In this work we consider the computational approximation of a unique continuation problem for the Helmholtz equation using a stabilized finite element method. First conditional stability estimates are derived for which, under a convexity assumption on the geometry, the constants grow at most linearly in the wave number. Then these estimates are used to obtain error bounds for the finite element method that are explicit with respect to the wave number. Some numerical illustrations are given.
Authors
Erik Burman Department of Mathematics, University College London, Gower Street, London, WC1E 6BT, United Kingdom
Mihai Nechita Department of Mathematics, University College London, Gower Street, London, WC1E 6BT, United Kingdom
Lauri Oksanen Department of Mathematics, University College London, Gower Street, London, WC1E 6BT, United Kingdom
Keywords
Helmholtz equation; unique continuation; Finite Element method; wave number explicit; conditional Hölder stability.
Paper coordinates
E. Burman, M. Nechita, L. Oksanen, Unique continuation for the Helmholtz equation using stabilized finite element methods, J. Math. Pures Appl., 129 (2019), pp. 1-22. DOI: 10.1016/j.matpur.2018.10.003
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UNIQUE CONTINUATION FOR THE HELMHOLTZ EQUATION USING STABILIZED FINITE ELEMENT METHODS
ERIK BURMAN, MIHAI NECHITA, AND LAURI OKSANEN
Abstract
In this work we consider the computational approximation of a unique continuation problem for the Helmholtz equation using a stabilized finite element method. First conditional stability estimates are derived for which, under a convexity assumption on the geometry, the constants grow at most linearly in the wave number. Then these estimates are used to obtain error bounds for the finite element method that are explicit with respect to the wave number. Some numerical illustrations are given.
1. Introduction
We consider a unique continuation (or data assimilation) problem for the Helmholtz equation
and introduce a stabilized finite element method (FEM) to solve the problem computationally. Such methods have been previously studied for Poisson's equation in [5], [6] and [8], and for the heat equation in [10]. The main novelty of the present paper is that our method is robust with respect to the wave number kk, and we prove convergence estimates with explicit dependence on kk, see Theorem 1 and Theorem 2 below.
An abstract form of a unique continuation problem is as follows. Let omega sub B sub Omega\omega \subset B \subset \Omega be open, connected and non-empty sets in R^(1+n)\mathbb{R}^{1+n} and suppose that u inH^(2)(Omega)u \in H^{2}(\Omega) satisfies (1) in Omega\Omega. Given uu in omega\omega and ff in Omega\Omega, find uu in BB.
This problem is non-trivial since no information on the boundary del Omega\partial \Omega is given. It is well known, see e.g. [20], that if bar(B\\omega)sub Omega\overline{B \backslash \omega} \subset \Omega then the problem is conditionally Hölder stable: for all k >= 0k \geq 0 there are C > 0C>0 and alpha in(0,1)\alpha \in(0,1) such that for all u inH^(2)(Omega)u \in H^{2}(\Omega)
If B\\omegaB \backslash \omega touches the boundary of Omega\Omega, then one can only expect logarithmic stability, since it was shown in the classical paper [21] that the optimal stability estimate for analytic continuation from a disk of radius strictly less than 1 to the concentric unit disk is of logarithmic type, and analytic functions are harmonic.
In general, the constants CC and alpha\alpha in (2) depend on kk, as can be seen in Example 4 given in A. However, under suitable convexity assumptions on the geometry and direction of continuation it is possible to prove that in (2) both the constants CC and alpha\alpha are independent
of kk, see the uniform estimate in Corollary 2 below, which is closely related to the so-called increased stability for unique continuation [17]. Obtaining optimal error bounds in the finite element approximation crucially depends on deriving estimates similar to (2), with weaker norms in the right-hand side, as in Corollary 3below, or in both sides, by shifting the Sobolev indices one degree down, as in Lemma 2 below.
In addition to robustness with respect to kk, an advantage of using stabilized FEM for this unique continuation problem is that-when designed carefully-its implementation does not require information on the constants CC and alpha\alpha in (2), or any other quantity from the continuous stability theory, such as a specific choice of a Carleman weight function. Moreover, unlike other techniques such as Tikhonov regularization or quasi-reversibility, no auxiliary regularization parameters need to be introduced. The only asymptotic parameter in our method is the size of the finite element mesh, and in particular, we do not need to saturate the finite element method with respect to an auxiliary parameter as, for example, in the estimate (34) in 4.
Throughout the paper, CC will denote a positive constant independent of the wave number kk and the mesh size hh, and which depends only on the geometry of the problem. By A≲BA \lesssim B we denote the inequality A <= CBA \leq C B, where CC is as above.
For the well-posed problem of the Helmholtz equation with the Robin boundary condition
{:(3)Delta u+k^(2)u=-f quad" in "Omegaquad" and "quaddel_(n)u+iku=0quad" on "del Omega",":}\begin{equation*}
\Delta u+k^{2} u=-f \quad \text { in } \Omega \quad \text { and } \quad \partial_{n} u+\mathrm{i} k u=0 \quad \text { on } \partial \Omega, \tag{3}
\end{equation*}
{:(5)||u||_(H^(2)(Omega)) <= Ck||f||_(L^(2)(Omega)):}\begin{equation*}
\|u\|_{H^{2}(\Omega)} \leq C k\|f\|_{L^{2}(\Omega)} \tag{5}
\end{equation*}
hold for a star-shaped Lipschitz domain Omega\Omega and any wave number kk bounded away from zero [3. The error estimates that we derive in Section 3, e.g. ||u-u_(h)||_(H^(1)(B)) <= C(hk)^(alpha)||u||_(**)\left\|u-u_{h}\right\|_{H^{1}(B)} \leq C(h k)^{\alpha}\|u\|_{*} in Theorem 2, contain the term
which corresponds to the well-posed case term k||f||_(L^(2)(Omega))k\|f\|_{L^{2}(\Omega)}.
It is well known from the seminal works [2, 18, 19] that the finite element approximation of the Helmholtz problem is challenging also in the well-posed case due to the so-called pollution error. Indeed, to observe optimal convergence orders of H^(1)H^{1} - and L^(2)L^{2}-errors the mesh size hh must satisfy a smallness condition related to the wave number kk, typically for piecewise affine elements, the condition k^(2)h≲1k^{2} h \lesssim 1. This is due to the dispersion error that is most important for low order approximation spaces. The situation improves if higher order polynomial approximation is used. Recently, the precise conditions for optimal convergence when using hph p-refinement ( pp denotes the polynomial order of the approximation space) were shown in [24]. Under the assumption that the solution operator for Helmholtz problems is polynomially bounded in kk, it is shown that quasi-optimality is obtained under the conditions that kh//pk h / p is sufficiently small and the polynomial degree pp is at least O(log k)O(\log k).
