unique continuation for the helmholtz equation using a
play

Unique continuation for the Helmholtz equation using a stabilized - PowerPoint PPT Presentation

Unique continuation for the Helmholtz equation using a stabilized finite element method Lauri Oksanen University College London Based on a joint work with Erik Burman and Mihai Nechita Motivation: recovering a speed of sound by layer stripping


  1. Unique continuation for the Helmholtz equation using a stabilized finite element method Lauri Oksanen University College London Based on a joint work with Erik Burman and Mihai Nechita

  2. Motivation: recovering a speed of sound by layer stripping Reconstruction of the front face of an acoustic lens using a variant of the Boundary Control method [de Hoop-Kepley-L.O.] . We find the speed sound c ( x ) in ∂ 2 t u − c 2 ∆ u = 0 given u and ∂ ν u on the boundary/surface for many solutions u . This is easiest near the boundary.

  3. Motivation: recovering a speed of sound by layer stripping True speed of sound (blue curve) and the reconstructed one (red triangles) as a function of depth along a ray path.

  4. Boundary normal coordinates for the lens Reconstruction is computed on a rectangular patch in boundary normal coordinates. The boundary normal coordinates degenerate behind the lens.

  5. Focusing ray paths ◮ In theory, the Boundary Control method avoids problems related to focusing by recovering the speed of sound in patches. ◮ The data needs to be continued across regions where the speed of sound is already known. Some ray paths emanating from a point at the surface.

  6. Unique continuation ◮ In theory, the data can be extended by using unique continuation. ◮ The rest of the talk focuses on numerical analysis of unique continuation in the frequency domain . c(x)=? c(x)=? c(x)=? Left. Wave field that reflects at the bottom of a slab. Right. The same snapshots computed without knowing the speed of sound below the red line [de Hoop-Kepley-L.O.] .

  7. Unique continuation problem for the Helmholtz equation Consider three open, connected and non-empty sets ω ⊂ B ⊂ Ω in R n . Unique continuation problem. Given u | ω determine u | B for a solution u to the Helmholtz equation ∆ u + k 2 u = 0 in Ω.

  8. Conditional H¨ older stability/three solid balls inequality If B does not touch the boundary of Ω, then the unique continuation problem is conditionally H¨ older stable. For all k ≥ 0 there are C > 0 and α ∈ (0 , 1) such that L 2 (Ω) ) α � u � 1 − α � ∆ u + k 2 u � � � u � H 1 ( B ) ≤ C ( � u � H 1 ( ω ) + H 1 (Ω) . � ◮ In general, the constant C depends on k . ◮ If there is a line that intersects B but not ω , then C blows up faster than any polynomial in k . ◮ This can be shown by constructing a WKB solution localizing on the line (quasimode with non-homogeneous boundary conditions). ◮ Assuming suitable convexity, the constant C is independent of k .

  9. Isakov’s increased stability estimate B ω In a convex setting as above, it holds that � u � L 2 ( B ) ≤ CF + Ck − 1 F α � u � 1 − α H 1 (Ω) , � � ∆ u + k 2 u � where F = � u � H 1 ( ω ) + L 2 (Ω) and the constants C and α are � independent of k .

  10. Shifting in the Sobolev scale � � ∆ u + k 2 u � Recall that F = � u � H 1 ( ω ) + L 2 (Ω) . In Isakov’s estimate, � � u � L 2 ( B ) ≤ CF + Ck − 1 F α � u � 1 − α (1) H 1 (Ω) , the sides of the inequality are at different levels in the Sobolev scale. For a plane wave u ( x ) = e ik kx , with | k k k | = k , it holds that k � u � H 1 ( ω ) ∼ (1 + k ) � u � L 2 ( ω ) . This suggest that the analogue of (1), with both the sides at the same level in the Sobolev scale, could be � u � L 2 ( B ) ≤ CkE + CE α � u � 1 − α L 2 (Ω) , � � ∆ u + k 2 u � where E = � u � L 2 ( ω ) + H − 1 (Ω) . �

  11. Shifting in the Sobolev scale � � ∆ u + k 2 u � Recall that E = � u � L 2 ( ω ) + H − 1 (Ω) . We show a stronger � estimate than � u � L 2 ( B ) ≤ CkE + CE α � u � 1 − α L 2 (Ω) . Lemma [Burman-Nechita-L.O] . For a suitable convex geometry ω ⊂ B ⊂ Ω. There are C > 0 and α ∈ (0 , 1) such that for all k ∈ R � u � L 2 ( B ) ≤ CE α � u � 1 − α L 2 (Ω) . Our numerical analysis is based on this estimate.

  12. On the convexity assumption We prove the estimate only in the particular geometry This is a model for a local problem near a point on ∂ B assuming that ∂ B is convex there. In what follows, we will consider only this geometry.

