1 Introduction
Alexandrov’s estimate states that if $\Omega $ is a bounded open convex domain in $\mathbb {R}^n$ , and $u:\bar \Omega \to \mathbb {R}$ is a convex function such that $u=0$ on $\partial \Omega $ , then there exists a constant $C_n$ such that
Here,
and $\partial u$ denotes the subgradient of u, whose definition is recalled in (2.1). For now, we just mention that if u is $C^2$ , then $|\partial u(\Omega )| = \|\! \det D^2 u\|_{L^1(\Omega )}$ .
Estimate (1.1) plays an important role in the regularity theory of the Monge-Ampère equation (see, for example [Reference Gutiérrez4, Reference Figalli2]), and it is a key ingredient in some basic linear elliptic PDE estimates (see, for example, [Reference Gilbarg and Trudinger3], Chapter 9).
In this paper, we establish some improvements of (1.1). Before stating them, we introduce some notation. We will write
and
The definition immediately implies that for every $u\in {C^\mathrm{con}_0}(\bar \Omega )$ ,
and that this is sharp in that it fails for some $u\in {C^\mathrm{con}_0}(\bar \Omega )$ if $\omega _\Omega $ is replaced by any smaller function. With this notation, Alexandrov’s estimate (1.1) amounts to the assertion that $\omega _\Omega (\delta )\le C(\Omega )\delta ^{1/n}$ for all $\delta>0$ .
In this paper, we give a precise description of $\omega _\Omega $ , depending on the geometry of $\partial \Omega $ . This allows us to show that for any bounded, convex domain $\Omega $ whose boundary satisfies a very weak nondegeneracy condition (see (1.12)), there exists some $\alpha>1/n$ such that $\omega _\Omega (\delta ) \le C(\Omega ,\alpha )\delta ^\alpha $ for all $\delta>0$ or, in other words, that
Beyond that, we aim to characterize the range of $\alpha $ for which an estimate like the above holds and to estimate the optimal constant $C(\alpha ,\Omega )$ in (1.5), in terms of the geometry of $\partial \Omega $ .
Our first result addresses domains for which the Gaussian curvature $\kappa $ of the boundary satisfies
Except where stated otherwise, we do not impose any smoothness conditions beyond those that follow from convexity, which imply that $\partial \Omega $ is twice differentiable, and hence, the Gaussian curvature is defined, $\mathcal {H}^{n-1}$ a.e.. The left-hand side of (1.6) should be understood to mean the infimum over all points at which $\kappa $ is defined.
Theorem 1.1 Assume that $\Omega \subset \mathbb {R}^n$ is convex and bounded and that (1.6) holds. Let $\alpha _* := \frac 12 + \frac 1{2n}$ . Then
where $|B^n_1|$ denotes the volume of the unit ball in $\mathbb {R}^n$ .
Remark 1.2 The theorem implies that for $n=2$ ,
and that the estimate is sharp in the sense that it does not hold for any larger Hölder exponent or any smaller constant. Similarly, for $n\ge 3$ , since $\omega _\Omega (\delta )$ is continuous (this follows from (1.1) and the subadditivity of $\omega _\Omega $ , which is easily deduced from the definition) and constant for $\delta> \operatorname {diam}(\Omega )$ , the theorem implies that $\sup _{\delta>0} \delta ^{-\alpha }\omega _\Omega (\delta ) <\infty $ , and hence that (1.5) holds, if and only if $\alpha \le \alpha _*$ .
Note also that conclusion (1.8) may be described as an asymptotically sharp bound for the Hölder- $\alpha _*$ constant of $u\in {C^\mathrm{con}_0}(\bar \Omega )$ on scales $\le \delta $ , as $\delta \to 0$ . It is natural to ask
This again would yield the sharp constant in (1.5) for the critical space. We are tempted to conjecture that the answer is “yes,” but we do not have any evidence to support this. We believe that the requirement that $\Omega $ is $C^2$ is unnecessary and that convexity and (1.6) should suffice for (1.8).
Our other main result is less precise but completely general, in particular applying to domains for which the boundary curvature may vanish. As we will see, it implies that we can improve (1.1) to stronger Hölder norms as long as the domain satisfies a very weak nondegeneracy condition. It requires more notation. If $\Omega \subset \mathbb {R}^n$ is a convex set, we write $\Omega ^\circ $ to denote the polar of $\Omega $ , defined by
For $a\in \Omega $ and $\nu \in S^{n-1}$ , we write
If $P\subset \mathbb {R}^n$ is a k-dimensional subspace and $A\subset P$ is a subset with relatively open interior, we will write
For example,
as long as $S^\circ (x,\nu )$ has open interior within $\nu ^\perp $ , which will always be the case for us.
For $a\in \Omega $ , we will write
and
for the set of outer unit normals at boundary points closest to a.
We now state our second main result.
Theorem 1.3 Assume that $\Omega $ is a bounded, convex, and open subset of $\mathbb {R}^n$ . Then for every positive $\delta \le \max _{a\in \Omega }d_{\Omega }(a)$ ,
In principle, given a domain $\Omega $ with vanishing curvature, estimate (1.11) allows us to determine the exact scaling of $\omega _\Omega (\delta )$ as $\delta \searrow 0$ , and hence the exact range of exponents $\alpha>1/n$ for which estimate (1.5) holds. We illustrate this in Section 3 below with several examples. For now, we note the following:
Corollary 1.4 For $\Omega $ as above and $\alpha>1/n$ , the Hölder- $\alpha $ estimate (1.5) holds if and only if
for $\beta = n\alpha -1$ .
We omit the proof, as this follows directly from Theorem 1.3.
Remark 1.5 It is known that if $S\subset \mathbb {R}^n$ is any bounded convex set with nonempty interior, then
see [Reference Kuperberg7] for a proof with a good estimate of $c_n$ (whose sharp value is the focus of the Mahler conjecture). Thus, (1.11) implies that there exists $C = C_n$ such that
Remark 1.6 It is not hard to check that if $x\in \partial \Omega $ is a point at which $\partial \Omega $ is twice differentiable, with Gaussian curvature $\kappa $ , and if $\nu $ is the outer unit normal at x, then
We present the short proof in Lemma 3.4. This provides a quantitative link between the curvature at $x\in \partial \Omega $ and the rate of blowup of $|S^\circ ( x-\delta \nu , \nu )|$ as $\delta \searrow 0$ . In view of this, it is natural to interpret (1.12) as a degenerate positive curvature condition, growing more degenerate (and yielding a weaker Hölder exponent) as $\beta $ decreases.