Another way to obtain absolute stability (i.e. stability without, or under mild, conditions on the mesh size) of the approximate scheme is to use stabilization. The continuous interior
penalty stabilization (CIP) was introduced for the Helmholtz problem in [26], where stability was shown in the kh≲1k h \lesssim 1 regime, and was subsequently used to obtain error bounds for standard piecewise affine elements when k^(3)h^(2)≲1k^{3} h^{2} \lesssim 1. It was then shown in [11 that, in the one dimensional case, the CIP stabilization can also be used to eliminate the pollution error, provided the penalty parameter is appropriately chosen. When deriving error estimates for the stabilized FEM that we herein introduce, we shall make use of the mild condition kh≲1k h \lesssim 1. To keep down the technical detail we restrict the analysis to the case of piecewise affine finite element spaces, but the extension of the proposed method to the high order case follows using the stabilization operators suggested in 5 (see also [7] for a discussion of the analysis in the ill-posed case).
From the point of view of applications, unique continuation problems often arise in control theory and inverse scattering problems. For instance, the above problem could arise when the acoustic wave field uu is measured on omega\omega and there are unknown scatterers present outside Omega\Omega.
2. Continuum stability estimates
Our stabilized FEM will build on certain variations of the basic estimate (2), with the constants independent of the wave number, and we derive these estimates in the present section. The proofs are based on a Carleman estimate that is a variation of [17, Lemma 2.2] but we give a self-contained proof for the convenience of the reader. In 17] the Carleman estimate was used to derive a so-called increased stability estimate under suitable convexity assumptions on the geometry. To be more precise, let Gamma sub del Omega\Gamma \subset \partial \Omega be such that Gamma sub del omega\Gamma \subset \partial \omega and Gamma\Gamma is at some positive distance away from del omega nn Omega\partial \omega \cap \Omega. For a compact subset SS of the open set Omega\Omega, let P(nu;d)P(\nu ; d) denote the half space which has distance dd from SS and nu\nu as the exterior normal vector. Let Omega(nu;d)=P(nu;d)nn Omega\Omega(\nu ; d)=P(\nu ; d) \cap \Omega and denote by BB the union of the sets Omega(nu;d)\Omega(\nu ; d) over all nu\nu for which P(nu;d)nn del Omega sub GammaP(\nu ; d) \cap \partial \Omega \subset \Gamma. This geometric setting is exemplified by Figure 3a and it is illustrated in a general way in Figures 1 and 2 of [17] where BB is denoted by Omega(Gamma;d)\Omega(\Gamma ; d). Under these assumptions it was proven that
where F=||u||_(H^(1)(omega))+||Delta u+k^(2)u||_(L^(2)(Omega))F=\|u\|_{H^{1}(\omega)}+\left\|\Delta u+k^{2} u\right\|_{L^{2}(\Omega)} and the constants CC and alpha\alpha are independent of kk. Here FF can be interpreted as the size of the data in the unique continuation problem and the H^(1)H^{1}-norm of uu as an a priori bound. As kk grows, the first term on the right-hand side of (7) dominates the second one, and the stability is increasing in this sense.
As our focus is on designing a finite element method, we prefer to measure the size of the data in the weaker norm
Taking uu to be a plane wave solution to (1) suggests that
||u||_(L^(2)(B)) <= CkE+CE^(alpha)||u||_(L^(2)(Omega))^(1-alpha)\|u\|_{L^{2}(B)} \leq C k E+C E^{\alpha}\|u\|_{L^{2}(\Omega)}^{1-\alpha}
could be the right analogue of (7) when both the data and the a priori bound are in weaker norms. We show below, see Lemma 2, a stronger estimate with only the second term on the right-hand side.
Lemma 1 below captures the main step of the proof of our Carleman estimate. This is an elementary, but somewhat tedious, computation that establishes an identity similar to that in [23] where the constant in a Carleman estimate for the wave equation was studied. For an overview of Carleman estimates see [22, 25], the classical references are [15, Chapter 17] for second order elliptic equations, and [16, Chapter 28] for hyperbolic and more general equations. In the proofs, the idea is to use an exponential weight function e^(ℓ(x))e^{\ell(x)} and study the expression
Delta(e^(ℓ)w)=e^(ℓ)Delta w+" lower order terms "\Delta\left(e^{\ell} w\right)=e^{\ell} \Delta w+\text { lower order terms }
or the conjugated operator e^(-ℓ)Deltae^(ℓ)e^{-\ell} \Delta e^{\ell}. A typical approach is to study commutator estimates for the real and imaginary part of the principal symbol of the conjugated operator, see e.g. [22]. This can be seen as an alternative way to estimate the cross terms appearing in the proof of Lemma 1. Sometimes semiclassical analysis is used to derive the estimates, see e.g. [22]. This is very convenient when the estimates are shifted in the Sobolev scale, and we will use these techniques in Section 2.2 below.
2.1. A Carleman estimate and conditional Hölder stability. Denote by (*,*),|*|(\cdot, \cdot),|\cdot|, div,grad\operatorname{div}, \nabla and D^(2)D^{2} the inner product, norm, divergence, gradient and Hessian with respect to the Euclidean structure in Omega subR^(1+n)\Omega \subset \mathbb{R}^{1+n}. (Below, Lemma 1 and Corollary 1 are written so that they hold also when Omega\Omega is a Riemannian manifold and the above concepts are replaced with their Riemannian analogues.)
Lemma 1. Let k >= 0k \geq 0. Let ℓ,w inC^(2)(Omega)\ell, w \in C^{2}(\Omega) and sigma inC^(1)(Omega)\sigma \in C^{1}(\Omega). We define v=e^(ℓ)wv=e^{\ell} w, and
where R=(grad sigma,grad v)v+(div(a gradℓ)-a sigma)v^(2)R=(\nabla \sigma, \nabla v) v+(\operatorname{div}(a \nabla \ell)-a \sigma) v^{2}.
A proof of this result is given in A. In the present paper we use Lemma 1 only with the choice sigma=Deltaℓ\sigma=\Delta \ell, or equivalently a=0a=0, but the more general version of the lemma is useful when non-convex geometries are considered. In fact, instead of using a strictly convex function phi\phi as in Corollary 1 below, it is possible to use a function phi\phi without critical points, and convexify by taking ℓ=taue^(alpha phi)\ell=\tau e^{\alpha \phi} and sigma=Deltaℓ+alpha lambdaℓ\sigma=\Delta \ell+\alpha \lambda \ell for suitable constants alpha\alpha and lambda\lambda. In the present context this will lead to an estimate that is not robust with respect to kk, but we will use such a technique in the forthcoming paper [9].
Corollary 1 (Pointwise Carleman estimate). Let phi inC^(3)(Omega)\phi \in C^{3}(\Omega) be a strictly convex function without critical points, and choose rho > 0\rho>0 such that
D^(2)phi(X,X) >= rho|X|^(2),quad X inT_(x)Omega,x in OmegaD^{2} \phi(X, X) \geq \rho|X|^{2}, \quad X \in T_{x} \Omega, x \in \Omega
Let tau > 0\tau>0 and w inC^(2)(Omega)w \in C^{2}(\Omega). We define ℓ=tau phi,v=e^(ℓ)w\ell=\tau \phi, v=e^{\ell} w, and
where the constants a_(j),b_(j) > 0,j=0,1a_{j}, b_{j}>0, j=0,1, depend only on rho,i n f_(x in Omega)|grad phi(x)|^(2)\rho, \inf _{x \in \Omega}|\nabla \phi(x)|^{2} and s u p_(x in Omega)|grad(Delta phi(x))|^(2)\sup _{x \in \Omega}|\nabla(\Delta \phi(x))|^{2}.
