}_{k}, (33)

where the coefficients ℐk\mathcal{I}_{k} are top degree forms on the D1∖D2D_{1}\setminus D_{2} factor, without x~1\tilde{x}_{1} dependence. Here we write ≈\approx as a reminder that we have ignored the exponentially small errors from identifying the tubular neighbourhood with the normal bundles of D1∖D2D_{1}\setminus D_{2}, which is holomorphically trivial up to finite cover.

We now identify the leading term d​log⁡ξ′∧d​log⁡ξ′¯∧ℐ0d\log\xi^{\prime}\wedge d\overline{\log\xi^{\prime}}\wedge\mathcal{I}_{0}. By thinking about form types, this comes from the binomial expansion term

n​v0​d​dc​x~1n+2n∧(a​(d1d2)nn−1​x~1n−2n⁡(n−1)​d​dc​ϕT​Y)n−1,nv_{0}dd^{c}\tilde{x}_{1}^{\frac{n+2}{n}}\wedge\left(a(\frac{d_{1}}{d_{2}})^{\frac{n}{n-1}}\tilde{x}_{1}^{\frac{n-2}{n(n-1)}}dd^{c}\phi_{TY}\right)^{n-1},

which is

2​(n+2)​v0n​d22​−14​π​d​log⁡ξ′∧d​log⁡ξ′¯∧an−1​(d1d2)n​(d​dc​ϕT​Y)n−1.\frac{2(n+2)v_{0}}{nd_{2}^{2}}\frac{\sqrt{-1}}{4\pi}d\log\xi^{\prime}\wedge d\overline{\log\xi^{\prime}}\wedge a^{n-1}(\frac{d_{1}}{d_{2}})^{n}(dd^{c}\phi_{TY})^{n-1}.

From the explicit formula (24) for v0,av_{0},a,

v0​an−1=(nn+2)3,v_{0}a^{n-1}=(\frac{n}{n+2})^{3},

and recalling the complex Monge-Ampère equation for the Tian-Yau metric in Theorem 4.2, the above simplifies to

2​n2​∫Yc1​(L0)n−2(n+2)2​d22​(d1d2)n​d2n−2​−14​π​d​log⁡ξ′∧d​log⁡ξ′¯∧−1(n−1)2​ΩD1∧Ω¯D1.\frac{2n^{2}\int_{Y}c_{1}(L_{0})^{n-2}}{(n+2)^{2}d_{2}^{2}}(\frac{d_{1}}{d_{2}})^{n}d_{2}^{n-2}\frac{\sqrt{-1}}{4\pi}d\log\xi^{\prime}\wedge d\overline{\log\xi^{\prime}}\wedge\sqrt{-1}^{(n-1)^{2}}\Omega_{D_{1}}\wedge\overline{\Omega}_{D_{1}}.

Up to exponentially small errors from complex structure identifications, in terms of the local defining functions ξ1,ξ2\xi_{1},\xi_{2} for D1,D2D_{1},D_{2},

ΩD1≈d​log​ξ2∧ΩY,log⁡ξ′≈d2​log​ξ1−d1​log​ξ2,Ω≈d​log​ξ1∧d​log​ξ2∧ΩY,\Omega_{D_{1}}\approx d\log\xi_{2}\wedge\Omega_{Y},\quad\log\xi^{\prime}\approx d_{2}\log\xi_{1}-d_{1}\log\xi_{2},\quad\Omega\approx d\log\xi_{1}\wedge d\log\xi_{2}\wedge\Omega_{Y},

and the above reduce to K0​−1n2​Ω∧Ω¯,K_{0}\sqrt{-1}^{n^{2}}\Omega\wedge\overline{\Omega}, for the constant K0K_{0} in (28). In short, the leading term cancels with K0​−1n2​Ω∧Ω¯K_{0}\sqrt{-1}^{n^{2}}\Omega\wedge\overline{\Omega}.

The subleading terms are suppressed by the factor x~1−nn−1\tilde{x}_{1}^{-\frac{n}{n-1}}, and the fast convergence of the power series means we only need to consider ℐ1\mathcal{I}_{1}. In the Tian-Yau core region x2=O⁡(1)x_{2}=O(1), the crude information is that d​log⁡ξ′∧d​log⁡ξ′¯∧ℐ1d\log\xi^{\prime}\wedge d\overline{\log\xi^{\prime}}\wedge\mathcal{I}_{1} has local Ck,αC^{k,\alpha} norm O⁡(1)O(1). This explains the O⁡(x1−nn−1)O(x_{1}^{-\frac{n}{n-1}}) decay in the x2=O⁡(1)x_{2}=O(1) subregion.

For 1≪x2≪x11\ll x_{2}\ll x_{1}, the deviation between the Tian-Yau potential ϕT​Y\phi_{TY} and the Calabi ansatz potential is O⁡(e−c​x21/2)O(e^{-cx_{2}^{1/2}}), namely O⁡(e−c​rD1n−1n)O(e^{-cr_{D_{1}}^{\frac{n-1}{n}}}) (for some changing constant c>0c>0). After replacing ϕT​Y\phi_{TY} by n−1n​x2nn−1\frac{n-1}{n}x_{2}^{\frac{n}{n-1}}, we recover the potential uu in the generic region. Ignoring exponentially small complex structure errors as usual, then uu is by construction a solution to the complex Monge-Ampère equation. This explains the exponential decay ℐk=O⁡(e−c​x21/2)\mathcal{I}_{k}=O(e^{-cx_{2}^{1/2}}) for k≥1k\geq 1. ∎

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