To conclude this introduction, we note that several recent works have established sharp estimates of Hölder seminorms of solutions of Monge-Ampère equations of the form
for particular geometrically meaningful functions $F(x, u, Du)$ ; see, for example, [Reference Chen and Jian1, Reference Jian and Li5, Reference Jian and Wang6, Reference Le8, Reference Le9]. Some of these papers allow for domains in which the boundary curvature can vanish, and they determine Hölder exponents that reflect the boundary behavior in a way that has some similarities to what we find in Theorem 1.3; see Corollary 3.1. The proofs in these references rely on careful constructions of sub- and supersolutions or. even in rare cases. explicit solutions. These play no role in our arguments.
2 Preliminaries, and the proof of Theorem 1.3
Like all the results in this paper, those in this section are elementary, and many if not all (apart from the proof of Theorem 1.3, which. however, is an immediate corollary of other results) are presumably known to experts. For the convenience of the reader, we nonetheless provide complete proofs, mostly self-contained.
First, we recall some standard definitions. For $u\in {C^\mathrm{con}_0}(\bar \Omega )$ and $x\in \Omega $ ,
and for $A\subset \Omega $ ,
As mentioned above, if u is $C^2$ and strictly convex, then by the change of variables $p = Du(x)$ ,
(This remains true under somewhat weaker assumptions.) Given $a\in \Omega $ , we will write $u_{a}:\bar \Omega \to \mathbb {R}$ to denote the function defined by
The definition states that
and $u_a$ is linear on the line segment from any point on $\partial \Omega $ to a. When we wish to explicitly indicate the dependence of $u_a$ on $\Omega $ , we will write $u_{\Omega ,a}$ . It is well-known and straightforward to check that $u_a$ is convex.
Next, we define $f_\Omega :\Omega \to \mathbb {R}$ by
The following result implies that to understand the modulus of continuity for functions $u\in {C^\mathrm{con}_0}(\bar \Omega )$ with $|\partial u(\Omega )|$ finite, it suffices to study the asymptotics of $f_\Omega (a)$ as $a\to \partial \Omega $ .
Proposition 2.1 Let $\Omega $ be a bounded, convex, open subset of $\mathbb {R}^n$ . Then the modulus $\omega _\Omega $ defined in (1.3) satisfies
Proof Step 1. We first claim that for $u\in {C^\mathrm{con}_0}(\bar \Omega )$ and any $a,b\in \Omega $ , there exists $\bar a\in \Omega $ such that
We recall the proof, which is standard. Consider $a,b\in \Omega $ such that $u(a) \le u(b)\le 0$ . Let $\bar b$ be the point in $\partial \Omega $ on the ray that starts at a and passes through b. Then there exists some $\theta \in (0,1)$ such that $ b = (1-\theta )a + \theta \bar b$ . We next define $\bar a = \theta a + (1-\theta ) \bar b$ . These definitions imply that
Thus, $d_{\Omega }(\bar a)\le |\bar a -\bar b| = |a-b|$ . Moreover, by convexity,
Since $d_{\Omega }(\bar a)\le |a - b|$ , this proves (2.4).
Step 2. Given $u\in {C^\mathrm{con}_0}(\bar \Omega )$ , $\delta>0$ and $x,y\in \Omega $ such that $|x-y|\le \delta $ , fix $a\in \Omega $ such that $d_{\Omega }(a)\le \delta $ and $|u(x)-u(y)|\le |u(a)|$ , and define $w(x) = u(a) u_a(x)$ . Then $u\le w\le 0$ in $\Omega $ and $u=w=0$ on $\partial \Omega $ , so standard arguments (see, for example, [Reference Gutiérrez4, Lemma 1.4.1]) imply that
with equality if and only if $u = w$ . The definition (1.3) of $\omega _\Omega $ then implies that
Thus, for nonzero $u\in {C^\mathrm{con}_0}(\bar \Omega )$ ,
It follows from this and the definition of $\omega _\Omega $ that
However, given any $a\in \Omega $ such that $d_{\Omega }(a)\le \delta $ , consider $u = u_a$ , and fix $b\in \partial \Omega $ such that $d_{\Omega }(a) = |a-b|$ . Then
and thus,
Motivated by Proposition 2.1, we record some properties of $f_\Omega $ and related notions.
Lemma 2.1 $\partial u_a(a) = \partial u_a(\Omega )$ .
Proof It is clear that $\partial u_a(a) \subset \partial u_a(\Omega )$ . To prove the other inclusion, assume that $p\in \partial u(x_0)$ for some $x_0\in \Omega $ . We must show that $p\in \partial u(a)$ . We may assume that $x_0\ne a$ , so we can write $x_0 = \theta a + (1-\theta )y$ for some $y\in \partial \Omega $ and $\theta \in (0,1)$ .
For $x\in \Omega $ and $p\in \mathbb {R}^n$ , we will write $\ell _{x,p}(z) := u_a(x) + p\cdot (z-x)$ , so that $p\in \partial u_a(x)$ if and only if $\ell _{x,p}\le u_a$ in $\Omega $ . Since $u_a$ and $\ell _{x_0, p}$ are both linear when restricted to the segment $\{ sa+(1-s)y : s\in (0,1]\}$ , and because $x_0$ belongs to the interior of this segment and $u_a\ge \ell _{x_0,p}$ on this segment, we see that $u_a = \ell _{x_0,p}$ on this segment, and in particular at $x = a$ . Thus, $\ell _{x_0,p}$ is a supporting hyperplane at a; in fact, $\ell _{x_0,p} = \ell _{a,p}$ . It follows that $p\in \partial u_a(a)$ .
Lemma 2.2 If $a \in \Omega \subset \Omega '$ , then $f_{\Omega }(a) \ge f_{\Omega '}(a)$ .
Proof If $p\in \partial u_{\Omega ',a}(\Omega ')$ , then $p\in \partial u_{\Omega ', a}(a)$ , which implies that $\ell _{a,p}\le u_{\Omega ',a}$ in $\Omega '$ . But it is easy to check that $u_{\Omega ',a} \le u_{\Omega ,a}$ in $\Omega $ , and it follows that $\ell _{a,p}\le u_{\Omega ,a}$ in $\Omega $ , which implies that $p\in \partial u_{\Omega , a}(a)$ .
