Regularity for convex viscosity solutions of Lagrangian mean curvature equation
Abstract.
We show that convex viscosity solutions of the Lagrangian mean curvature equation are regular if the Lagrangian phase has Hölder continuous second derivatives.
1. Introduction
We establish regularity for convex viscosity solutions of the Lagrangian mean curvature equation
(1.1) |
under the assumption that is in for some . Here ’s are the eigenvalues of the Hessian matrix and then the phase becomes a potential for the mean curvature of the Lagrangian submanifold . The induced Riemannian metric can be written as or
In [HL82, (2.19)], the mean curvature vector of this Lagrangian submanifold was shown to be
(1.2) |
where is the gradient operator for the metric and is the complex structure, or the rotation matrix in . Note that by our assumption on , is bounded.
When the phase is constant, denoted by , solves the special Lagrangian equation
(1.3) |
or equivalently,
Equation (1.3) originates in the special Lagrangian geometry of Harvey- Lawson [HL82]. The Lagrangian graph is called special when the argument of the complex number or the phase is constant, and it is special if and only if is a (volume minimizing) minimal surface in [HL82].
A dual form of (1.3) is the Monge-Ampère equation
(1.4) |
This is the potential equation for special Lagrangian submanifolds in as introduced in [Hit97]. The gradient graph is volume maximizing in this pseudo-Euclidean space, as shown by Warren [War10]. In the 1980s, Mealy [Mea89] showed that an equivalent algebraic form of the above equation is the potential equation for his volume maximizing special Lagrangian submanifolds in .
The regularity of solutions is a fundamental problem for these geometrically and analytically significant equations. Our main results are the following:
Theorem 1.1.
Let be a convex viscosity solution of (1.1) on , where . Then .
We use the above regularity to prove the following interior estimate.
Theorem 1.2.
Let be a convex solution of (1.1) on , where . Then satisfies the following Hessian estimate
(1.5) |
We state the following application of our result.
Application. Lagrangian mean curvature flow:
We specialize to . In this case, the gradient graph corresponds to a translating soliton for Lagrangian mean curvature flow. Indeed, if solves the potential equation
then the gradient graph solves the Lagrangian mean curvature equation
where is the mean curvature, and is the projection onto the normal space of ; see [CCH12, pg 203]. Now let solve (1.1) for . Then , so is a translating soliton with “constant” mean curvature . We conclude that translating Lagrangian solitons with convex potentials and “vertical” speeds are smooth. Local a priori estimates for convex solutions to Lagrangian mean curvature flow were found in [NY11].
The convexity of the special Lagrangian equation plays a dominant role in its regularity theory. The arctangent operator is concave if is convex, or if the Hessian has a lower bound . Bao and Chen [BC03] showed regularity for convex strong solutions. For smooth convex solutions of (1.3), Hessian estimates have been obtained by Chen-Warren-Yuan [CWY09]. Recently in [CSY19], Chen-Shankar-Yuan confirmed that convex viscosity solutions of (1.3) are smooth. The semiconvex singular solutions constructed by Wang-Yuan [WY13] show that the convexity condition is necessary. Similarly, if in (1.3) we have critical phase or supercritical phase , then has convex level sets, but it was shown by Yuan [Yua06] that this fails for subcritical phases . For critical and supercritical phases, Hessian estimates for (1.3) have been obtained by Warren-Yuan [WY09, WY10] and Wang-Yuan [WY14], see also [Li19]. For subcritical phases, solutions of (1.3) were constructed by Nadirashvili-Vlăduţ [NV10] and Wang-Yuan [WY13]. Hessian lower bounds also play a role in the dual equation (1.4). The Monge-Ampére type equation has Pogorelov-type singular convex viscosity solutions whose graphs contain a line. However, under the necessary strict convexity assumption , interior regularity was obtained by Pogorelov [Pog78] for a smooth enough right hand side , by Urbas [Urb88] if is Lipschitz and , and by Caffarelli [Caf90] if is merely Hölder.
The convexity of creates its own challenges in proving regularity, since it is unstable under smooth approximations of the boundary value. To use the method of a priori estimates, one would solve the Dirichlet problem for a modified concave equation , where for and for . If we approximate the boundary data and find the smooth solution of this problem, it may no longer be convex, and therefore lacks a connection to the original problem. Although a priori estimates are available for (1.1) and (1.3), estimates for are unknown.
