Calderón problem. Mikko Salo


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1 Calderón problem Lecture notes, Spring 2008 Mikko Salo Department of Mathematics and Statistics University of Helsinki
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3 Contents Chapter 1. Introduction 1 Chapter 2. Multiple Fourier series Fourier series in L Sobolev spaces 11 Chapter 3. Uniqueness Reduction to Schrödinger equation Complex geometrical optics Uniqueness proof 26 Chapter 4. Stability Schrödinger equation More facts on Sobolev spaces Conductivity equation 37 Chapter 5. Partial data Carleman estimates Uniqueness with partial data 50 Bibliography 55 v
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5 CHAPTER 1 Introduction Electrical Impedance Tomography (EIT) is an imaging method with potential applications in medical imaging and nondestructive testing. The method is based on the following important inverse problem. Calderón problem: Is it possible to determine the electrical conductivity of a medium by making voltage and current measurements on its boundary? In this course we will prove a fundamental uniqueness result due to Sylvester and Uhlmann, which states that the conductivity is determined by the boundary measurements. We will also consider stable dependence of the conductivity on boundary measurements, and the case where measurements are only made on part of the boundary. In addition, we will discuss useful techniques in partial differential equations, Fourier analysis, and inverse problems. Let us begin by recalling the mathematical model of EIT, see [5] for details. The purpose is to determine the electrical conductivity γ(x) at each point x Ω, where Ω R n represents the body which is imaged (in practice n = 3). We assume that Ω is a bounded open subset of R n with C boundary, and that γ is a positive C 2 function in Ω. Under the assumption of no sources or sinks of current in Ω, a voltage potential f at the boundary Ω induces a voltage potential u in Ω, which solves the Dirichlet problem for the conductivity equation, (1.1) { γ u = 0 in Ω, u = f on Ω. Since γ is positive, there is a unique weak solution u H 1 (Ω) for any boundary value f H 1/2 ( Ω). One can define the Dirichlet to Neumann map (DN map) formally as Λ γ f = γ u. ν Ω 1
6 2 1. INTRODUCTION This is the current flowing through the boundary. More precisely, the DN map is defined weakly as (Λ γ f, g) Ω = γ u v dx, f, g H 1/2 ( Ω), Ω where u is the solution of (1.1), and v is any function in H 1 (Ω) with v Ω = g. The pairing on the boundary is integration with respect to the surface measure, (f, g) Ω = fg ds. With this definition Λ γ is a bounded linear map from H 1/2 ( Ω) into H 1/2 ( Ω). The Calderón problem (also called the inverse conductivity problem) is to determine the conductivity function γ from the knowledge of the map Λ γ. That is, if the measured current Λ γ f is known for all boundary voltages f H 1/2 ( Ω), one would like to determine the conductivity γ. There are several aspects of this inverse problem which are interesting both for mathematical theory and practical applications. Ω 1. Uniqueness. If Λ γ1 = Λ γ2, show that γ 1 = γ Reconstruction. Given the boundary measurements Λ γ, find a procedure to reconstruct the conductivity γ. 3. Stability. If Λ γ1 is close to Λ γ2, show that γ 1 and γ 2 are close (in a suitable sense). 4. Partial data. If Γ is a subset of Ω and if Λ γ1 f Γ = Λ γ2 f Γ for all boundary voltages f, show that γ 1 = γ 2. Starting from the work of Calderón in 1980, the inverse conductivity problem has been studied intensively. In the case where n 3 and all conductivities are in C 2 (Ω), the following positive results are an example of what can be proved. Theorem. (SylvesterUhlmann 1987) If Λ γ1 = Λ γ2, then γ 1 = γ 2 in Ω. Theorem. (Nachman 1988) There is a convergent algorithm for reconstructing γ from Λ γ. Theorem. (Alessandrini 1988) Let γ j H s (Ω) for s > n + 2, and 2 assume that γ j H s (Ω) M and 1/M γ j M (j = 1, 2). Then γ 1 γ 2 L (Ω) ω( Λ γ1 Λ γ2 H 1/2 ( Ω) H 1/2 ( Ω))
7 1. INTRODUCTION 3 where ω(t) = C log t σ for small t > 0, with C = C(Ω, M, n, s) > 0, σ = σ(n, s) (0, 1). Theorem. (KenigSjöstrandUhlmann 2007) Assume that Ω is convex and Γ is any open subset of Ω. If Λ γ1 f Γ = Λ γ2 f Γ for all f H 1/2 ( Ω), and if γ 1 Ω = γ 2 Ω, then γ 1 = γ 2 in Ω. During this course we will discuss the methods involved in these results. The main tool will be the construction of special solutions, called complex geometrical optics solutions, to the conductivity equation and related equations. This will involve Fourier analysis, and we will begin the course with a discussion of ndimensional Fourier series. References. This course a continuation of the class Impedanssitomografian perusteet (Principles of EIT) given by Petri Ola [5]. From [5] we will mainly use the solvability of the Dirichlet problem for elliptic equations, the definition of the DN map, and results which state that the boundary values of the conductivity can be recovered from the DN map. Chapter 2 on multiple Fourier series is classical, an excellent reference is Zygmund [8]. In Chapter 3 we prove the uniqueness result of SylvesterUhlmann [6]. The proof of the main estimate, Theorem 3.7, follows Hähner [4]. The stability question is taken up in Chapter 4, where the main results are due to Alessandrini [1]. The treatment also benefited from FeldmanUhlmann [3]. In the final Chapter 5 we introduce Carleman estimates and prove the result in BukhgeimUhlmann [2], which states that it is enough to measure currents on roughly half of the boundary to determine the conductivity.