Thus, $\partial u_{\Omega ',a}(\Omega ') \subset \partial u_{\Omega ,a}(\Omega )$ , from which we deduce that $f_{\Omega '}(a)\le f_\Omega (a).$
Lemma 2.3 Assume that $\Omega \subset \mathbb {R}^n$ is bounded, convex, and open, with $a\in \Omega $ .
Then
An equivalent statement appears as an exercise (problem 3.3) in the recent text [Reference Le10].
Proof We first prove the lemma for $a=0$ . We know from Lemma 2.1 that $\partial u_0(\Omega ) = \partial u_0(0)$ . Then
Since $u_0(x)\le 0$ in $\Omega $ , it follows that
However, if $p\in \Omega ^\circ $ , then $\ell _{0,p}(x):= -1+x\cdot p$ is an affine function such that $\ell _{0,p} \le 0 = u_0$ on $\partial \Omega $ and $\ell _{0,p}(0)=-1 = u_0(0)$ . It follows from this and the definition of $u_0$ that $\ell _{0,p} \le u_0$ in $\Omega $ , and hence that $p\in \partial u_0(0)$ .
It follows that $\partial u_0(\Omega ) = \Omega ^\circ $ , and hence that $f_\Omega (0) = |\Omega ^\circ |$ .
For general $a\in \Omega $ , the definitions imply that for every $x\in \Omega $ ,
Thus, $f_\Omega (a) = |\partial u_{\Omega , a}( a) | = |\partial u_{\Omega -a,0}(0)| = |(\Omega -a)^\circ | $ .
Lemma 2.4 Let $M:\mathbb {R}^n\to \mathbb {R}^n$ be an invertible linear transformation, and let $M\Omega := \{ Mx: x\in \Omega \}$ . Then
Proof The definitions imply that for every $x\in \Omega $ ,
Thus, for every $x\in \Omega $ ,
We deduce that $\partial u_{M\Omega , Ma}(M\Omega ) = \{ M^{-T}p : p\in \partial u_{\Omega ,a}(\Omega )\}$ . Now the conclusion follows from basic properties of Lebesgue measure.
Lemma 2.5 Assume that $\Omega \subset \mathbb {R}^n$ is a bounded, open convex set containing the origin. For any subspace P of $\mathbb {R}^n$ , define
(Thus, $\Omega _P^\circ $ denotes the polar of $\Omega _P$ within P rather than within the ambient $\mathbb {R}^n$ .)
Let $\pi _P:\mathbb {R}^n\to P$ denote orthogonal projection onto P.
Then
Proof We will show that $(\pi _P(\Omega ^\circ ))^\circ = (\Omega _P^\circ )^\circ = \bar \Omega _P$ , where our convention is that if $A\subset P$ is convex, then $A^\circ $ denotes the polar within P, whereas if A is a convex set not contained in P, then $A^\circ $ denotes its polar in $\mathbb {R}^n$ . Then
completing the proof.
Lemma 2.6 Let $\Omega $ be an open convex subset of $\mathbb {R}^n$ with nonempty boundary. For $a\in \Omega $ , let $x\in \partial \Omega $ be a point such that $|a-x| = d_{\Omega }(a)$ , and let $\nu = \frac {x-a}{|x-a|}$ . (Thus, $\nu \in N(a)$ , in the notation introduced in (1.10).) Then
Remark 2.7 A curious consequence of (2.7) is that for $a\in \Omega $ , if there exist more than one point $b\in \partial \Omega $ such that $d_{\Omega }(a) = |b-a|$ , then
Proof Step 1. After a translation and a rotation, we may assume that $a=0$ and that $x = (0,\ldots , 0,-\delta )$ , where $\delta = d_{\Omega }(a)$ . Then $-e_n$ is the outer unit normal at x, and hence, $\Omega \subset \{ y\in \mathbb {R}^n : y_n> -\delta \}$ . One can then quickly check that
Let $P := \mathbb {R}^{n-1}\times \{0\}$ , so that $\Omega _P = S(a,\nu )$ . It then follows from Lemma 2.5 that
Now let T denote the Steiner symmetrization of $\Omega ^\circ $ with respect to the hyperplane $x_n=0$ . Well-known properties of Steiner symmetrization imply that $|T| = |\Omega ^\circ |$ , that T inherits the convexity of $\Omega ^\circ $ , and, owing to (2.8), (2.9), that
By convexity, T contains the cones in $\mathbb {R}^n$ with base $S^\circ (a,\nu )\subset \mathbb {R}^{n-1}\times \{0\}$ with vertices at $\pm \frac 1 {2\delta }e_n$ . Each of these cones has measure $\frac 1{2 \delta n} |S^\circ (a,\nu )|$ . We conclude that
Step 2. Let $P^\perp = \{0^{n-1}\}\times \mathbb {R}$ , the orthogonal complement of P. Since $a=0$ and $d_{\Omega }(a) \ge \delta $ , it is clear that $\Omega \cap P^\perp = \Omega _{P^\perp } \supset \{0^{n-1}\}\times (-\delta ,\delta )$ . It easily follows that $\Omega _{P^\perp }^\circ \subset \{0^{n-1}\}\times (-\frac 1\delta , \frac 1\delta )$ . In addition, Lemma 2.6 implies that
It follows from these facts and (2.9) that
(writing $S^0(a,\nu )$ as a subset of $\mathbb {R}^{n-1}$ rather than of $\mathbb {R}^{n-1}\times \{0\}$ ). Thus,
3 Examples
Our first illustration of the utility of Theorem 1.3 addresses a class of convex sets considered in several recent papers.
Corollary 3.1 Let $\Omega $ be a bounded, open convex subset of $\mathbb {R}^n$ , and assume that there exist positive constants $\eta $ and $p_1,\dots , p_k$ , with $k\le n-1$ , such that at any $b\in \partial \Omega $ , after a translation and a rotation,
Then there exists a constant C, depending on $\eta , n, \operatorname {diam}(\Omega )$ , such that
Note that (3.1) allows $\Omega $ to be completely degenerate at b in $n-k-1$ directions.
In [Reference Chen and Jian1, Reference Jian and Wang6], sharp Hölder estimates on domains satisfying (3.1) at every $b\in \partial \Omega $ (for a suitable b-dependent choice of coordinates) are proved for solutions of certain equations of the form (1.16). Interestingly, the quantity $\sum _{j=1}^k \frac 1{p_j}$ also appears in the Hölder exponents in these results, modified by other parameters appearing in the nonlinearity on the right-hand side of (1.16).