In showing regularity for convex solutions of (1.3), the authors of [CSY19] managed to avoid a priori estimates altogether. The basic idea was to change variables using the Lewy-Yuan rotation of the gradient graph, , such that the Hessian bounds decreased from to . Since minimal graphical tangent cones with such bounds are flat, they were able to deduce regularity in new coordinates using ideas from [Yua01]. One problem, however, is that defining such a rotation is unclear if convex is not . To adapt to the lower regularity setting, it was shown in [CSY19] that in the smooth case, can be constructed using the Legendre transform, which is still well defined in the Lipschitz case.
Extending the constant phase (1.3) results to variable phases (1.1) is subtle, and not always possible. Interior regularity for solutions of (1.1) with a supercritical and critical phase were recently obtained in [Bha21, Bha22, BMS22], but singular solutions are known if has Hölder regularity [Bha21, Remark 1.3]. In fact, these singular solutions are convex, so Theorem 1.1 is not valid unless is sufficiently smooth. Moreover, in our companion paper [BS20], we exhibit convex singular solutions which solve an equation with depending also on the gradient. In such cases, is smooth in both arguments. Convex singular solutions do not exist for analogous uniformly elliptic PDEs . The non-uniform ellipticity of the arctangent operator in (1.3) makes the PDE highly sensitive to the structure of the variable phase. Nevertheless, the results of this paper show that no conditions on are needed for regularity of convex viscosity solutions, apart from some smoothness such as .
In proving Theorem 1.1, the treatment of the variable phase is delicate, and the technique does not always work. The key step to deduce regularity, or , is to show that in rotated coordinates, never saturates its upper bound of . For constant phases, this is done using the strong maximum principle for -subharmonic . For variable phases, subharmonicity only holds up to extra terms, such as . If is convex, then subharmonicity is restored, but Theorem 1.1 does not assume any conditions on other than smoothness. To handle these terms, we carefully account for the coordinate change, and relate to , for example. It turns out that the resulting expression vanishes when saturates its upper bound, restoring the maximum principle. To understand how this could happen, observe that for a convex singular solution, the forward map has large Jacobian matrix in the directions. It follows that the inverse map has small Jacobian in those directions, so the rotated phase will inherit this flatness.
This paper is divided into the following sections. In section 2, we formulate the Lewy-Yuan rotation for the Lipschitz potential . In section 3, we establish regularity of the rotated potential . In section 4, we deduce regularity of the original potential , thereby proving Theorem 1.1. In section 5, we prove the Hessian estimate (1.5).
Acknowledgments. The authors are grateful to Yu Yuan for his guidance, support, and helpful discussions. The authors thank D. H. Phong for helpful comments and suggestions. AB acknowledges the support of the AMS-Simons Travel Grant. RS was partially supported by the NSF Graduate Research Fellowship Program under grant No. DGE-1762114. The authors thank the anonymous referee for the referee’s thorough feedback.
2. Rotation for Lipschitz potential
We formulate Lewy-Yuan rotation for the convex function solving (1.1), using the idea introduced in [CSY19]; we refer to sections 2.1 and 2.2 in that paper for various details in this section. If is smooth on , then the gradient graph is a Lagrangian submanifold of , and if is convex, then the downward rotation yields another Lagrangian submanifold with smooth potential on . Because the canonical angles decrease by an angle of
it follows that the rotation sends solutions of (1.1) to solutions of another Lagrangian mean curvature equation, which now is uniformly elliptic by the Hessian bounds
(2.1) |
This makes regularity theory tractable in new coordinates using the ideas developed in [Yua01].
If we do not assume that is in , then the subdifferential , i.e., the slopes of tangent planes touching from below at , is not a graph over (for example, if , then ). Nevertheless, if we rotate the subdifferential downwards by , then we still obtain a gradient graph , where and is given explicitly by
(2.2) |
where , , and
is the Legendre transform of convex ; see [CSY19, Proposition 2.1]. The image domain is open and connected by [CSY19, Lemma 2.1], which comes from the fact that
(2.3) |
is strictly convex.
The transform (2.2) is order preserving, , hence, it preserves uniform limits. It follows that satisfies the same Hessian bounds (2.1) as in the smooth case. We could then use interpolation to see that locally uniformly provided uniformly, but this also follows from strict convexity, as in [CSY19, Proposition 2.3], i.e. if for convex, then
(2.4) |
The smallness of would then follow from reverse rotation .
Following [CSY19, Propositions 2.2,2.3], we show that viscosity solutions are preserved under this rotation.
Proposition 2.1.
Proof.
We first prove the following claim.
Claim 1.
We show that is a supersolution of (2.5) in .