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9 CHAPTER 2 Multiple Fourier series 2.1. Fourier series in L 2 Joseph Fourier laid the foundations of the mathematical field now known as Fourier analysis in his 1822 treatise on heat flow. The basic question is to represent periodic functions as sums of elementary pieces. If the period of f is 2π and the elementary pieces are sine and cosine functions, then the desired representation would be f(x) = (a k cos(kx) + b k sin(kx)). k=0 Since e ikx = cos(kx)+i sin(kx), we may alternatively consider the series (2.1) f(x) = c k e ikx. k= We will need to represent functions of n variables as Fourier series. If f is a function in R n which is 2πperiodic in each variable, then a natural analog of (2.1) would be f(x) = k Z n c k e ik x. This is the form of Fourier series which we will study. Note that the terms on the righthand side are 2πperiodic in each variable. There are many subtle issues related to various modes of convergence for the series above. However, we will mostly just need the case of convergence in L 2 norm for Fourier series of L 2 functions, and in this case no problems arise. Consider the cube Q = [ π, π] n, and define an inner product on L 2 (Q) by (f, g) = (2π) n fḡ dx, f, g L 2 (Q). Q With this inner product, L 2 (Q) is a separable infinitedimensional Hilbert space. The space of functions which are locally square integrable and 5
10 6 2. MULTIPLE FOURIER SERIES 2πperiodic in each variable may be identified with L 2 (Q). Therefore, we will consider Fourier series of functions in L 2 (Q). Lemma 2.1. The set {e ik x } is an orthonormal subset of L 2 (Q). Proof. A direct computation: if k, l Z n then (e ik x, e il x ) = (2π) n e i(k l) x dx = (2π) n π = π { 1, k = l, 0, k l. π π Q e i(k 1 l 1 )x1 e i(kn ln)xn dx n dx 1 We recall a Hilbert space fact: if {e j } j=1 is an orthonormal subset of a separable Hilbert space H, then the following are equivalent: (1) {e j } j=1 is an orthonormal basis, in the sense that any f H may be written as the series f = (f, e j )e j with convergence in H, (2) for any f H one has f 2 = j=1 (f, e j ) 2, j=1 (3) if f H and (f, e j ) = 0 for all j, then f 0. If the condition (3) is satisfied, the orthonormal system {e j } is called complete. The main point is that {e ik x } k Z n is complete in L 2 (Q). Lemma 2.2. If f L 2 (Q) satisfies (f, e ik x ) = 0 for all k Z n, then f 0. The proof is given below. The main result on Fourier series of L 2 functions is now immediate. Below we denote by l 2 (Z n ) the space of complex sequences c = (c k ) k Z n with norm ( ) 1/2. c l 2 (Z n ) = k Z n c k 2
11 2.1. FOURIER SERIES IN L 2 7 Theorem 2.3. If f L 2 (Q), then one has the Fourier series f(x) = k Z n ˆf(k)e ik x with convergence in L 2 (Q), where the Fourier coefficients are given by ˆf(k) = (f, e ik x ) = (2π) n f(x)e ik x dx. One has the Plancherel formula f 2 L 2 (Q) = ˆf(k) 2. k Z n Q Conversely, if c = (c k ) l 2 (Z n ), then the series f(x) = k Z n c k e ik x converges in L 2 (Q) to a function f satisfying ˆf(k) = c k. Proof. The facts on the Fourier series of f L 2 (Q) follow directly from the discussion above, since {e ik x } k Z n is a complete orthonormal system in L 2 (Q). For