Proof. We employ the equality in Lemma 1 with ℓ=tau phi\ell=\tau \phi and sigma=Deltaℓ\sigma=\Delta \ell. With this choice of sigma\sigma, it holds that a=0a=0. As the two first terms on the right-hand side of the equality are positive, it is enough to consider
The above Carleman estimate implies an inequality that is similar to the three-ball inequality, see e.g. [1]. The main difference is that here the foliation along spheres is followed in the opposite direction, i.e. the convex direction.
When continuing the solution inside the convex hull of omega\omega as in [17], we consider for simplicity a specific geometric setting defined in Corollary 2 below and illustrated in Figure 1. The stability estimates we prove below in Corollary 2 and Corollary 3, and Lemma 2 also hold in other geometric settings in which BB is included in the convex hull of omega\omega and B\\omegaB \backslash \omega does not touch the boundary of Omega\Omega, such as the one in Figure 3a. We prove this in Example 1.
Proof. Choose sqrt(r^(2)+beta^(2)) < s < rho\sqrt{r^{2}+\beta^{2}}<s<\rho and observe that del Omega\\B(y,s)sub bar(omega)\partial \Omega \backslash B(y, s) \subset \bar{\omega}. Define phi(x)=|x-y|^(2)\phi(x)=|x-y|^{2}. Then phi\phi is smooth and strictly convex in bar(Omega)\bar{\Omega}, and it does not have critical points there.
Choose chi inC_(0)^(oo)(Omega)\chi \in C_{0}^{\infty}(\Omega) such that chi=1\chi=1 in Omega\\(B(y,s)uu omega)\Omega \backslash(B(y, s) \cup \omega) and set w=chi uw=\chi u. Corollary 1 implies that for large tau > 0\tau>0
{:(8)int_(Omega)(tau^(3)w^(2)+tau|grad w|^(2))e^(2tau phi)dx <= Cint_(Omega)(Delta w+k^(2)w)^(2)e^(2tau phi)dx:}\begin{equation*}
\int_{\Omega}\left(\tau^{3} w^{2}+\tau|\nabla w|^{2}\right) e^{2 \tau \phi} d x \leq C \int_{\Omega}\left(\Delta w+k^{2} w\right)^{2} e^{2 \tau \phi} d x \tag{8}
\end{equation*}
a result also stated, without a detailed proof, in [20[20, Exercise 3.4.6 ]]. The commutator [Delta,chi][\Delta, \chi] vanishes outside B(y,s)uu omegaB(y, s) \cup \omega and phi < s^(2)\phi<s^{2} in B(y,s)B(y, s). Hence the right-hand side of (8) is bounded by a constant times
where q=(beta+R)^(2)-rho^(2)q=(\beta+R)^{2}-\rho^{2} and p=rho^(2)-s^(2) > 0p=\rho^{2}-s^{2}>0. The claim follows from [22, Lemma 5.2].
Corollary 3. Let omega sub B sub Omega\omega \subset B \subset \Omega be defined as in Corollary 2. Then there are C > 0C>0 and alpha in(0,1)\alpha \in(0,1) such that
Proof. Let omega_(1)sub omega sub B subOmega_(1)sub Omega\omega_{1} \subset \omega \subset B \subset \Omega_{1} \subset \Omega, denote for brevity by L\mathcal{L} the operator Delta+k^(2)\Delta+k^{2}, and consider the following auxiliary problem
{:[Lw=Lu quad" in "Omega_(1)],[del_(n)w+ikw=0quad" on "delOmega_(1)]:}\begin{aligned}
\mathcal{L} w & =\mathcal{L} u \quad \text { in } \Omega_{1} \\
\partial_{n} w+\mathrm{i} k w & =0 \quad \text { on } \partial \Omega_{1}
\end{aligned}
whose solution satisfies the estimate [3, Corollary 1.10]
||grad w||_(L^(2)(Omega_(1)))+k||w||_(L^(2)(Omega_(1))) <= Ck||Lu||_(H^(-1)(Omega_(1)))\|\nabla w\|_{L^{2}\left(\Omega_{1}\right)}+k\|w\|_{L^{2}\left(\Omega_{1}\right)} \leq C k\|\mathcal{L} u\|_{H^{-1}\left(\Omega_{1}\right)}
which gives
||w||_(H^(1)(Omega_(1))) <= Ck||Lu||_(H^(-1)(Omega))\|w\|_{H^{1}\left(\Omega_{1}\right)} \leq C k\|\mathcal{L} u\|_{H^{-1}(\Omega)}
For v=u-wv=u-w we have Lv=0\mathcal{L} v=0 in Omega_(1)\Omega_{1}. The stability estimate in Corollary 2 used for omega_(1),B,Omega_(1)\omega_{1}, B, \Omega_{1} reads as
Now we choose a cutoff function chi inC_(0)^(oo)(omega)\chi \in C_{0}^{\infty}(\omega) such that chi=1\chi=1 in omega_(1)\omega_{1} and chi u\chi u satisfies
L(chi u)=chiLu+[L,chi]u,quaddel_(n)(chi u)+ik(chi u)=0" on "del omega.\mathcal{L}(\chi u)=\chi \mathcal{L} u+[\mathcal{L}, \chi] u, \quad \partial_{n}(\chi u)+i k(\chi u)=0 \text { on } \partial \omega .
Since the commutator [L,chi][\mathcal{L}, \chi] is of first order, using again [3, Corollary 1.10] we obtain
The same argument for Omega_(1)sub Omega\Omega_{1} \subset \Omega gives
||u||_(H^(1)(Omega_(1))) <= Ck(||u||_(L^(2)(Omega))+||Lu||_(H^(-1)(Omega))),\|u\|_{H^{1}\left(\Omega_{1}\right)} \leq C k\left(\|u\|_{L^{2}(\Omega)}+\|\mathcal{L} u\|_{H^{-1}(\Omega)}\right),
thus leading to the conclusion.
2.2. Shifted three-ball inequality. In this section we prove an estimate as in Corollary 2, but with the Sobolev indices shifted down one degree, and our starting point is again the Carleman estimate in Corollary 1. When shifting Carleman estimates, as we want to keep track of the large parameter tau\tau, it is convenient to use the semiclassical version of pseudodifferential calculus. We write ℏ > 0\hbar>0 for the semiclassical parameter that satisfies ℏ=1//tau\hbar=1 / \tau.
The semiclassical (pseudo)differential operators are (pseudo)differential operators where, roughly speaking, each derivative is multiplied by ℏ\hbar, for the precise definition see Section 4.1 of [27]. The scale of semiclassical Bessel potentials is defined by
J^(s)=(1-ℏ^(2)Delta)^(s//2),quad s inRJ^{s}=\left(1-\hbar^{2} \Delta\right)^{s / 2}, \quad s \in \mathbb{R}
Then a semiclassical differential operator of order mm is continuous from H_(scl)^(m+s)(R^(n))H_{\mathrm{scl}}^{m+s}\left(\mathbb{R}^{n}\right) to H_(scl)^(s)(R^(n))H_{\mathrm{scl}}^{s}\left(\mathbb{R}^{n}\right), see e.g. Section 8.3 of [27].