  13. Stabilized finite element method We use the shorthand notation G ( u , z ) = ( ∇ u , ∇ z ) − k 2 ( u , z ) , ( · , · ) = ( · , · ) L 2 (Ω) , �·� ω = �·� L 2 ( ω ) . The stabilized FEM for the unique continuation problem is based on finding the critical point of the Lagrangian functional L q ( u , z ) = 1 ω + 1 2 s ( u , u ) − 1 2 � u − q � 2 2 s ∗ ( z , z ) , + G ( u , z ) , on a scale of finite element spaces V h , h > 0. Here q ∈ L 2 ( ω ) is the data. The crux of the method is to choose suitable regularizing terms s ( u , u ) and s ∗ ( z , z ). They are defined only in the finite element spaces .

  14. Error estimates For a suitable choice of a scale of finite element spaces V h , h > 0, and regularizing terms s ( u , u ) and s ∗ ( z , z ), we show that L q ( u , z ) = 1 ω + 1 2 s ( u , u ) − 1 2 � u − q � 2 2 s ∗ ( z , z ) + G ( u , z ) , has a unique critical point ( u h , z h ) ∈ V h , and that for all k , h > 0, satisfying kh ≤ 1, it holds that � u � H 2 (Ω) + k 2 � u � L 2 (Ω) � u − u h � L 2 ( B ) ≤ Ch α k 2 α − 2 � � . Here u is the solution to the unique continuation problem � ∆ u + k 2 u = 0 , u | ω = q .

  15. Error estimates with noisy data Consider now the case that u | ω = q is known only up to an error δ q ∈ L 2 ( ω ). That is, we assume that ˜ q = q + δ q is known. Let ( u h , z h ) ∈ V h be the minimizer of the perturbed Lagrangian L ˜ q . Then for all k , h > 0, satisfying kh ≤ 1, it holds that � u − u h � L 2 ( B ) ≤ Ch α k 2 α − 2 � � u � H 2 (Ω) + k 2 � u � L 2 (Ω) + h − 1 � δ q � L 2 ( ω ) � , where u is again the solution to the unique continuation problem � ∆ u + k 2 u = 0 , u | ω = q .

  16. On previous literature Several authors, e.g. Bourgeois, Klibanov, ..., have considered the unique continuation problem for the Helmholtz equation from the computational point of view. ◮ They use the quasi-reversibilty method originating from [Latt` es-Lions’67] ◮ No rate of convergence with respect to the mesh size is proven For related problems, there are also methods based on Carleman estimates on discrete spaces e.g. by Le Rousseau. Stabilized finite element methods for unique continuation, with proven convergence rates, have been recently developed in the following cases ◮ Laplace equation [Burman’14] ◮ Heat equation [Burman-L.O.]

  17. Details of the finite element method Let us now specify s and s ∗ and the domain V h for the Lagrangian L q ( u , z ) = 1 ω + 1 2 s ( u , u ) − 1 2 � u − q � 2 2 s ∗ ( z , z ) , + G ( u , z ) . Let V h be the H 1 -conformal approximation space based on the P 1 finite element over a suitable triangulation of Ω. Here h is the mesh size. Set W h = V h ∩ H 1 V h = V h × W h , 0 (Ω) . Denote by F h the set of internal faces of the triangulation, and define � � h � n · ∇ u � 2 J ( u , u ) = u ∈ V h , F ds , F F ∈F h where � n · ∇ u � F is the jump of the normal derivative. Set γ = 10 − 5 and � 2 s ∗ ( z , z ) = �∇ z � 2 � � hk 2 u � s ( u , u ) = γ J ( u , u ) + γ L 2 (Ω) , L 2 (Ω) .

  18. Computational example: a convex case The unique continuation problem for the Helmholtz equation in the unit 2 cos ky square with k = 10. The exact solution is u ( x , y ) = sin kx 2 . √ √ We use a regular mesh with 2 × 256 × 256 triangles. Left. True u . Right. Minimizer u h of the Lagrangian L q . Here ω is the region touching left, bottom and right sides.

  19. Computational example: a non-convex case The same example except that ω is changed. Left. True u . Right. Minimizer u h of the Lagrangian L q . Here ω is the rectangular region touching only the bottom side.

  20. Comparison of the errors Left. Convex case Right. Non-convex case. Note that the scales differ by two orders of magnitude.

  21. Convergence: the convex case Circles: H 1 -error, rate ≈ 0 . 64; squares: L 2 -error, rate ≈ 0 . 66; down triangles: h − 1 J ( u h , u h ), rate ≈ 1; up triangles: s ∗ ( z h , z h ) 1 / 2 , rate ≈ 1 . 3.

  22. Convergence: the non-convex case

  23. Convergence: the effect of noise in the convex case Left. Perturbation O ( h ). Right. Perturbation O ( h 2 ).

  24. Ideas towards the proof in the case k = 0 Consider the Lagrangian L q ( u , z ) = 1 ω + 1 2 s ( u , u ) − 1 2 � u − q � 2 2 s ∗ ( z , z ) , +( ∇ u , ∇ z ) , on the discrete space V h × W h , W h = V h ∩ H 1 0 (Ω), with � s ∗ ( z , z ) = �∇ z � 2 . � h � n · ∇ u � 2 s ( u , u ) = J ( u , u ) = F ds , F F ∈F h The critical points ( u , z ) of L q satisfy the normal equations D u L q v = 0 , D z L q w = 0 , for all v ∈ V h and w ∈ W h .

Recommend


More recommend