Proof Let $\delta>0$ and $a\in \Omega $ with $d_{\Omega }(a)=|a-b|=\delta $ for some $b\in \partial \Omega $ . After a translation and rotation, we may assume that (3.1) holds. We necessarily have that $a=(0, \ldots , 0, \delta )$ . Indeed, suppose $a_i\ne 0$ for some $1\le i \le n-1$ . Then from the supporting hyperplane $\{x_{n}=0\}$ , we obtain
a contradiction, verifying the claim.
Now, relabeling coordinates, we write the unit outer normal at b as $\nu =-e_{n}$ and have that
Thus, $|S(a,\nu )|$ is bounded by the volume of the set on the right, which is
for a constant C dependingFootnote 1 on $\eta , p_1,\ldots , p_k, k, n-1, \text {diam}(\Omega )$ . Since a was arbitrary, (1.13) and Theorem 1.3 (or see (1.14)) imply that
Hence, the result on the Hölder estimate.
If there is any point $b\in \partial \Omega $ such that after a translation and a rotation
for some positive numbers $\eta , p_1,\ldots , p_k, h$ , then by a similar argument to that above, one can show that $\omega _\Omega (\delta ) \ge c \delta ^\alpha $ for all sufficiently small $\delta $ and the same $\alpha $ as above. This would use the fact that if S is a centrally symmetric convex body in $\mathbb {R}^k$ , then $|S| \, |S^\circ | \le |B^k_1|^2$ .
The following lemma provides a way to generate a large class of examples.
Lemma 3.2 Assume that $\Omega \subset \mathbb {R}^2$ is a smooth convex set of the form
for some $R, D>0$ , where $h:[-R,R]\to [0,\infty )$ is an even function, smooth on $(-R,R)$ , such that $h(0)=h'(0) = h"(0)=0$ and $h(R) = \frac D2$ .
Assume, moreover, that the boundary curvature is nondecreasing as one moves in the direction of increasing $x_1$ along $\partial \Omega $ from $(0, 0)$ toward $(R,D/2)$ .
Then, writing $h^{-1}(\delta )$ to denote the unique positive solution of the equation $h(x)=\delta $ for $0<\delta \le D/2$ , there exists $\delta _0>0$ such that
The lemma implies that given any modulus of the form $\omega (\delta ) = \sqrt {\delta h^{-1}(\delta )}$ for h satisfying the above hypotheses, we can construct a domain for which the sharp modulus of continuity $\omega _\Omega $ in the Alexandrov estimate exactly agrees with $\omega $ , up to a factor of $2\sqrt 2$ .
Proof Assume that $0<\delta <\delta _0$ , to be fixed below.
Step 1. It is clear from (3.2) and properties of h that if $\delta _0$ is sufficiently small (in fact, here, $\delta _0<D/2$ is sufficient), then the origin is the unique closest boundary point to $(0,\delta )$ , and hence that $N(a)$ as defined in (1.10) consists of $\{ -e_2\}$ . Then the definitions imply that
Recall our convention that $S^\circ (a,\nu )$ denotes the polar within the subspace $\nu ^\perp $ . If a and b are positive numbers, then $(a,b)^\circ = [\frac 1a, \frac 1b]$ , so it follows that
This and Theorem 1.3 imply the lower bound for $\omega _\Omega (\delta )$ in (3.3).
Step 2. To complete the proof of the Lemma, again by Theorem 1.3, it suffices to show that if $d_{\Omega }(a)=\delta $ and $\nu \in N(a)$ , then
if $\delta _0$ is small enough. Fix any $a\in \Omega $ such that $d_{\Omega }(a)=\delta $ and any $b\in \partial \Omega $ such that $d_{\Omega }(a)=|a-b|$ , and let $\nu = \frac {b-a}{|b-a|}$ . Noting from (3.2) that $\Omega $ is symmetric about the $x_2$ axis (since h is even) and about the line $x_2 = D/2$ , we can assume that $b\in \{(x_1, x_2)\in \partial \Omega : 0\le x_1\le R, x_2 = h(x_1)\}$ .
Then we define $\widetilde \Omega $ to be the set obtained by translating b to the origin and rotating so that $\widetilde \Omega \subset \{(x_1, x_2): x_2>0\}$ . This operation moves a to the point $(0,\delta )$ . Next, we let $\tilde h_1$ be the function whose graph parametrizes the lower part of $\partial \widetilde \Omega $ , defined by $\tilde h(x_1) := \inf \{ x_2\in \mathbb {R} : (x_1, x_2)\in \widetilde \Omega \}$ . By our assumption about the monotonicity of the boundary curvature along the short arc connecting $(0,0)$ to $(R,D/2)$ , we see that if $\delta _0$ is small enough, then
for $0< x_1 < h^{-1}(\delta _0)$ . Since $\tilde h(0) = \tilde h'(0) = h(0) = h'(0)$ , and because $0=h"(0)\le \tilde h"(0)$ , this implies that $\tilde h(x_1) \ge h(x_1)$ for $0<x_1< h^{-1}(\delta _0)$ .
Computing $S^\circ (a,\nu )$ in the coordinate system of $\widetilde \Omega $ , we find that $S(a,\nu ) = (-\alpha , \beta )\times \{0\}$ , where $-\alpha ,\beta $ are the negative and positive solutions, respectively, of the equation $\tilde h(x)=\delta $ , and thus,
But the fact that $\tilde h \ge h$ for $0<x_1< h^{-1}(\delta _0)$ implies that $\beta \le h^{-1}(\delta )$ , proving (3.4).
Based on the above lemma, it is straightforward to construct examples of domains $\Omega \subset \mathbb {R}^2$ such that $\omega _\Omega (\delta ) \sim \delta ^{1/p}$ for given $p>2$ . Another example is obtained by taking $h(x)$ in (3.2) such that
and extended (after choosing a small enough) so that the graph of h has increasing curvature until the point where its tangent becomes vertical. Then the lemma implies that for the resulting domain $\Omega $ ,
In this spirit, it would be straightforward to construct sets with $\omega _\Omega $ , for example, having logarithmic or other corrections to Hölder moduli $\delta ^\alpha $ for some $\frac 1n <\alpha < \frac 12 + \frac 1{2n}$ .
The next lemma shows that, loosely speaking, the scaling in the classical Alexandrov estimate (1.1) is almost never optimal:
Lemma 3.3 Let $\Omega \subset \mathbb {R}^n$ be a convex, open domain, and assume that $\Omega \subset B_R$ for some $R>0$ . Then
In fact, if $\omega _\Omega (\delta ) \ge A\delta ^{1/n}$ for $\delta \in (0,\delta _0)$ , then there exists a supporting hyperplane P such that
The estimate of the radius of the ball is not sharp.