We will give a shifting argument that is similar to that in Section 4 of [12]. To this end, we need the following pseudolocal and commutator estimates for semiclassical pseudodifferential operators, see e.g. (4.8) and (4.9) of [12]. Suppose that psi,chi inC_(0)^(oo)(R^(n))\psi, \chi \in C_{0}^{\infty}\left(\mathbb{R}^{n}\right) and that chi=1\chi=1
near supp(psi)\operatorname{supp}(\psi), and let A,BA, B be two semiclassical pseudodifferential operators of orders s,ms, m, respectively. Then for all p,q,N inRp, q, N \in \mathbb{R}, there is C > 0C>0
Both these estimates follow from the composition calculus, see e.g. [27, Theorem 4.12].
Let phi\phi be as in Corollary 1 and set ℓ=phi//ℏ\ell=\phi / \hbar and sigma=Deltaℓ\sigma=\Delta \ell in Lemma 1. Then
Write P=e^(phi//ℏ)ℏ^(2)Deltae^(-phi//ℏ)P=e^{\phi / \hbar} \hbar^{2} \Delta e^{-\phi / \hbar} and let v inC_(0)^(oo)(Omega^('))v \in C_{0}^{\infty}\left(\Omega^{\prime}\right) where Omega^(')subR^(n)\Omega^{\prime} \subset \mathbb{R}^{n} is open and bounded, and bar(Omega)subOmega^(')\bar{\Omega} \subset \Omega^{\prime}. Then, rescaling by ℏ^(4)\hbar^{4},
Let chi,psi inC_(0)^(oo)(Omega^('))\chi, \psi \in C_{0}^{\infty}\left(\Omega^{\prime}\right) and suppose that psi=1\psi=1 near Omega\Omega and chi=1\chi=1 near supp(psi)\operatorname{supp}(\psi). Then for v inC_(0)^(oo)(Omega)v \in C_{0}^{\infty}(\Omega),
Take now s=-1s=-1 and let the cutoff chi\chi and the weight phi\phi be as in the proof of Corollary 2, with the additional condition on chi\chi such that there is psi inC_(0)^(oo)(B(y,s)uu omega)\psi \in C_{0}^{\infty}(B(y, s) \cup \omega) satisfying psi=1\psi=1 in supp([P,chi])\operatorname{supp}([P, \chi]).
Let u inC^(oo)(R^(n))u \in C^{\infty}\left(\mathbb{R}^{n}\right) and set w=e^(phi//ℏ)uw=e^{\phi / \hbar} u. Then the previous estimate becomes
Using the norm inequality ||*||_(H_(scl)^(-1)(R^(n))) <= Cℏ^(-2)||*||_(H^(-1)(R^(n)))\|\cdot\|_{H_{\mathrm{scl}}^{-1}\left(\mathbb{R}^{n}\right)} \leq C \hbar^{-2}\|\cdot\|_{H^{-1}\left(\mathbb{R}^{n}\right)}, we thus obtain
for small enough ℏ > 0\hbar>0. Absorbing the negative power of ℏ\hbar in the exponential, and using [22, Lemma 5.2], we conclude the proof of the following result.
Lemma 2. Let omega sub B sub Omega\omega \subset B \subset \Omega be defined as in Corollary 2. Then there are C > 0C>0 and alpha in(0,1)\alpha \in(0,1) such that
We aim to solve the unique continuation problem for the Helmholtz equation
{:(14)Delta u+k^(2)u=-f" in "Omega","quad u=q|_(omega)",":}\begin{equation*}
\Delta u+k^{2} u=-f \text { in } \Omega, \quad u=\left.q\right|_{\omega}, \tag{14}
\end{equation*}
where omega sub Omega subR^(1+n)\omega \subset \Omega \subset \mathbb{R}^{1+n} are open, f inH^(-1)(Omega)f \in H^{-1}(\Omega) and q inL^(2)(omega)q \in L^{2}(\omega) are given. Following the optimization based approach in [5, 8] we will make use of the continuum stability estimates in Section 2 when deriving error estimates for the finite element approximation.
3.1. Discretization. Consider a family T={T_(h)}_(h > 0)\mathcal{T}=\left\{\mathcal{T}_{h}\right\}_{h>0} of triangulations of Omega\Omega consisting of simplices such that the intersection of any two distinct ones is either a common vertex, a common edge or a common face. Also, assume that the family T\mathcal{T} is quasi-uniform. Let
V_(h)={u in C(( bar(Omega))):u|_(K)inP_(1)(K),K inT_(h)}V_{h}=\left\{u \in C(\bar{\Omega}):\left.u\right|_{K} \in \mathbb{P}_{1}(K), K \in \mathcal{T}_{h}\right\}
be the H^(1)H^{1}-conformal approximation space based on the P_(1)\mathbb{P}_{1} finite element and let
Consider the orthogonal L^(2)L^{2}-projection Pi_(h):L^(2)(Omega)rarrV_(h)\Pi_{h}: L^{2}(\Omega) \rightarrow V_{h}, which satisfies
{:[(u-Pi_(h)u,v)_(L^(2)(Omega))=0","quad u inL^(2)(Omega)","v inV_(h)],[||Pi_(h)u||_(L^(2)(Omega)) <= ||u||_(L^(2)(Omega))","quad u inL^(2)(Omega)]:}\begin{aligned}
\left(u-\Pi_{h} u, v\right)_{L^{2}(\Omega)} & =0, \quad u \in L^{2}(\Omega), v \in V_{h} \\
\left\|\Pi_{h} u\right\|_{L^{2}(\Omega)} & \leq\|u\|_{L^{2}(\Omega)}, \quad u \in L^{2}(\Omega)
\end{aligned}
and the Scott-Zhang interpolator pi_(h):H^(1)(Omega)rarrV_(h)\pi_{h}: H^{1}(\Omega) \rightarrow V_{h}, that preserves vanishing Dirichlet boundary conditions. Both operators have the following stability and approximation properties, see e.g. [13, Chapter 1],
where i=pi,Pi,k=1,2i=\pi, \Pi, k=1,2 and m=0,k-1m=0, k-1.
The regularization on the discrete level will be based on the L^(2)L^{2}-control of the gradient jumps over elements edges using the jump stabilizer
J(u,u)=sum_(F inF_(h))int_(F)h[[n*grad u]]^(2)ds,quad u inV_(h)\mathcal{J}(u, u)=\sum_{F \in \mathcal{F}_{h}} \int_{F} h \llbracket n \cdot \nabla u \rrbracket^{2} d s, \quad u \in V_{h}
where F_(h)\mathcal{F}_{h} is the set of all internal faces, and the jump over F inF_(h)F \in \mathcal{F}_{h} is given by
[[n*grad u]]_(F)=n_(1)*grad u|_(K_(1))+n_(2)*grad u|_(K_(2)),\llbracket n \cdot \nabla u \rrbracket_{F}=\left.n_{1} \cdot \nabla u\right|_{K_{1}}+\left.n_{2} \cdot \nabla u\right|_{K_{2}},
with K_(1),K_(2)inT_(h)K_{1}, K_{2} \in \mathcal{T}_{h} being two simplices such that K_(1)nnK_(2)=FK_{1} \cap K_{2}=F, and n_(j)n_{j} the outward normal of K_(j),j=1,2K_{j}, j=1,2. The face subscript is omitted when there is no ambiguity.