the converse, if (c k ) l 2 (Z n ), then k Zn M k N c k e ik x 2 L 2 (Q) = k Zn M k N c k 2 by orthogonality. Since the right hand side can be made arbitrarily small by choosing M and N large, we see that f N = k Z n, k N c ke ik x is a Cauchy sequence in L 2 (Q), and converges to f L 2 (Q). One obtains ˆf(k) = (f, e ik x ) = c k again by orthogonality. It remains to prove Lemma 2.2. We begin with the most familiar case, n = 1. The partial sums of the Fourier series of a function f L 2 ([ π, π]), extended as a 2πperiodic function into R, are given by S m f(x) = m k= m ˆf(k)e ikx = m k= m ( 1 π ) f(y)e iky dy e ikx 2π π = π π D m (x y)f(y) dy
12 8 2. MULTIPLE FOURIER SERIES where D m (x) is the Dirichlet kernel D m (x) = 1 2π m k= m = 1 ei(2m+1)x 1 2π e imx e ix 1 e ikx = 1 2π e imx (1 + e ix e i2mx ) = 1 e i(m+ 1 2 )x e i(m+ 1 2 )x = 1 sin((m + 1)x) 2 2π e i 1 2 x e i 1 2 x 2π sin( 1x). 2 Thus, definining the convolution of two 2πperiodic locally integrable functions by f g(x) = π π f(x y)g(y) dy, we see that S m f(x) = (D m f)(x). The Dirichlet kernel acts in a similar way as an approximate identity, but is problematic because it takes both positive and negative values. Definition. A sequence (K N (x)) N=1 of 2πperiodic continuous functions on the real line is called an approximate identity if (1) K N 0 for all N, (2) π K π N(x) dx = 1 for all N, and (3) for all δ > 0 one has lim sup N δ x π K N (x) 0. Thus, an approximate identity (K N ) for large N resembles a Dirac delta at 0, extended in a 2πperiodic way. It is possible to approximate L p functions by convolving them against an approximate identity. Lemma 2.4. Let (K N ) be an approximate identity. If f L p ([ π, π]) where 1 p <, or if f is a continuous 2πperiodic function and p =, then K N f f L p ([ π,π]) 0 as N. Proof. Since K N has integral 1, we have (K N f)(x) f(x) = π π K N (y)[f(x y) f(x)] dy
13 2.1. FOURIER SERIES IN L 2 9 Let first f be continuous and p =. To estimate the L norm of K N f f, we fix ε > 0 and compute π (K N f)(x) f(x) K N (y) f(x y) f(x) dy π K N (y) f(x y) f(x) dy+ K N (y) f(x y) f(x) dy. y δ Here δ > 0 is chosen so that δ y π f(x y) f(x) < ε whenever x R and y δ. 2 This is possible because f is uniformly continuous. Further, we use the definition of an approximate identity and choose N 0 so that ε sup K N (x) <, for N N 0. δ x π 4π f L With these choices, we obtain (K N f)(x) f(x) ε 2 y δ K N (y) dy + 4π f L sup K N (x) < ε δ x π whenever N N 0. The result is proved in the case p =. Let now f L p ([ π, π]) and 1 p <. We need the integral form of Minkowski s inequality, ( F (x, y) dν(y) p ) 1/p ( 1/p dµ(x) F (x, y) dµ(x)) p dν(y), X Y which is valid on σfinite measure spaces (X, µ) and (Y, ν), cf. the usual Minkowski inequality y F (, y) L p y F (, y) Lp. Using this, we obtain π K N f f L p ([ π,π]) K N (y) f( y) f L p ([ π,π]) dy π = K N (y) f( y) f L p dy + K N (y) f( y) f L p dy δ y π 4π f L p sup δ x π Y X y δ Now, for any ε > 0, there is δ > 0 such that K N (x) + sup f( y) f L p. y δ f( y) f L p ([ π,π]) < ε whenever y δ. 2 Thus the second term can be made arbitrarily small by choosing δ sufficiently small, and then the first term is also small if N is large. This shows the result.