Proof We first claim that for $R, c>0$ and $S\subset \mathbb {R}^k$ ,
Indeed, for $r<R$ , suppose $S\subset B_R$ does not contain $B_r$ . By a rotation, we may assume that there is a point of the form $b = (0,\ldots , 0, r_1)$ with $0<r_1<r$ such that $d_S(0) = |0 - b| = r_1$ . Then the plane $\{ x : x_k = r_1\}$ is a supporting hyperplane at b, so $S\subset B_R \cap \{ x : x_k < r_1\}$ . We claim that
This is clear, since if $y = (y', y_n)$ belongs to the set on the left, then one readily checks that $x\cdot y\le 1$ for all $x\in S \subset B_R \cap \{ x : x_k<r_1\}$ , proving (3.6). It follows that
This cannot happen if $r \le \frac {|B^{k-1}_1|}{2c(2R)^{k-1}}$ . So for such r, it must be the case that $B_r\subset S$ , proving (3.5).
Now assume that there exists $A>0$ such that $\omega _\Omega (\delta )\ge A \delta ^{1/n}$ , and fix a sequence $a_j\in \Omega $ and $\nu _j\in N(a_j)$ such that $d_{\Omega }(a_j) := \delta _j\to 0$ , and $|S^\circ (a_j, \nu _j)| < n A^{-n}$ . The existence of such sequences follows directly from Theorem 1.3. Upon passing to subsequences (still labeled $a_j, \nu _j, \delta _j$ ) we may assume that $a_j\to b\in \partial \Omega $ . After a translation and a rotation, we may assume that $b=0$ and $\Omega \subset \{ x\in \mathbb {R}^n : x_n>0\}$ .
Appealing to (3.5) with $k=n-1$ , we find that $B_r\subset S(a_j, \nu _j)$ with $r = \frac {|B^{n-2}_1| A^n }{2^{n-1}n R^{n-2}}$ . Then the definition of $S(a_j,\nu _j)$ implies that
This implies that $\nu _j\to - e_n $ as $j\to \infty $ and $a_j\to b=0$ . Then
as $j\to \infty $ , in the Hausdorff distance. It follows that $B^{n-1}_r\times \{0\}\subset \bar \Omega $ , and hence, since $\Omega \subset \{x : x_n>0\}$ , we conclude that $B^{n-1}_r\times \{0\}\subset \partial \Omega $ . Thus, we have found a flat spot.
We omit the proof that if $\partial \Omega $ has a flat spot, then $\omega _\Omega (\delta ) \ge c\delta ^{1/n}$ for some c, which is a very direct consequence of Theorem 1.3.
Finally, we present the proof of a fact already stated in the introduction.
Lemma 3.4 If $x\in \partial \Omega $ is a point at which $\partial \Omega $ is twice differentiable, with Gaussian curvature $\kappa $ , and if $\nu $ is the outer unit normal at x, then
Proof Choosing coordinates so that $x=0$ and $\nu = - e_n$ , we find that locally near $0$ , $\Omega $ has the form $\{ x = (x', x_n)\in \mathbb {R}^{n-1}\times \mathbb {R}: x_n> h(x')\}$ for h such that $h(x') = \frac 12 x'\cdot Q x'(1+o(1))$ as $x'\to 0$ , with $\det Q = \kappa $ . From there, the definitions imply that
The expansion of h for small $x'$ implies that for any $\varepsilon>0$ , there exists $\delta _0>0$ such that if $0<\delta <\delta _0$ , then
Since the ellipse $\{ x' : x'\cdot Q x' < r^2\}$ has volume $r^{n-1}|B^{n-1}_1|/\sqrt {\det Q}$ , we deduce (3.7) from the standard fact that $|E| \, |E^\circ | = |B^{n-1}_1|^2$ for any ellipse E in $\mathbb {R}^{n-1}$ , a consequence of affine invariance.
4 Proof of Theorem 1.1
The proof of Theorem 1.1 is distributed among Propositions 4.1, 4.2, and 4.3. Before starting their proofs, we give a preliminary lemma.
Lemma 4.1 Let $E\subset \mathbb {R}^n$ denote the ellipsoid
let $a := (0,\ldots , 0, -\alpha )$ for some $\alpha \in [0,\ell _n)$ , and let $p = (0,\ldots ,0, -\ell _n)\in \partial E$ . If $\alpha $ is close enough to $\ell _n$ , then
Proof We recall that if $S\subset \mathbb {R}^n$ is a convex set, the support function $\sigma _S$ is defined by
It is rather clear from the definitions that
Step 1. Let B denote the unit ball $B^n_1$ . Then using the properties of the support function noted above,
For a as above, by writing $y = (y', y_n)\in \mathbb {R}^{n-1}\times \mathbb {R}$ , by squaring both sides, completing a square, and rearranging, we find that
The inequality on the right defines an ellipsoid whose volume is easily found, yielding
Since $d_{\partial B}(a) = 1-\alpha $ , we can rewrite this as
Step 2. Now let E denote a general ellipsoid as in the statement of the theorem. Noting that
we find from Lemma 2.4 that
Also, since $M^{-1}a = (0,\ldots , 0, -\alpha /\ell _n)$ , we see that $d_B(M^{-1}a) = 1-\frac \alpha {\ell _n} = \frac {\ell _n-\alpha }{\ell _n}$ . Substituting into the above formula, we obtain
It is clear that if $\alpha $ is close enough to $\ell _n$ , then $\ell _n-\alpha = d_{ E}(a)$ . So to complete the proof, we must show that $\kappa (p) = \ell _n^{n-1}/(\ell _1^2\cdots \ell _{n-1}^2)$ . This is an easy computation. Near p, we write $\partial E$ as the graph
We compute that $Dg(0)=0$ and $D^2 g(0) = \ell _n \text {diag}(\ell _1^{-2}, \ldots , \ell _{n-1}^{-2})$ , and it follows that $\kappa (p) = \det D^2 g(0) = \ell _n^{n-1}/(\ell _1^{2} \cdots \ell _{n-1}^{2})$ , as claimed.