Lemma 3. There is C > 0C>0 such that all u inV_(h),v inH_(0)^(1)(Omega),w inH^(2)(Omega)u \in V_{h}, v \in H_{0}^{1}(\Omega), w \in H^{2}(\Omega) and h > 0h>0 satisfy
{:[(17)(grad u","grad v)_(L^(2)(Omega)) <= CJ(u","u)^(1//2)(h^(-1)||v||_(L^(2)(Omega))+||v||_(H^(1)(Omega)))],[(18)J(i_(h)w,i_(h)w) <= Ch^(2)||w||_(H^(2)(Omega))^(2)","quad i in{pi","Pi}.]:}\begin{align*}
(\nabla u, \nabla v)_{L^{2}(\Omega)} & \leq C \mathcal{J}(u, u)^{1 / 2}\left(h^{-1}\|v\|_{L^{2}(\Omega)}+\|v\|_{H^{1}(\Omega)}\right) \tag{17}\\
\mathcal{J}\left(i_{h} w, i_{h} w\right) & \leq C h^{2}\|w\|_{H^{2}(\Omega)}^{2}, \quad i \in\{\pi, \Pi\} . \tag{18}
\end{align*}
Proof. See [10, Lemma 2] when the interpolator is pi_(h)\pi_{h}. Since this proof uses just the approximation properties of pi_(h)\pi_{h}, it holds verbatim for Pi_(h)\Pi_{h}.
where ||*||_(omega)\|\cdot\|_{\omega} denotes ||*||_(L^(2)(omega))\|\cdot\|_{L^{2}(\omega)}, and ss and s^(**)s^{*} are stabilizing (regularizing) terms for the primal and dual variables that should be consistent and vanish at optimal rates. The stabilization must control certain residual quantities representing the data of the error equation. The primal stabilizer will be based on the continuous interior penalty given by J\mathcal{J}. It must take into account the zeroth order term of the Helmholtz operator. The dual variable can be stabilized in the H^(1)H^{1}-seminorm. Notice that when the PDE-constraint is satisfied, z=0z=0 is the solution for the dual variable of the saddle point, thus the stabilizer s^(**)s^{*} is consistent. Hence we make the following choice
For a detailed presentation of such discrete stabilizing operators we refer the reader to [5] or [7]. We define on V_(h)V_{h} and W_(h)W_{h}, respectively, the norms
||u||_(V)=s(u,u)^(1//2),quad u inV_(h),quad||z||_(W)=s^(**)(z,z)^(1//2),quad z inW_(h)\|u\|_{V}=s(u, u)^{1 / 2}, \quad u \in V_{h}, \quad\|z\|_{W}=s^{*}(z, z)^{1 / 2}, \quad z \in W_{h}
together with the norm on V_(h)xxW_(h)V_{h} \times W_{h} defined by
Since A[(u,z),(u,-z)]=||u||_(omega)^(2)+||u||_(V)^(2)+||z||_(W)^(2)A[(u, z),(u,-z)]=\|u\|_{\omega}^{2}+\|u\|_{V}^{2}+\|z\|_{W}^{2} we have the following inf-sup condition
that guarantees a unique solution in V_(h)xxW_(h)V_{h} \times W_{h} for (19).
3.2. Error estimates. We start by deriving some lower and upper bounds for the norm ||*||_(V)\|\cdot\|_{V}. For u_(h)inV_(h),z inH_(0)^(1)(Omega)u_{h} \in V_{h}, z \in H_{0}^{1}(\Omega), we use (17) to bound
where ||u||_(**)\|u\|_{*} is defined as in (6).
Lemma 4. Let u inH^(2)(Omega)u \in H^{2}(\Omega) be the solution to (14) and (u_(h),z_(h))inV_(h)xxW_(h)\left(u_{h}, z_{h}\right) \in V_{h} \times W_{h} be the solution to (19). Then there exists C > 0C>0 such that for all h in(0,1)h \in(0,1)
||∣(u_(h)-Pi_(h)u,z_(h))|| <= Ch||u||_(**)\left\|\mid\left(u_{h}-\Pi_{h} u, z_{h}\right)\right\| \leq C h\|u\|_{*}
Proof. Due to the inf-sup condition (20) it is enough to prove that for (v,w)inV_(h)xxW_(h)(v, w) \in V_{h} \times W_{h},
A[(u_(h)-Pi_(h)u,z_(h)),(v,w)] <= Ch||u||_(**)||||(v,w)||.A\left[\left(u_{h}-\Pi_{h} u, z_{h}\right),(v, w)\right] \leq C h\|u\|_{*}\| \|(v, w) \| .
The weak form of (14) implies that
A[(u_(h)-Pi_(h)u,z_(h)),(v,w)]=(u-Pi_(h)u,v)_(omega)+G(u-Pi_(h)u,w)-s(Pi_(h)u,v).A\left[\left(u_{h}-\Pi_{h} u, z_{h}\right),(v, w)\right]=\left(u-\Pi_{h} u, v\right)_{\omega}+G\left(u-\Pi_{h} u, w\right)-s\left(\Pi_{h} u, v\right) .