14 10 2. MULTIPLE FOURIER SERIES Now, if the Dirichlet kernels (D m ) were an approximate identity, by Lemma 2.4 one would have S m f f in L 2 for any f L 2. This would in particular imply that any f L 2 which satisfies (f, e ikx ) = ˆf(k) = 0 for all k Z n, would be the zero function. However, D m is not an approximate identity because it takes negative values. One does get an approximate identity if a different summation method used: instead of the partial sums S m f consider the Cesàro sums σ N f(x) = 1 N + 1 N S m f(x). m=0 This can be written in convolution form as σ N f(x) = 1 N + 1 where F N is the Fejér kernel, F N (x) = = = = 1 2π(N + 1) N (D m f)(x) = (F N f)(x) m=0 N e i(m+ 1 2 )x e i(m+ 1 2 )x m=0 e i 1 2 x e i 1 2 x 1 e i 1 2 x ei(n+1)x 1 e i 1 e ix 2 x e i(n+1)x 1 1 e ix 1 2π(N + 1) e i 1 2 x e i 1 2 x 1 e i(n+1)x 1 + e i(n+1)x 1 2π(N + 1) (e i 1 2 x e i 1 2 x ) 2 1 sin 2 ( N+1x) 2 2π(N + 1) sin 2 ( 1x). 2 Clearly this is nonnegative, and in fact F N is an approximate identity (exercise). It follows from Lemma 2.4 that Cesàro sums of the Fourier series an L p function always converge in the L p norm if 1 p <. Lemma 2.5. If f L p ([ π, π]) where 1 p <, or if f is a continuous 2πperiodic function and p =, then σ N f f L p ([ π,π]) 0 as N. Proof of Lemma 2.2. We begin with the case n = 1. If f L 2 ([ π, π]) and (f, e ikx ) = 0 for all k Z, then S m f = 0 and also σ N f = 0 for all N. By Lemma 2.5 it follows that f 0.
15 2.2. SOBOLEV SPACES 11 Now let n 2, and assume that f L 2 (Q) and (f, e ik x ) = 0 for all k Z n. Since e ik x = e ik 1x1 e iknxn, we have π π h(x 1 ; k 2,..., k n )e ik 1x 1 dx 1 = 0 for all k 1 Z, where h(x 1 ; k 2,..., k n ) = f(x 1, x 2,..., x n )e i(k 2x k nx n) dx 2 dx n. [ π,π] n 1 Now h( ; k 2,..., k n ) is in L 2 ([ π, π]) by the CauchySchwarz inequality. By the completeness of the system {e ik 1x 1 } in one dimension, we obtain that h( ; k 2,..., k n ) = 0 for all k 2,..., k n Z. Applying the same argument in the other variables shows that f 0. We have now proved the main facts on Fourier series of L 2 functions Sobolev spaces In this section we wish to consider Sobolev spaces of periodic functions. In fact, most of the results given here will not be used in their present form, but they provide good motivation for the developments in Chapter 3. Let T n = R n /2πZ n be the ndimensional torus. Note that L 2 (Q) above may be identified with L 2 (T n ). However, C(Q) is different from C(T n ); in fact C(T n ) (resp. C (T n )) can be identified with the continuous (resp. C ) 2πperiodic functions in R n. First we need to define weak derivatives of periodic functions. This is similar to the nonperiodic case, except that here the test function space will be C (T n ). We use the notation D j = 1 i x j, D α = D α 1 1 D αn n. Definition. Let f L 2 (T n ). We say that D α f L 2 (T n ) if there is a function v L 2 (T n ) which satisfies fd α ϕ dx = ( 1) α vϕ dx T n T n for all ϕ C (T n ). In this case we define D α f = v. As in the nonperiodic case, weak derivatives are unique, and for smooth functions the definition coincides with the usual derivative.
16 12 2. MULTIPLE FOURIER SERIES This uses the fact that there are no boundary terms arising from integration by parts, because of periodicity. Definition. If m 0 is an integer, we denote by H m (T n ) the space of functions f L 2 (T n ) such that D α f L 2 (T n ) for all α N n satisfying α m. We equip H m (T n ) with the inner product (f, g) H m (T n ) = (D α f, D α g). α m Then H m (T n ) is a Hilbert space. If f and D α f are in L 2 (T n ), one may compute the Fourier coefficients of D α f to be (D α f)ˆ(k) = (2π) n T n D α f(x)e ik x dx = (2π) n ( 1) α T n f(x)d α (e ik x ) dx = k α ˆf(k) by the definition of weak derivative, since e ik x C (T n ). This motivates the following characterization of H m (T n ) in terms of Fourier coefficients. Lemma 2.6. Let f L 2 (T n ). Then f H m (T n ) if and only if k m ˆf l 2 (Z n ), where k = (1 + k k n ) 1/2. Proof. One has f H m (T n ) D α f L 2 (T n ) k α ˆf(k) l 2 (Z n ) for α m for α m (k 2 1,..., k 2 n) α ˆf(k) 2 l 1 (Z n ) for α m. If the last condition is satisfied, then k 2m ˆf(k) 2 = c β (k1, 2..., kn) 2 β ˆf(k) 2 l 1 (Z n ), β m consequently k m ˆf(k) l 2 (Z n ). Conversely, if k m ˆf(k) l 2 (Z n ), then k α ˆf(k) l 2 (Z n ) for α m because k j k. It is now easy to prove a version of the Sobolev embedding theorem. Theorem 2.7. If m > n/2 then H m (T n ) C(T n ).