Let be a quadratic polynomial touching from below locally somewhere on the open set say at the origin Since at , , we assume , by subtracting from , and then letting . This guarantees the existence of its pre-rotated quadratic polynomial and also confirms that touches from below in an open neighborhood of the closed set We still have . Using the order preservation of -rotation that is also valid for reverse rotation, and continuity of the gradient mapping in [Roc97, Corollary 24.5.1], we see that the pre-rotated quadratic polynomial touches at from below in an open neighborhood of Using the fact that is a supersolution of (1.1) we get
which in turn implies
Therefore, the claim holds good.
Claim 2.
We show that is a subsolution of (2.5) in .
The first part of this proof is the same as [CSY19, Prop 2.3, Step1] where a convolution of is considered and the smooth -rotation is shown to be well defined on for small enough.
Next, observe that (1.1) is concave when is a convex function. Applying [CC95, Theorem 5.8], we see that the solid convex average is a subsolution of
for small enough. Combining [CSY19, Prop 2.1] with the first part of this proof, we see that the smooth -rotation is a subsolution of
in , where . By (2.4), uniformly on , so uniformly on . Since uniformly on , and they are viscosity subsolutions of locally uniformly convergent equations , it follows from [CC95, Proposition 2.9] that is a subsolution of the limiting equation (2.5).
In the remainder, we abbreviate the rotated phase by
(2.6) | ||||
In particular, since , we see that is Lipschitz, so far.
3. Regularity of the rotated potential
We first show that followed by . We recall the notion of VMO functions.
Definition 1 (Vanishing mean oscillation).
Let . A locally integrable function is in with modulus if
where is the average of over
Proposition 3.1 (VMO Estimates).
Let be a viscosity solution of (2.5) in , where and is continuous. Then and the modulus of , denoted by as .
Proof.
Suppose the contrary is true. Then we can find and sequences , , and a family of viscosity solutions of (2.5) with , such that
Next, we blow up . For , we set
Here, is a viscosity solution of
By continuity of , the right hand side converges uniformly to , while the left hand side can be extended outside of to a uniformly elliptic operator. Meanwhile, for any fixed , we use and to find a convergent subsequence. By the diagonalization method, we find a subsequence, also denoted , which converges locally uniformly in on to as . Viscosity solutions are closed under uniform limits and locally uniformly convergent, uniformly elliptic sequences of PDEs [CC95, Proposition 2.9], so on any fixed ball, we find that is a viscosity solution of the special Lagrangian equation (1.3)
We also have convergence. Applying the estimate from [CC95, Prop 7.4], we get
where the RHS goes to as . Using the fact that , we see that for any , approaches as .
Since solves the special Lagrangian equation with Hessian bounds on , the work of Yuan from the 2000’s now applies [Yua01]. We refer verbatim to [CSY19, pg. 9, Step 1] which shows that is smooth under such conditions. We next apply [Yua02, pg. 122, Step B], which shows that a smooth entire solution of the constant phase equation with bounds (2.1) is quadratic. We briefly summarize the idea here: Using the calibration argument, the gradient graph is volume minimizing. The monotonicity formula [Sim83, Pg 84] combined with the flatness [Yua02, Prop 2.2] of graphical tangent cones with Hessian bounds , show that is smooth, by applying the VMO and then arguments from [Yua01]. On the other hand, the Hessian bounds also rule out tangent cones at infinity, giving the Bernstein theorem of [Yua02].
Continuing with our proof, we next use the convergence and to obtain:
which is a contradiction. ∎
By translation invariance of the VMO seminorms, will also be in if is small. This means we can conclude the following but for the sake of completeness, we provide a proof similar to Proposition 3.1.
Corollary 3.1.
Let be sufficiently small, and and be as defined in Proposition 3.1. Then a continuous function of and is in .
Proof.
Letting , we repeat the proof of Proposition 3.1, assuming instead that
Rescaling as before via and , we take subsequences and send to obtain limits and . The convergence is in , so after a subsequence, we can assume and converge almost everywhere. By the dominated convergence theorem and , it follows that converges in . In fact, and are quadratic polynomials, so is a constant. Therefore we have
which is a contradiction. ∎
Note that the seminorms of are independent of if is small. The point of is we need to take a difference quotient of (2.5).
Proposition 3.2 ( Estimates).
Let be a viscosity solution of (2.5) in , where and is Lipschitz continuous. Then for all .
Proof.