Proposition 4.1 Let $\Omega \subset \mathbb {R}^n$ be a bounded, convex open subset of $\mathbb {R}^n$ for $n\ge 2$ , and assume that (1.6) holds. Then
Proof Given $\varepsilon>0$ , choose a point $p_\varepsilon \in \partial \Omega $ at which $\partial \Omega $ is twice differentiable and $\kappa (p_\varepsilon ) < (1+\varepsilon )\kappa _0$ . We may assume after a translation and a rotation that $p_\varepsilon =0$ and that there exists $r>0$ such that in a neighborhood of $p_\varepsilon $ ,
for a convex g such that
with
Now let $E_\varepsilon $ be the ellipse
for
We claim that
In view of (4.2), it suffices to show that if $\eta $ is small enough and $x = (x',x_n)\in E_\varepsilon $ , then $x\in B_r$ and $x_n> g(x')$ .
It is clear that there exists $\eta _0>0$ such that $E_\varepsilon \subset B^n_r$ whenever $0<\eta <\eta _0$ .
Second, we use the concavity of the square root to see that
Note also that the definitions imply that $|x'| < C \sqrt \eta $ for $(x',x_n)\in E_\varepsilon $ , so the above inequality and (4.3) imply that there exists $\eta _1\in (0,\eta _0)$ such that if $0<\eta <\eta _1$ , then $x_n> g(x')$ , completing the proof of (4.4).
We henceforth fix $\eta <\eta _1$ . Let $a_\delta = (0,\ldots , 0,\delta )$ for $\delta < \ell _n$ , and note that $a_\delta \in E_\varepsilon $ when $\delta <2\ell _n$ . Note also that $d_{\Omega }(a_\delta ) = d_{ E_\varepsilon }(a_\delta )= \delta $ for all sufficiently small $\delta>0$ .
It follows from Lemma 2.2 that $f_\Omega (a_\delta )\le f_{E_\varepsilon }(a_\delta ) (a)$ , so we use (an easy modification of) Lemma 4.1 to conclude
where $\kappa _{E_\varepsilon }(0)$ denotes the curvature of $\partial E_\varepsilon $ at $0$ , which is
Applying Proposition 2.1, we find that
Since $\varepsilon>0$ was arbitrary, conclusion (4.1) follows.
Proposition 4.2 Let $\Omega $ be a bounded, open, convex subset of $\mathbb {R}^2$ satisfying (1.6). Then
Proof We will show that for any $a\in \Omega $ ,
In view of Proposition 2.1, this implies that
This will complete the proof of the Proposition, as the opposite inequality follows from Proposition 4.1.
To prove (4.5), fix any $a\in \Omega $ , and let $b\in \partial \Omega $ be a point such that $d_{\Omega }(a) = |a-b| =: \delta $ , not necessarily small. After a rotation and a translation, we may assume that $b = (0,0)$ and $a = (0,\delta )$ . Clearly, $B_\delta (a)\subset \Omega $ , and $0\in \partial B_\delta (a)\cap \partial \Omega $ . From these facts and the convexity of $\Omega $ , one easily sees that $\Omega \subset \{ (x_1,x_2) : x_2>0\}$ and
Let $I = \{ x_1 : (x_1,x_2)\in \Omega \text { for some }x_2\}$ be the projection of $\Omega $ onto the $x_1$ -axis. Then writing the lower part of $\partial \Omega $ as the graph of a function $g:I\to \mathbb {R}$ , we have
Note that g is differentiable at $x_1=0$ , with $g'(0)=0$ .
We now claim that
We will prove this for $x_1>0$ ; the argument for $x_1<0$ is basically identical. Let us write $S := \{ x_1\in I : g\text { is twice differentiable at }x_1\}$ . To prove (4.6), we recall assumption (1.6), which implies that
This clearly implies that $g"(x_1)\ge \kappa _0$ in S. Since g is convex, $g'$ is increasing function, so for positive $x_1\in I$ , elementary real analysis yields
Since $g'$ is locally Lipschitz, we obtain (4.6) by integrating again.
In view of (4.6) and Lemma 2.2, in order to prove (4.5), it suffices to show that
This is a straightforward computation. First, let
Then $\widetilde D := MD = \{ (x_1, x_2) : x_2> x_1^2 \}$ and $Ma = (0,1) = e_2$ . By Lemma 2.4,
and
Given $y\in \mathbb {R}^2$ , we compute $\sigma _{\widetilde D - e_2}(y)$ by attempting to find x that maximizes $x\mapsto y\cdot (x-e_2)$ subject to the constraint that $x\in \widetilde D$ . It is clear that a maximum can only occur for $x\in \partial \widetilde D$ , so one can use Lagrange multipliers to find that
It easily follows that
concluding the proof of (4.7).
The remaining assertion of Theorem 1.1 is contained in the following proposition. The idea of the proof is to approximate $\partial \Omega $ from the outside, locally, by a quadratic. We need to be able to do this in a uniform way and. having done so, to extract information about $\partial u_a(\Omega )$ from its quadratic approximation when this approximation is only local.
Proposition 4.3 If $n\ge 3$ and $\partial \Omega $ is $C^2$ , then
Proof In view of Proposition 4.1 and Proposition 2.1, we only need to prove that
Step 1. We first claim that for any $\varepsilon _1>0$ , there exists $r_0>0$ such that for any $b \in \partial \Omega $ , there exists a rigid motion S (that is, the composition of a rotation and a translation) and a convex $C^2$ function $g:B^{n-1}_{r_0}\to [0,\infty )$ such that
and $g(0)=0$ , with
where $\| \cdot \|$ denotes the operator norm. Informally, this states that $\partial \Omega $ is uniformly $C^2$ . Since $\partial \Omega $ is $C^2$ and compact, on some level this is clear, but we provide some details nonetheless. Our proof of (4.10) will also show that there exist positive $\Lambda _{min}\le \Lambda _{max}$ , independent of $b\in \partial \Omega $ , such that
First, the compactness of $\partial \Omega $ implies that there exists $R>0$ , $J\ge 2$ and
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• maps $S_j: \mathbb {R}^n\to \mathbb {R}^n$ for $j=1,\ldots , J$ , each one a rigid motion (the composition of a translation and a rotation),
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• $C^2$ functions $h_j:B_{4R}^{n-1}\to [0,\infty )$ for $j=1,\ldots , J$ ,
such that $|\nabla h_j| \le \frac 14$ in $B_{4R}^{n-1}$ and
For every j, clearly, $h_j, D h_j$ , and $D^2 h_j$ are uniformly continuous on $B_{3R}^{n-1}$ , and there are only finitely many of these functions, so there exists a common $C^2$ modulus of continuity for $\{ h_j\}_{j=1}^J$ on $B_{3R}^{n-1}$ , by which we mean a continuous, increasing function $\mu :[0,\infty )\to [0,\infty )$ such that $\mu (0)=0$ and
for all x and y in $B_{3R}^{n-1}$ and $j=1,\ldots , J$ .