17 2.2. SOBOLEV SPACES 13 Proof. Let f H m (T n ), so that k m ˆf l 2 (Z n ) and f(x) = k Z n ˆf(k)e ik x. Let M k = ˆf(k)e ik x = k m ( k m ˆf(k)). We have k Z n M k k m l 2 (Z n ) k m ˆf(k) l 2 (Z n ) <, by Lemma 2.6 and since m > n/2. Since the terms in the Fourier series of f are continuous functions, this Fourier series converges absolutely and uniformly into a continuous function in T n by the Weierstrass M test. The final result in this section will be elliptic regularity in the periodic case. Consider a second order differential operator P (D) acting on 2πperiodic functions in R n, P (D) = a α D α, α 2 where a α are complex constants. The principal part of P (D) is P 2 (D) = a α D α. α =2 We say that P (D) is elliptic if P 2 (D) has real coefficients, and P 2 (k) > 0 whenever k Z n {0}. The following proof also indicates how Fourier series are used in the solution of partial differential equations. Theorem 2.8. Let P (D) be an elliptic second order differential operator with constant coefficients, and assume that u L 2 (T n ) solves the equation P (D)u = f in T n, for some f L 2 (T n ). Then u H 2 (T n ). Proof. Taking the Fourier coefficients on both sides of P (D)u = f gives (2.2) P (k)û(k) = ˆf(k), k Z n. We have P 2 (k) = k 2 P 2 (k/ k ) c k 2
18 14 2. MULTIPLE FOURIER SERIES for some c > 0, by ellipticity. Then for k 0, n P (k) = P 2 (k) + a j k j + a 0 P 2 (k) ( j=1 n a j ) k a 0 j=1 c k 2 C k. If C > 0 is sufficiently large, it follows that P (k) 1 2 c k 2, for k C. From (2.2) we obtain û(k) = ˆf(k) 2 P (k) c k ˆf(k), k C. 2 Since ˆf(k) l 2 (Z n ) this shows that k 2 û(k) l 2 (Z n ), which implies u H 2 (T n ) as required.
19 CHAPTER 3 Uniqueness In this chapter, we will discuss the proof of the following uniqueness result of Sylvester and Uhlmann. Theorem 3.1. Let Ω R n be a bounded open set with smooth boundary, where n 3, and let γ 1 and γ 2 be two positive functions in C 2 (Ω). If Λ γ1 = Λ γ2, then γ 1 = γ 2 in Ω. In fact, this theorem will be reduced to a uniqueness result for the Schrödinger equation (also due to Sylvester and Uhlmann). Theorem 3.2. Let Ω R n be a bounded open set with smooth boundary, where n 3, and let q 1 and q 2 be two functions in L (Ω) such that the Dirichlet problems for +q 1 and +q 2 in Ω are well posed. If Λ q1 = Λ q2, then q 1 = q 2 in Ω. The reduction of Theorem 3.1 to Theorem 3.2 is presented in Section 3.1 along with the relevant definitions. The proof of the uniqueness results relies on complex geometrical optics (CGO) solutions, which are constructed in Section 3.2 for the Schrödinger equation by Fourier analysis and perturbation arguments. Section 3.3 includes an integral identity relating boundary measurements to interior information about the coefficients, and this identity is used to prove Theorem 3.2 by taking an asymptotic limit with suitable CGO solutions Reduction to Schrödinger equation The first step in the proof is the reduction of the conductivity equation to a Schrödinger equation, ( + q)u = 0 in Ω, where q is a function in L (Ω). This equation turns out to be easier to handle, since the principal part is the Laplacian. 15
20 16 3. UNIQUENESS Lemma 3.3. If γ C 2 (Ω) and u H 1 (Ω) then (3.1) γ (γ 1/2 u) = γ 1/2 ( + q)u in the weak sense, where q = γ γ. Proof. This is a direct computation: if u C 2 (Ω) then j (γ j ( 1 γ u)) = j ( γ j u) + j ( j ( γ)u) = γ 2 j u j ( γ) j u + j ( γ) j u + 2 j ( γ)u. The claim follows by taking the sum over j. The case where u H 1 (Ω) can be proved by approximation 1. If q L (Ω), we consider the Dirichlet problem for the Schrödinger equation, { ( + q)u = 0 in Ω, (3.2) u = f on Ω, where f H 1/2 ( Ω). We say that u H 1 (Ω) is a weak solution of (3.2) if u Ω = f, and if for all ϕ H0(Ω) 1 one has ( u ϕ + quϕ) dx = 0. Ω 1 Let (u k ) C 2 (Ω) be a sequence with u k u in H 1 (Ω). We have γ (γ 1/2 u k ) = γ 1/2 ( + q)u k. If a C 1 (Ω) then u au is a continuous map on H 1 (Ω), since au H1 (Ω) = au L2 (Ω)+ ( a)u+a u L2 (Ω) 2( a L (Ω)+ a L (Ω)) u H1 (Ω). Using that γ is in C 2 (Ω) and that : H m (Ω) H m 1 (Ω) is a continuous map, we have u k u in H 1 (Ω) = γ 1/2 u k γ 1/2 u in H 1 (Ω) = (γ 1/2 u k ) (γ 1/2 u) in L 2 (Ω) = γ (γ 1/2 u k ) γ (γ 1/2 u) in L 2 (Ω) = γ (γ 1/2 u k ) γ (γ 1/2 u) in H 1 (Ω). Similarly, γ 1/2 ( + q)u k γ 1/2 ( + q)u in H 1 (Ω), which shows that (3.1) holds in the sense of H 1 (Ω).