Letting , we obtain the linearized equation
(3.1) |
where
and we use the Einstein summation notation. For small , equation (3.1) holds pointwise (in fact, is twice differentiable everywhere, which is easily shown using the rescaling procedure in Proposition 3.1) on , and can be thought of as a linear equation for in nondivergence form, with, by Corollary 3.1, coefficients and right hand side , each of whose seminorms are independent of . Recalling the interior estimates due to [CFL91], see also [Vit92, Theorem 2.1], (although these estimates assume solutions are in , adding a cutoff function as in [GT01, proof of Theorem 9.11] yields standard interior estimates), we deduce that large, inside a slightly smaller domain in with local estimates independent of . Since for difference quotient we have , it follows that for all large , hence by the Sobolev Embedding Theorem for all . ∎
Now from Schauder theory, the rotated potential is as regular as the equation allows.
Corollary 3.2.
4. Proof of Theorem 1.1
The final step is to show that on . Indeed, once we prove this, we can compare with quadratics to convert to original variables. Let touch from above near and suppose, after lowering, that . By the order preservation of rotations, we see that touches from above near . Moreover, by the transformation law
Thus on , i.e. . This means is Lipschitz, so the above formula with replaced by implies . This means , and as before, we deduce . Since and , we conclude that . We now establish the desired inequality.
Remark 4.1.
We need only for the following proposition.
Proposition 4.1.
Let be a convex viscosity solution of (1.1) on , with . Then on .
Proof.
Suppose that at a point , or more generally that at . It follows that the following function is for near : . Fixing , we assume is diagonal at , with . Note that refers to the double partial derivatives of the function w.r.t to .
From [Bha21, Lemma 4.1] we get the following:
(4.1) |
where
with
Again following the notation introduced in [Bha21, pg 11], for each fixed in the above expression, we set and write
where denotes the th component of the mean curvature vector (given by (1.2): ), i.e. the component of the mean curvature vector along with being the eigendirection of . One can re-write
where for each fixed , the th term of is given by
By constant phase terms, we denote terms without dependence on the variable phase , which are therefore the same as in the case considered by [CSY19]. The constant phase terms are nonnegative if the Hessian bounds (2.1) are true, as in [CSY19, Section 3].
Using (2.6), we note the following
(4.2) |
Before dealing with (4.2), we would first like to deal with the second and third terms of (4.1), since (4.2) can be treated similarly.
The third term of (4.1) involving is harmless, so it suffices to lower bound the second term, which will have two contributions. Recalling (2.6),
(4.3) |
The first term of (4.3) yields a harmless contribution to the maximum principle:
For the second term of (4.3), we start with
(4.4) |
for some locally bounded . Next, we note that for nearby . By the convexity of in ,
so putting yields
(4.5) |
We thus conclude that in a sufficiently small neighborhood of ,
for some bounded continuous , where . We make a quick note here: The bound given by (4.2) can be treated in an exactly similar manner as above.
The strong maximum principle still holds because the right side vanishes at an interior maximum, according to [GT01, Lemma 3.4 and Theorem 3.5]. It follows that and on an open set containing . Since is connected, we conclude this is true everywhere: . However, because is bounded, we can touch it from above somewhere in by a sufficiently tall quadratic . The rotation then touches from above somewhere in . But corresponds (see [CSY19, end of section 3]) to , a contradiction. ∎
5. Proof of Theorem 1.2
Proof.
We now prove Hessian estimate (1.5) by compactness. If the estimate fails, then there is a sequence of convex solutions and phases to (1.1) with
Since is bounded, we can pass to a subsequence and assume converges uniformly to on . Note that is necessarily convex, so , as in Section 2, is uniformly convex. This means is open and contains , for . Moreover, if we shrink slightly and suppose , then for large enough , since if , then uniform convexity yields, via (2.4),
So the rotated sequence is defined on arbitrarily large subsets of , converging uniformly to thereabouts by the order preservation of rotation. It follows that is the locally uniform limit on of smooth rotations .
The smooth rotations have eigenvalues which blowup: . To see this for , we use the estimates for , noting that converges to some in the norm of after taking a subsequence. Along a subsequence, it follows that eventually converges locally in to in , so . Moreover, is a solution of the rotated equation , so by the strong maximum principle arguments in Proposition 4.1. This is a contradiction, since somewhere on for bounded convex . ∎
Remark 5.1.
In fact, a stronger Hessian estimate than (1.5) holds:
(5.1) |
where and are positive constants depending on and . This result follows from the methods in [Bha21]; the proof in [Bha21] goes through if the supercriticality condition is replaced by the convexity condition . A weaker estimate for such smooth solutions was obtained earlier in [War08, Theorem 8].
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