Using (16) we bound the first term to get
(u-Pi_(h)u,v)_(omega) <= Ch^(2)||u||_(H^(2)(Omega))||v||_(omega)\left(u-\Pi_{h} u, v\right)_{\omega} \leq C h^{2}\|u\|_{H^{2}(\Omega)}\|v\|_{\omega}
For the second term we use the L^(2)L^{2}-orthogonality property of Pi_(h)\Pi_{h}, and (16) to obtain
G(u-Pi_(h)u,w)=(grad(u-Pi_(h)u),grad w)_(L^(2)(Omega)) <= Ch||w||_(W)||u||_(H^(2)(Omega)),G\left(u-\Pi_{h} u, w\right)=\left(\nabla\left(u-\Pi_{h} u\right), \nabla w\right)_{L^{2}(\Omega)} \leq C h\|w\|_{W}\|u\|_{H^{2}(\Omega)},
while for the last term we employ (22) to estimate
s(Pi_(h)u,v) <= ||Pi_(h)u||_(V)||v||_(V) <= Ch||u||_(**)||v||_(V)s\left(\Pi_{h} u, v\right) \leq\left\|\Pi_{h} u\right\|_{V}\|v\|_{V} \leq C h\|u\|_{*}\|v\|_{V}◻\square
Theorem 1. Let omega sub B sub Omega\omega \subset B \subset \Omega be defined as in Corollary 2. Let u inH^(2)(Omega)u \in H^{2}(\Omega) be the solution to (14) and (u_(h),z_(h))inV_(h)xxW_(h)\left(u_{h}, z_{h}\right) \in V_{h} \times W_{h} be the solution to (19). Then there are C > 0C>0 and alpha in(0,1)\alpha \in(0,1) such that for all k,h > 0k, h>0 with kh≲1k h \lesssim 1
Proof. Consider the residual (:r,w:)=G(u_(h)-u,w)=G(u_(h),w)-(:f,w:),w inH_(0)^(1)(Omega)\langle r, w\rangle=G\left(u_{h}-u, w\right)=G\left(u_{h}, w\right)-\langle f, w\rangle, w \in H_{0}^{1}(\Omega). Taking v=0v=0 in (19) we get G(u_(h),w)=(:f,w:)+s^(**)(z_(h),w),w inW_(h)G\left(u_{h}, w\right)=\langle f, w\rangle+s^{*}\left(z_{h}, w\right), w \in W_{h} which implies that
Theorem 2. Let omega sub B sub Omega\omega \subset B \subset \Omega be defined as in Corollary 2. Let u inH^(2)(Omega)u \in H^{2}(\Omega) be the solution to (14) and (u_(h),z_(h))inV_(h)xxW_(h)\left(u_{h}, z_{h}\right) \in V_{h} \times W_{h} be the solution to (19). Then there are C > 0C>0 and alpha in(0,1)\alpha \in(0,1) such that for all k,h > 0k, h>0 with kh≲1k h \lesssim 1
Proof. We employ a similar argument as in the proof of Theorem 1 with the same estimates for the residual norm and the L^(2)L^{2}-errors in omega\omega and Omega\Omega, only now using the continuum estimate in Corollary 3 to obtain
{:[||u-u_(h)||_(H^(1)(B)) <= Ck(||u-u_(h)||_(L^(2)(omega))+||r||_(H^(-1)(Omega)))^(alpha)(||u-u_(h)||_(L^(2)(Omega))+||r||_(H^(-1)(Omega)))^(1-alpha)],[ <= Ckh^(alpha)(k^(-2)+h)^(1-alpha)||u||_(**)]:}\begin{aligned}
\left\|u-u_{h}\right\|_{H^{1}(B)} & \leq C k\left(\left\|u-u_{h}\right\|_{L^{2}(\omega)}+\|r\|_{H^{-1}(\Omega)}\right)^{\alpha}\left(\left\|u-u_{h}\right\|_{L^{2}(\Omega)}+\|r\|_{H^{-1}(\Omega)}\right)^{1-\alpha} \\
& \leq C k h^{\alpha}\left(k^{-2}+h\right)^{1-\alpha}\|u\|_{*}
\end{aligned}
which ends the proof.
Let us remark that if we make the assumption k^(2)h≲1k^{2} h \lesssim 1 then the estimate in Theorem 2 becomes
and combining Theorem 1 and Theorem 2 we obtain the following result.
Corollary 4. Let omega sub B sub Omega\omega \subset B \subset \Omega be defined as in Corollary 2. Let u inH^(2)(Omega)u \in H^{2}(\Omega) be the solution to (14) and (u_(h),z_(h))inV_(h)xxW_(h)\left(u_{h}, z_{h}\right) \in V_{h} \times W_{h} be the solution to (19). Then there are C > 0C>0 and alpha in(0,1)\alpha \in(0,1) such that for all k,h > 0k, h>0 with k^(2)h≲1k^{2} h \lesssim 1
Comparing with the well-posed boundary value problem (3) and the sharp bounds (4) and (5), we note that the k^(-1)||u||_(**)k^{-1}\|u\|_{*} term in the above estimate is analogous to the well-posed case term ||f||_(L^(2)(Omega))\|f\|_{L^{2}(\Omega)}.
3.3. Data perturbations. The analysis above can also handle the perturbed data
tilde(q)=q+delta q,quad tilde(f)=f+delta f\tilde{q}=q+\delta q, \quad \tilde{f}=f+\delta f
with the unperturbed data qq, ff in (14), and perturbations delta q inL^(2)(omega),delta f inH^(-1)(Omega)\delta q \in L^{2}(\omega), \delta f \in H^{-1}(\Omega) measured by
Lemma 5. Let u inH^(2)(Omega)u \in H^{2}(\Omega) be the solution to the unperturbed problem (14) and (u_(h),z_(h))inV_(h)xxW_(h)\left(u_{h}, z_{h}\right) \in V_{h} \times W_{h} be the solution to the perturbed problem (23). Then there exists C > 0C>0 such that for all h in(0,1)h \in(0,1)
||∣(u_(h)-Pi_(h)u,z_(h))|| <= C(h||u||_(**)+delta(( tilde(q)),( tilde(f))))\left\|\mid\left(u_{h}-\Pi_{h} u, z_{h}\right)\right\| \leq C\left(h\|u\|_{*}+\delta(\tilde{q}, \tilde{f})\right)
Proof. Proceeding as in the proof of Lemma 4, the weak form gives
{:[A[(u_(h)-Pi_(h)u,z_(h)),(v,w)]=(u-Pi_(h)u,v)_(omega)+G(u-Pi_(h)u,w)-s(Pi_(h)u,v)],[+(delta q","v)_(omega)+(:delta f","w:)]:}\begin{aligned}
A\left[\left(u_{h}-\Pi_{h} u, z_{h}\right),(v, w)\right] & =\left(u-\Pi_{h} u, v\right)_{\omega}+G\left(u-\Pi_{h} u, w\right)-s\left(\Pi_{h} u, v\right) \\
& +(\delta q, v)_{\omega}+\langle\delta f, w\rangle
\end{aligned}
We bound the perturbation terms by
{:[(delta q","v)_(omega)+(:delta f","w:) <= ||delta q||_(omega)||v||_(omega)+C||delta f||_(H^(-1)(Omega))||w||_(W)],[ <= C delta( tilde(q)"," tilde(f))||(v","w)||]:}\begin{aligned}
(\delta q, v)_{\omega}+\langle\delta f, w\rangle & \leq\|\delta q\|_{\omega}\|v\|_{\omega}+C\|\delta f\|_{H^{-1}(\Omega)}\|w\|_{W} \\
& \leq C \delta(\tilde{q}, \tilde{f})\|(v, w)\|
\end{aligned}
and we conclude by using the previously derived bounds for the other terms.
Theorem 3. Let omega sub B sub Omega\omega \subset B \subset \Omega be defined as in Corollary 2. Let u inH^(2)(Omega)u \in H^{2}(\Omega) be the solution to the unperturbed problem (14) and (u_(h),z_(h))inV_(h)xxW_(h)\left(u_{h}, z_{h}\right) \in V_{h} \times W_{h} be the solution to the perturbed problem (23). Then there are C > 0C>0 and alpha in(0,1)\alpha \in(0,1) such that for all k,h > 0k, h>0 with kh≲1k h \lesssim 1
concludes the proof.
Theorem 4. Let omega sub B sub Omega\omega \subset B \subset \Omega be defined as in Corollary 2. Let u inH^(2)(Omega)u \in H^{2}(\Omega) be the solution to the unperturbed problem (14) and (u_(h),z_(h))inV_(h)xxW_(h)\left(u_{h}, z_{h}\right) \in V_{h} \times W_{h} be the solution to the perturbed problem (23). Then there are C > 0C>0 and alpha in(0,1)\alpha \in(0,1) such that for all k,h > 0k, h>0 with kh≲1k h \lesssim 1
and combining Theorem 3 and Theorem 4 gives the following.