21 3.1. REDUCTION TO SCHRÖDINGER EQUATION 17 The problem (3.2) is said to be wellposed if the following three conditions hold: 1. (existence) there is a weak solution u in H 1 (Ω) for any boundary value f in H 1/2 ( Ω), 2. (uniqueness) the solution u is unique, 3. (stability) the solution operator f u is continuous from H 1/2 ( Ω) H 1 (Ω), that is, u H 1 (Ω) C f H 1/2 ( Ω). If the problem is wellposed, we can define a DN map formally by Λ q : H 1/2 ( Ω) H 1/2 ( Ω), f u. ν Ω This is analogous to the conductivity equation, and also here the precise definition of the DN map is given by the weak formulation (Λ q f, g) Ω = ( u v + quv) dx, f, g H 1/2 ( Ω), Ω where u solves (3.2) and v is any function in H 1 (Ω) with v Ω = g. The next proof shows that this is a valid definition and Λ q is a bounded linear map. Lemma 3.4. If q L (Ω) is such that the problem (3.2) is wellposed, then Λ q is a bounded linear map from H 1/2 ( Ω) to H 1/2 ( Ω), and satisfies by (Λ q f, g) Ω = (f, Λ q g) Ω, f, g H 1/2 ( Ω). Proof. Fix f H 1/2 ( Ω), and define a map T : H 1/2 ( Ω) C T (g) = Ω ( u v + quv) dx, where u solves (3.2) and v is any function in H 1 (Ω) with v Ω = g. Since u is a solution, we have ( u ϕ + quϕ) dx Ω for any ϕ H0(Ω). 1 Therefore we may replace v by v + ϕ in the definition of T (g). If v, ṽ H 1 (Ω) and v Ω = ṽ Ω = g, then v ṽ H0(Ω), 1 so indeed the definition does not depend on the particular choice of v (as long as v H 1 (Ω) and v Ω = g).
22 18 3. UNIQUENESS Now, for g H 1/2 ( Ω), use the onesided inverse to the trace operator to obtain v g H 1 (Ω) with v g H 1 (Ω) C g H ( Ω). Then by 1/2 CauchySchwarz T (g) u v g + quv g dx C u H 1 (Ω) v g H 1 (Ω) Ω C f H 1/2 ( Ω) g H 1/2 ( Ω). Thus T : H 1/2 ( Ω) C is a continuous map, and there is an element Λ q f H 1/2 ( Ω) satisfying (Λ q f, g) = T (g). Consequently, the map Λ q : f Λ q f is a bounded linear map H 1/2 ( Ω) H 1/2 ( Ω). To show the last identity, let f, g H 1/2 (Ω), and let u, v be solutions of (3.2) with boundary values u Ω = f, v Ω = g. Then (Λ q f, g) Ω = ( u v + quv) dx = ( v u + qvu) dx = (Λ q g, f) Ω by the definition of Λ q. The problem (3.2) is not always wellposed, consider for instance the case q = λ where λ > 0 is an eigenvalue of the Laplacian in Ω (then there exists a nonzero u H 1 (Ω) with u = λu in Ω and u Ω = 0). However, for potentials q coming from conductivities, the Dirichlet problem is always wellposed, and there is a relation between the DN maps Λ γ and Λ q. Lemma 3.5. If γ C 2 (Ω) and q = γ/ γ, then the Dirichlet problem (3.2) is wellposed and Λ q f = γ 1/2 Λ γ (γ 1/2 f) + 1 γ γ 1 2 ν f Ω, Ω f H 1/2 (Ω). Proof. Fix f H 1/2 ( Ω). We need to show that there is u in H 1 (Ω) which solves (3.2). Motivated by Lemma 3.3, we take v be the solution of γ v = 0 in Ω with v Ω = γ 1/2 f. Then u = γ 1/2 v is a function in H 1 (Ω) which solves ( + q)u = 0 with the right boundary values. The same argument with f = 0 shows that the solution is unique. Further, since γ C 2 (Ω), we have the estimate u H 1 (Ω) C v H 1 (Ω) C γ 1/2 f H 1/2 ( Ω) C f H 1/2 ( Ω). If u solves (3.2), then v = γ 1/2 u solves the conductivity equation and Λ γ (γ 1/2 f) = γ v ν u = γ1/2 ν 1 γ γ 1/2 2 ν f.