Now consider any $b\in \partial \Omega $ . Fix some $\bar x'\in B^{n-1}_R(0)$ and $j\in \{1,\ldots , J\}$ such that $b = S_j(\bar x', h_j(\bar x'))$ . By a further translation, we may send $(\bar x', h_j(\bar x'))$ to the origin in $\mathbb {R}^n$ . Then by a rotation in $\mathbb {R}^n$ , we can arrange that part of the (translated and rotated) graph of $h_j$ over $B_{2R}(\bar x')$ can be written as the graph over some ball $B_{r}^{n-1}$ of a convex $C^2$ function $g:B^{n-1}_r\to [0,\infty )$ such that $g(0)=0$ and $\nabla g(0)=0$ . By applying Lemma 4.2 below to $h(x') = h_j(x' - \bar x') - h_j(\bar x')$ , we find that independent of the choice of b, the domain of the resulting function g can be taken to be $B^{n-1}_R$ , and g has a $C^2$ modulus of continuity in $B_R^{n-1}$ that can be estimated solely in terms of $\mu $ from (4.12). This proves (4.10). Similarly, (4.11) follows from (4.25) in Lemma 4.2, which we prove below, together with the fact that for every $j\in \{1,\ldots ,J\}$ , the eigenvalues of $D^2 h_j$ are bounded away from $0$ in $B^{n-1}_R$ , being positive on $B^{n-1}_{2R}$ .
Step 2. We now prove (4.9).
Step 2.1: Normalization and approximation by a quadratic. Because $\partial \Omega $ is $C^2$ and compact, there exists $\delta _0>0$ such that if $\delta := d_{\Omega }(a) <\delta _0$ , then there is a unique $b\in \partial \Omega $ such that $d_{\Omega }(a)=|a-b|$ . Fix some such a and b. In view of Step 1, we may assume after a rigid motion that $a = \delta e_n = (0,\ldots , 0,\delta )$ and $b=0$ , and that there is a nonnegative convex function g, vanishing at $x'=0$ , such that (4.10) holds for some $\varepsilon _1$ and $r_0(\varepsilon _1)$ to be specified in a moment, and with $\{(x', g(x')) : |x'|<r_0\}$ contained in the (rotated and translated) $\partial \Omega $ .
Fix $\varepsilon>0$ . Using (4.10) for a suitably small choice of $\varepsilon _1$ and calculus, we can guarantee that
Let $M:= Q^{1/2}$ , the positive definite symmetric square root of Q, and define
Due to (4.11), the eigenvalues of M are bounded between $ \Lambda _{min}^{1/2}$ and $\Lambda _{max}^{1/2}$ . Thus,
The definition of $\widetilde g$ is chosen so that
Hypothesis (1.6) implies that $\det Q = (\text {curvature of }\partial \Omega \text { at }b=0) \ge \kappa _0$ , so we deduce from Lemma 2.4 that
In addition, using (4.14) and requiring that $\varepsilon < \frac 12 \Lambda _{min}$ , we can translate properties (4.13) into statements about $\tilde g$ . It follows that $(y',\tilde g(y'))\in \partial \widetilde \Omega $ and
Fix $z'$ such that $|z'|< r_\delta /2$ and let $\Phi (y') := z'+y' - D\tilde g(y')$ . Then the second inequality in (4.16) implies that $\Phi $ maps $\bar B_{r_2}^{n-1}$ to itself, for $r_2 = 2|z'| < r_\delta $ . Thus, the Brouwer Fixed Point Theorem implies that $\Phi $ has a fixed point $y'$ in $B_{r_2}^{n-1}$ . But $\Phi (y') =y'$ exactly when $D\tilde g(y') = z'$ . It follows that
Step 2.2: finding a large subset of $\partial u_{\widetilde \Omega , a}(\tilde \Omega )$ .
We will write $\tilde u_{\tilde a} := u_{\widetilde \Omega , \tilde a}$ . We next will show that
To see this, fix $z'\in B^{n-1}_{r_\delta /2}$ , and using (4.17), find $y'\in B^{n-1}_{r_\delta }$ such that $\nabla \tilde g(y') = z'$ . Let
We claim that $\ell _{y'}$ is a supporting hyperplane to the graph of $\tilde u_{\tilde a}$ at $\tilde a =e_n$ . We must show that $\ell _{y'}(\tilde a) = \tilde u_{\tilde a}(\tilde a) = -1$ , which follows directly from the definition, and that $\ell _a \le \tilde u_{\tilde a}$ in $\widetilde \Omega $ . Since both $\ell _a$ and $\tilde u_{\tilde a}$ are linear on line segments connecting $\partial \widetilde \Omega $ to $\tilde a$ , it suffices to check that $\ell _a \le \tilde u_{\tilde a} = 0$ on $\partial \widetilde \Omega $ . This follows from noting that $\ell _{y'}$ vanishes exactly on the hyperplane $\{ x\in \mathbb {R}^n : \nu (y) \cdot (x - y) = 0\}$ , where $y = (y', \tilde g(y'))\in \partial \widetilde \Omega $ and $\nu (y)$ is the outer unit normal to $\partial \widetilde \Omega $ at y. This is a supporting hyperplane to $\partial \widetilde \Omega $ , so $\ell _{y'}$ does not change sign in $\widetilde \Omega $ . Since $\ell _{y'}(\tilde a)<0$ , the claim follows.
Thus, $\nabla \ell _{y'}(\tilde a)\in \partial \tilde u_{\tilde a}(\tilde a)$ . Since it is clear that $0\in \partial \tilde u_{\tilde a}(\tilde a)$ and $\partial \tilde u_{\tilde a}(\tilde a)$ is convex, it follows that the segment $\{ s\nabla \ell _{y'}(\tilde a) : 0\le s \le 1\} \subset \partial \tilde u_{\tilde a}(\tilde a)$ ; that is,
However, recalling that $\nabla \tilde g(y') = z'$ , and using (4.16) and elementary inequalities,
We deduce (4.18) by combining this and (4.19).
Step 2.3: conclusion of proof. Since a was an arbitrary point such that $d_{\Omega }(a)=\delta $ , it follows from (4.18) and (4.15) that for all sufficiently small $\delta $ ,
We will show that
Since $\varepsilon>0$ is arbitrary, this and (4.20) imply (4.9) and thus complete the proof of the Proposition.