Corollary 5. Let omega sub B sub Omega\omega \subset B \subset \Omega be defined as in Corollary 2. Let u inH^(2)(Omega)u \in H^{2}(\Omega) be the solution to the unperturbed problem (14) and (u_(h),z_(h))inV_(h)xxW_(h)\left(u_{h}, z_{h}\right) \in V_{h} \times W_{h} be the solution to the perturbed problem (23). Then there are C > 0C>0 and alpha in(0,1)\alpha \in(0,1) such that for all k,h > 0k, h>0 with k^(2)h≲1k^{2} h \lesssim 1
We illustrate the above theoretical results for the unique continuation problem (14) with some numerical examples. Drawing on previous results in [5], we adjust the stabilizer in (19) with a fixed stabilization parameter gamma > 0\gamma>0 such that s(u,v)=gammaJ(u,v)+gammah^(2)k^(4)(u,v)_(L^(2)(Omega))s(u, v)=\gamma \mathcal{J}(u, v)+\gamma h^{2} k^{4}(u, v)_{L^{2}(\Omega)}. The error analysis stays unchanged under this rescaling. Various numerical experiments indicate that gamma=10^(-5)\gamma=10^{-5} is a near-optimal value for different kinds of geometries and solutions. The implementation of our method and all the computations have been carried out in FreeFem++ [14]. The domain Omega\Omega is the unit square, and the triangulation is uniform with alternating left and right diagonals, as shown in Figure 2. The mesh size is taken as the inverse square root of the number of nodes.
In the light of the convexity assumptions in Section 2, we shall consider two different geometric settings: one in which the data is continued in the convex direction, inside the convex hull of omega\omega, and one in which the solution is continued in the non-convex direction, outside the convex hull of omega\omega.
In the convex setting, given in Figure 3a, we take
for continuing the solution inside the convex hull of omega\omega. This example does not correspond exactly to the specific geometric setting in Corollary 2, but all the theoretical results are valid in this case as proven in Example 1. below.
Example 1. Let omega sub B sub Omega\omega \subset B \subset \Omega be defined by (24) (Figure 3a). Then the stability estimates in Corollary 2, Corollary 3 and Lemma 2 hold true.
Proof. Consider an extended rectangle tilde(Omega)sup Omega\tilde{\Omega} \supset \Omega such that the unit square Omega\Omega is centred horizontally and touches the upper side of tilde(Omega)\tilde{\Omega}, and tilde(omega)sup omega\tilde{\omega} \supset \omega and tilde(B)sup B\tilde{B} \supset B are defined as in Corollary 2. Choose a smooth cutoff function chi\chi such that chi=1\chi=1 in Omega\\omega\Omega \backslash \omega and chi=0\chi=0 in tilde(Omega)\\Omega\tilde{\Omega} \backslash \Omega. Applying now Corollary 2 for tilde(omega), tilde(B), tilde(Omega)\tilde{\omega}, \tilde{B}, \tilde{\Omega} and chi u\chi u we get
where we have used that the commutator [Delta,chi]u[\Delta, \chi] u is supported in omega\omega. A similar proof is valid for the estimates in Corollary 3 and Lemma 2.
Figure 2. Mesh example.
We will give results for two kinds of solutions: a Gaussian bump centred on the top side of the unit square Omega\Omega, given in Example 2, and a variation of the well-known Hamadard solution given in Example 3.
be a non-homogeneous solution of (14), i.e. f=-Delta u-k^(2)uf=-\Delta u-k^{2} u and q=u|_(omega)q=\left.u\right|_{\omega}.
Figure 4a shows that for Example 2, when k=10k=10, the numerical results strongly agree with the convergence rates expected from Theorem 1 and Theorem 2, and Lemma 4, i.e. sub-linear convergence for the relative error in the L^(2)L^{2} - and H^(1)H^{1}-norms, and quadratic convergence for J(u_(h),u_(h))\mathcal{J}\left(u_{h}, u_{h}\right). Although in Figure 4b we do obtain smaller errors and better than expected convergence rates when k=50k=50, various numerical experiments indicate that this example's behaviour when increasing the wave number kk is rather a particular one. For oscillatory solutions, such as those in Example 3, with fixed nn, or the homogeneous u=sin(kx//sqrt2)cos(ky//sqrt2)u=\sin (k x / \sqrt{2}) \cos (k y / \sqrt{2}), we have noticed that the stability deteriorates when increasing kk.
respectively shown in Figure 3b and Figure 3c, and we notice from Figure 5that the stability strongly deteriorates when one continues the solution outside the convex hull of omega\omega, as the error sizes and rates worsen.
We test the data perturbations by polluting ff and qq in (14) with uniformly distributed values in [-h,h][-h, h], respectively [-h^(2),h^(2)]\left[-h^{2}, h^{2}\right], on every node of the mesh. It can be seen in Figure 6 that the perturbations are visible for an O(h)O(h) amplitude, but not for an O(h^(2))O\left(h^{2}\right) one.
Let us recall that the stability estimates for the unique continuation problem are closely related to those for the notoriously ill-posed Cauchy problem, see e.g. [1] or [17]. It is of
Figure 3. Computational domains for Example 2.
Figure 4. Convergence in BB for Example 2 in the convex direction (24).
Figure 5. Convergence in BB for Example 2, k=10k=10.
Figure 6. Convergence in BB when perturbing ff and qq in Example 2 for (24), k=10k=10.
interest to consider the following variation of a well-known example due to Hadamard, since this example can be used to show that conditional Hölder stability is optimal for the unique continuation problem.
Example 3. Let n inNn \in \mathbb{N} and consider the Cauchy problem
{[Delta u+k^(2)u=0," in "Omega=(0","pi)xx(0","1)","],[u(x","0)=0," for "x in[0","pi]","],[u_(y)(x","0)=sin(nx)," for "x in[0","pi]","]:}\begin{cases}\Delta u+k^{2} u=0 & \text { in } \Omega=(0, \pi) \times(0,1), \\ u(x, 0)=0 & \text { for } x \in[0, \pi], \\ u_{y}(x, 0)=\sin (n x) & \text { for } x \in[0, \pi],\end{cases}
whose solution for n > kn>k is given by u=(1)/(sqrt(n^(2)-k^(2)))sin(nx)sinh(sqrt(n^(2)-k^(2))y)u=\frac{1}{\sqrt{n^{2}-k^{2}}} \sin (n x) \sinh \left(\sqrt{n^{2}-k^{2}} y\right), for n=kn=k by u=sin(kx)yu=\sin (k x) y, and for n < kn<k by u=(1)/(sqrt(k^(2)-n^(2)))sin(nx)sin(sqrt(k^(2)-n^(2))y)u=\frac{1}{\sqrt{k^{2}-n^{2}}} \sin (n x) \sin \left(\sqrt{k^{2}-n^{2}} y\right).