23 3.1. REDUCTION TO SCHRÖDINGER EQUATION 19 Since Λ q f = u/ ν, we obtain the relation between Λ γ and Λ q. We may now show that uniqueness in the inverse conductivity problem can be deduced from the corresponding result for the Schrödinger equation. Proof that Theorem 3.2 implies Theorem 3.1. Let γ 1, γ 2 be positive functions in C 2 (Ω), and assume that Λ γ1 = Λ γ2. If q j = γ j / γ j, then q j L (Ω) and by Theorem 3.5 the Dirichlet problems for + q j are well posed. Also, the boundary reconstruction result ([5], Theorem 6.6.1) implies that γ 1 = γ 2 and γ 1 / ν = γ 2 / ν on Ω. Thus, for any f in H 1/2 ( Ω) one has Λ q1 f = γ 1/2 1 Λ γ1 (γ 1/2 1 f) + 1 γ 1 2 γ 1 1 ν f Ω = γ 1/2 2 Λ γ2 (γ 1/2 = Λ q2 f. 2 f) γ 1 Theorem 3.2 gives that q 1 = q 2 in Ω. Therefore, 2 γ 2 ν f Ω (3.3) γ 1 γ1 = γ 2 γ2 in Ω. We would like to conclude from (3.3) that γ 1 = γ 2. Let q = γ 1/2 1 γ 1 = γ 1/2 2 γ 2, and consider the equation ( + q)u = 0 in Ω. Both γ 1 and γ 2 solve this equation, and γ 1 Ω = γ 2 Ω by boundary determination. Since the Schrödinger equation with potential q coming from a conductivity is wellposed, we obtain γ 1 = γ 2 by uniqueness of solutions. Remark 3.6. We record for later use another argument showing that (3.3) implies γ 1 = γ 2. The equation (3.3) looks like a nonlinear PDE involving γ 1 and γ 2. To simplify the equation, we note that (log γ) = The equation becomes n j=1 j ( 1 γ j γ) = γ γ (log γ) 2. (log γ 1 log γ 2 ) + (log γ 1 ) 2 (log γ 2 ) 2 = 0.
24 20 3. UNIQUENESS Rewriting slightly, we get γ1 γ1 (log ) + a (log ) = 0, γ2 γ2 where a = log γ 1 γ 2. This is a linear equation for the C 2 function v = log γ 1 γ2. Further, noting the identity (e a v) = e a ( v + a v), and using the fact that γ 1 = γ 2 on Ω, we see that v solves the Dirichlet problem { ((γ1 γ 2 ) 1/2 v) = 0 in Ω, v = 0 on Ω. This problem is wellposed, and we get v 0 and γ 1 γ Complex geometrical optics In this section, we will construct complex geometrical optics (CGO) solutions to the Schrödinger equation ( + q)u = 0 in Ω. The potential q is assumed to be in L (Ω). Motivation. First let q = 0. We try as a solution to the equation u = 0 the complex exponential at frequency ζ C n, This satisfies u(x) = e iζ x. Du(x) = ζe iζ x, D 2 u(x) = (ζ ζ)e iζ x. Thus, if ζ C n satisfies ζ ζ = 0, then u(x) = e iζ x solves u = 0. Writing ζ = Re ζ + i Im ζ, we see that ζ ζ = 0 Re ζ = Im ζ, Re ζ Im ζ = 0. Now suppose q is nonzero. The function u = e iζ x is not an exact solution of ( + q)u = 0 anymore, but we can find solutions which resemble complex exponentials. These are the CGO solutions, which have the form (3.4) u(x) = e iζ x (1 + r(x)). Here r is a correction term which is needed to convert the approximate solution e iζ x to an exact solution.