To establish (4.21), note first that $E_{\varepsilon ,\delta }$ forms an increasing family of sets as $\delta \searrow 0$ . Thus, the Monotone Convergence Theorem implies that $\lim _{\delta \to 0}|E_{\varepsilon ,\delta }| = |E_{\varepsilon ,0}|$ , for
We claim that, in fact,
Indeed, both $\mathcal E_{\varepsilon ,0}$ and $E_{\varepsilon ,0}$ are contained in the set $\{ 0\} \cup \{(q', q_n) : q_n < 0\}$ . It is clear that the origin belongs to both sets. Any point with $(q', q_n)$ with $q_n<0$ can be written
Then
and
from which we see that
One then checks that
For $q_n<0$ , the right-hand side is larger than $1$ if and only if $t>1$ . Thus,
Since $(q', q_n)\in E_{\varepsilon ,0}$ if and only if $0<t\le 1$ in (4.23), this implies (4.22).
And it is clear that $|\mathcal E_{\varepsilon ,0}|= \frac {(1-\varepsilon )^{(n-1)/2}|B^n_1|}{2^{(n+1)/2}}$ , proving (4.21).
Finally, we establish the lemma used above. In the proof, we find it helpful to write points $x = (x', x_n)\in \mathbb {R}^n = \mathbb {R}^{n-1}\times \mathbb {R}$ as column vectors $\binom {x'}{x_n}$ .
Lemma 4.2 Let $h\in C^2(B^{n-1}_{2R})$ satisfy $h(0)= 0$ and $\| \nabla h\|_{L^\infty } \le \frac 14$ .
Then there exists a rotation $S\in SO(n)$ and a function $g\in C^2(B^{n-1}_R)$ such that $\nabla g(0)=0$ ,
and such that the $C^2$ modulus of continuity of g can be estimated in terms only of the $C^2$ modulus of continuity of h in $B^{n-1}_{20R/11}$ . Moreover,
for some $m \in [-\frac {1}{4},\frac {1}{4}]$ , and if h is convex, then g is convex.
The conclusion of the lemma is a little stronger than we need for the proof of Proposition 4.3.
Proof We may assume by a suitable choice of coordinates that $\nabla h (0) = m e_{n-1}$ for some $m\in [-\frac 14, \frac 14]$ , where $e_{n-1}$ is the standard basis vector along the $x_{n-1}$ axis.
We then define (temporarily adopting column vector notation for ease of reading)
Clearly, $S\in SO(n)$ . Note that $\alpha \ge 4/\sqrt {17}> 4/5$ and $|\beta |\le 1/\sqrt {17} < 1/4$ . We next define $\Phi :B_{2R}^{n-1} \to \mathbb {R}^n$
where we will write the components of $\phi $ as $(\phi ^1,\ldots , \phi ^{n-1})$ , for $\phi $ and $\phi ^n$ taking values in $\mathbb {R}^{n-1}$ and $\mathbb {R}$ , respectively. We now define
We now verify that these functions have the stated properties.
Proof that g is well-defined on $B_R^{n-1}$ : From the definitions, we see that
Thus, writing $\| A\|$ to denote the operator norm of a matrix A and $I_k$ the $k\times k$ identity matrix, we check that
Now fix any $y'\in B_R^{n-1}$ , and define $\Phi (x') = y'+x' -\phi (x')$ . Then for any $x', z'\in B_{2R}^{n-1}$ ,
Thus, $\Phi $ is a contraction mapping. Note also, that when $y=0$ , we find from (4.28) that $|\phi (x')-x'| \le \frac 9{20}|x'|$ . So if $|x'| \le 20R/11$ , then
So $\Phi $ maps $B^{n-1}_{20R/11}$ to itself, and the Contraction Mapping Principle thus implies that there is a unique $z'\in B^{n-1}_{20R/11}$ such that $\Phi (z') = z'$ , which says exactly that $\phi (z') = y'$ .
These facts imply that $\phi ^{-1} =\psi $ is well-defined in $B^{n-1}_R$ , taking values in $B^{n-1}_{20R/11}$ , and hence that g is well-defined in $B^{n-1}_R$ as well.
Proof that (4.24) holds: The definitions imply that if $y' = \phi (x')$ , then $g(y') = \phi ^n(x')$ , and thus,
We deduce (4.24) from this and remarks above about the range of $\psi $ .
Proof that $\nabla g(0)=0$ : We compute
Since $\phi (0)=0$ , it is clear that $\psi (0)=0$ . It thus suffices to check that $\nabla \phi ^n (0)=0$ . This follows from the choice of $\alpha $ and $\beta $ , which guarantees that
$C^2$ modulus of continuity of g: By differentiating (4.29), we obtain
Moreover,
For every $x'\in B_{2R}^{n-1}$ , it follows from (4.27) that $D\phi (x')$ belongs to the compact set $\{ A\in M^{n-1} : \| A - I\| \le 9/20 \}$ on which the map $A\mapsto A^{-1}$ is smooth and hence bounded and Lipschitz. Hence, $D\psi $ is bounded in $B_R^{n-1}$ , and $\psi $ is Lipschitz continuous. Then elementary estimates show that first $D\psi $ and then $D^2\psi $ have moduli of continuity estimated only in terms of the $C^2$ modulus of continuity of $\phi $ , which in turn is controlled by the $C^2$ modulus of continuity of h. Then similar arguments show that the $C^2$ modulus of continuity of g can be estimated only in terms of that of h.
Formula for $D^2 g(0)$ . Computing as in our verification that $\nabla g(0)=\nabla \phi ^n(0)=0$ , and recalling that $\psi (0)=0$ , one easily checks that $D^2 \phi ^n(0) = \alpha D^2 h(0)$ . Similarly, nothing from the definitions that $\partial _{n-1}\phi ^{n-1}(0) = \alpha +\beta m = 1/\alpha $ , one checks that
We deduce (4.25) from these facts and (4.30).
Finally, it is clear that if h is convex, then g is convex, as then the graph of g is part of the lower boundary of a convex set.
Acknowledgements
This work was partially supported by the Natural Sciences and Engineering Research Council of Canada under Operating Grant 261955. In addition, the research of Charles Griffin was partially funded by an NSERC Undergraduate Summer Research Award. The authors thank Nam Q. Le and an anonymous referee for some helpful remarks.