It can be seen in Figure 7a that the convergence rates agree with the ones predicted for the convex setting
i.e. sub-linear convergence for the relative error in the L^(2)L^{2} - and H^(1)H^{1}-norms, and quadratic convergence for J(u_(h),u_(h))\mathcal{J}\left(u_{h}, u_{h}\right), although one can notice that the values of the jump stabilizer J(u_(h),u_(h))\mathcal{J}\left(u_{h}, u_{h}\right) visibly increase compared to Example 2.
When continuing the solution in the non-convex direction, the stability strongly deteriorates and for coarse meshes the numerical approximation doesn't reach the convergence regime, as it can be seen in Figure 7b for the non-convex setting
Example 4. Consider the geometry Omega=(0,1)^(2),omega=(0,1)xx(0,epsilon)\Omega=(0,1)^{2}, \omega=(0,1) \times(0, \epsilon) and B=(0,1)xx(0,1-epsilon)B=(0,1) \times(0,1-\epsilon), and the ansatz u(x,y)=e^(ikx)a(x,y)u(x, y)=e^{i k x} a(x, y). Let n inNn \in \mathbb{N} and a(x,y)=a_(0)(x,y)+k^(-1)a_(-1)(x,y)+dots+a(x, y)=a_{0}(x, y)+k^{-1} a_{-1}(x, y)+\ldots+
(a) Convex direction (27). Circles: H^(1)H^{1}-error, rate ~~0.94\approx 0.94; squares: L^(2)L^{2}-error, rate ~~0.83\approx 0.83; down triangles: h^(-1)J(u_(h),u_(h))h^{-1} \mathcal{J}\left(u_{h}, u_{h}\right), rate ~~1\approx 1; up triangles: ||z||_(W)\|z\|_{W}, rate ~~1.6\approx 1.6.
(b) Non-convex direction (28). Circles: H^(1)H^{1} error; squares: L^(2)L^{2}-error; down triangles: h^(-1)J(u_(h),u_(h))h^{-1} \mathcal{J}\left(u_{h}, u_{h}\right); up triangles: ||z||_(W)\|z\|_{W}.
Figure 7. Convergence in BB for Example 3, k=10,n=12k=10, n=12. k^(-n)a_(-n)(x,y)k^{-n} a_{-n}(x, y). We have that
Delta u+k^(2)u=e^(ikx)(2ikdel_(x)a+Delta a)\Delta u+k^{2} u=e^{i k x}\left(2 i k \partial_{x} a+\Delta a\right)
and we choose a_(j),j=0,dots,-na_{j}, j=0, \ldots,-n such that
{:(29)del_(x)a_(0)=0","quad2idel_(x)a_(j)+Deltaa_(j+1)=0","quad-j=1","dots","n:}\begin{equation*}
\partial_{x} a_{0}=0, \quad 2 i \partial_{x} a_{j}+\Delta a_{j+1}=0, \quad-j=1, \ldots, n \tag{29}
\end{equation*}
Then
Delta u+k^(2)u=e^(ikx)k^(-n)Deltaa_(-n)\Delta u+k^{2} u=e^{i k x} k^{-n} \Delta a_{-n}
and ||Delta u+k^(2)u||_(L^(2)(Omega))=k^(-n)||Deltaa_(-N)||_(L^(2)(Omega))\left\|\Delta u+k^{2} u\right\|_{L^{2}(\Omega)}=k^{-n}\left\|\Delta a_{-N}\right\|_{L^{2}(\Omega)}. Since a_(j),j=0,dots,-na_{j}, j=0, \ldots,-n, are independent of kk we obtain
We can solve (29) such that a_(0)(x,y)=a_(0)(y),supp(a_(0))sub(epsilon,1-epsilon)a_{0}(x, y)=a_{0}(y), \operatorname{supp}\left(a_{0}\right) \subset(\epsilon, 1-\epsilon) and supp(a)sub[0,1]xx(epsilon,1-epsilon)\operatorname{supp}(a) \subset[0,1] \times (\epsilon, 1-\epsilon). Then
u|_(omega)=0,quad" and "||u||_(H^(1)(B))=||u||_(H^(1)(Omega))=Ck,quad" for large "k.\left.u\right|_{\omega}=0, \quad \text { and }\|u\|_{H^{1}(B)}=\|u\|_{H^{1}(\Omega)}=C k, \quad \text { for large } k .
The estimate (2) then becomes
k <= Ck^(-alpha n)k^(1-alpha),quad" i.e. "k^(alpha(n+1)) <= Ck \leq C k^{-\alpha n} k^{1-\alpha}, \quad \text { i.e. } k^{\alpha(n+1)} \leq C
Choosing large nn we see that CC depends on kk, and for any N inN,C <= k^(N)N \in \mathbb{N}, C \leq k^{N} cannot hold.
Proof of Lemma 1. Recall the following identities for a function ww and vector fields XX and YY
where D_(X)D_{X} is the covariant derivative. Recall also that the Hessian is symmetric, i.e. D^(2)w(X,Y)=D^(2)w(Y,X)D^{2} w(X, Y)= D^{2} w(Y, X). We have
and it remains to study the cross terms b Delta vb \Delta v and bqvb q v.
Let us begin by studying beta Delta v\beta \Delta v where beta=-2(grad v,gradℓ)\beta=-2(\nabla v, \nabla \ell). We have
where c_(0)=|grad v|^(2)gradℓc_{0}=|\nabla v|^{2} \nabla \ell and R_(0)=(grad sigma,grad v)vR_{0}=(\nabla \sigma, \nabla v) v.
Let us now study the second cross term in (30). We have
whence, recalling that q=k^(2)+a+|gradℓ|^(2)q=k^{2}+a+|\nabla \ell|^{2} and -a=-sigma+Deltaℓ-a=-\sigma+\Delta \ell,
{:[(35)bqv=(-sigma q+div(q gradℓ))v^(2)+divc_(1)],[=(-|gradℓ|^(2)sigma+div(|gradℓ|^(2)gradℓ))v^(2)-k^(2)av^(2)+divc_(1)+R_(1)]:}\begin{align*}
b q v & =(-\sigma q+\operatorname{div}(q \nabla \ell)) v^{2}+\operatorname{div} c_{1} \tag{35}\\
& =\left(-|\nabla \ell|^{2} \sigma+\operatorname{div}\left(|\nabla \ell|^{2} \nabla \ell\right)\right) v^{2}-k^{2} a v^{2}+\operatorname{div} c_{1}+R_{1}
\end{align*}
where c_(1)=-qv^(2)gradℓc_{1}=-q v^{2} \nabla \ell and R_(1)=(div(a gradℓ)-a sigma)v^(2)R_{1}=(\operatorname{div}(a \nabla \ell)-a \sigma) v^{2}. The identity (31) with v=ℓv=\ell implies that
The claim follows by combining (36), (35), (34) and (30).
Acknowledgements. Erik Burman was supported by EPSRC grants EP/P01576X/1 and EP/P012434/1. Lauri Oksanen was supported by EPSRC grants EP/L026473/1 and EP/P01593X/1.
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Department of Mathematics, University College London, Gower Street, London UK, WC1E 6BT.
E-mail addresses: {e.burman, mihai.nechita.16, l.oksanen}@ucl.ac.uk.
Date: October 29, 2018.