25 3.2. COMPLEX GEOMETRICAL OPTICS 21 In fact, we are interested in solutions in the asymptotic limit as ζ. This follows the principle that it is usually not possible to obtain explicit formulas for solutions to general equations, but in suitable asymptotic limits explicit expressions for solutions may exist. We note that (3.4) is a solution of ( + q)u = 0 iff (3.5) e iζ x ( + q)e iζ x (1 + r) = 0. It will be convenient to conjugate the exponentials e iζ x into the Laplacian. By this we mean that We can rewrite (3.5) as e iζ x D j (e iζ x v) = (D j + ζ j )v, e iζ x D 2 (e iζ x v) = (D + ζ) 2 v = (D 2 + 2ζ D)v. (D 2 + 2ζ D + q)(1 + r) = 0. This implies the following equation for r: (3.6) (D 2 + 2ζ D + q)r = q. The solvability of (3.6) is the most important step in the construction of CGO solutions. We proceed in several steps Basic estimate. We first consider the free case in which there is no potential on the left hand side of (3.6). Theorem 3.7. There is a constant C 0 depending only on Ω and n, such that for any ζ C n satisfying ζ ζ = 0 and ζ 1, and for any f L 2 (Ω), the equation (3.7) (D 2 + 2ζ D)r = f in Ω has a solution r H 1 (Ω) satisfying r L 2 (Ω) C 0 ζ f L 2 (Ω), r L 2 (Ω) C 0 f L 2 (Ω). The idea of the proof is that (3.7) is a linear equation with constant coefficients, so one can try to solve it by the Fourier transform. Since (D j u)ˆ(ξ) = ξ j û(ξ), the Fourier transformed equation is (ξ 2 + 2ζ ξ)ˆr(ξ) = ˆf(ξ).
26 22 3. UNIQUENESS We would like to divide by ξ 2 + 2ζ ξ and use the inverse Fourier transform to get a solution r. However, the symbol ξ 2 + 2ζ ξ vanishes for some ξ R n, and the division cannot be done directly. It turns out that we can divide by the symbol if we use Fourier series in a large cube instead of the Fourier transform, and moreover take the Fourier coefficients in a shifted lattice instead of the usual integer coordinate lattice. Proof of Theorem 3.7. Write ζ = s(ω 1 +iω 2 ) where s = ζ / 2 and ω 1 and ω 2 are orthogonal unit vectors in R n. By rotating coordinates in a suitable way, we can assume that ω 1 = e 1 and ω 2 = e 2 (the first and second coordinate vectors). Thus we need to solve the equation (D 2 + 2s(D 1 + id 2 ))r = f. We assume for simplicity that Ω is contained in the cube Q = [ π, π] n. Extend f by zero outside Ω into Q, which gives a function in L 2 (Q) also denoted by f. We need to solve (3.8) (D 2 + 2s(D 1 + id 2 ))r = f in Q. Let w k (x) = e i(k+ 1 2 e2) x for k Z n. That is, we consider Fourier series in the lattice Z n + 1e 2 2. Writing (u, v) = (2π) n u v dx, u, v L 2 (Q), Q we see that (w k, w l ) = 0 if k l and (w k, w k ) = 1, so {w k } is an orthonormal set in L 2 (Q). It is also complete: if v L 2 (Q) and (v, w k ) = 0 for all k Z n then (ve 1 2 ix 2, e ik x ) = 0 for all k Z n, which implies v = 0. Hilbert space theory gives that f can be written as the series f = k Z n f k w k, where f k = (f, w k ) and f 2 L 2 (Q) = k Z n f k 2. Seeking also r in the form r = k Z n r k w k, and using that the equation (3.8) results in Dw k = (k e 2)w k, p k r k = f k, k Z n, where p k := (k e 2) 2 + 2s(k 1 + i(k )).
27 3.2. COMPLEX GEOMETRICAL OPTICS 23 Note that Im p k = 2s(k ) is never zero, which was the reason for 2 considering the shifted lattice. We define r k := 1 p k f k and r := k Z n r k w k. The last series converges in L 2 (Q) to a function r L 2 (Q) since r k 1 p k f k and then ( ) 1/2 r L 2 (Q) = r k 2 1 s k 1 2s(k ) f k 1 s f k, ( k f k 2 ) 1/2 = 1 s f L 2 (Q). This shows the desired estimate in L 2 (Q). It remains to show that Dr L 2 (Q) with correct bounds. We have Dr = k Z n (k e 2)r k w k. The derivative is justified since this is a convergent series in L 2 (Q): we claim (3.9) (k e 2)r k 4 f k, k Z n, which implies that Dr L 2 (Q) 4 f L 2 (Q). To show (3.9) we consider two cases: if k e 2 4s we have (k e 2)r k and if k e 2 4s then 4s 2s k 2 + 1/2 f k 4 f k, k e sk 1 k e 2 2 2s k e k e 2 2 which implies The statement is proved. (k e 2)r k k e k e 2 2 f k 1 2s f k.
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