INVERSE PROBLEMS for NONLINEAR HYPERBOLIC EQUATIONS Gunther Uhlmann Jian Zhai 1. Introduction. Many Physical Phenomena Are Model

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INVERSE PROBLEMS for NONLINEAR HYPERBOLIC EQUATIONS Gunther Uhlmann Jian Zhai 1. Introduction. Many Physical Phenomena Are Model DISCRETE AND CONTINUOUS doi:10.3934/dcds.2020380 DYNAMICAL SYSTEMS Volume 41, Number 1, January 2021 pp. 455{469 INVERSE PROBLEMS FOR NONLINEAR HYPERBOLIC EQUATIONS Gunther Uhlmann∗ Department of Mathematics, University of Washington, Seattle, WA 98195, USA Institute for Advanced Study, The Hong Kong University of Science and Technology Kowloon, Hong Kong, China Jian Zhai Institute for Advanced Study, The Hong Kong University of Science and Technology Kowloon, Hong Kong, China Abstract. There has been considerable progress in recent years in solving inverse problems for nonlinear hyperbolic equations. One of the striking aspects of these developments is the use of nonlinearity to get new information, which is not possible for the corresponding linear equations. We illustrate this for several examples including Einstein equations and the equations of nonlinear elasticity among others. 1. Introduction. Many physical phenomena are modeled by nonlinear hyperbolic equations (see for example [40]). In recent years, starting with the paper [20] sev- eral inverse problems for nonlinear hyperbolic equations have been solved, ranging from semilinear wave equations to nonlinear elastic equations and Einstein equa- tions. The nonlinearity of the equation is used in an essential way. The interaction of waves, caused by the nonlinearity of the equation, produces new waves giving information that is not available for the corresponding linear equation. We will survey in this paper some recent progress on inverse problems for nonlinear hyper- bolic equations. The most exciting breakthrough is the possibility of recovering time-dependent coefficients for nonlinear evolution equations. The unique recovery of a time-dependent coefficient in a linear hyperbolic equation is in general still not known. To solve inverse problems for linear hyperbolic equations, a powerful method, called the boundary control (BC) method, was developed by Belishev starting with the acoustic wave type equation ([2]). The BC method relies on a sharp unique continuation result for the wave equation that was proven later by Tataru [33]. However, this result is only valid if the coefficients of the equation depend ana- lytically on time. One way to avoid using Tataru's result is to reduce the inverse problems to some geometrical inverse problems. We refer to [29, 27, 31, 30] for 2020 Mathematics Subject Classification. Primary: 35R30; Secondary: 35A27, 35L70. Key words and phrases. Inverse problems, nonlinear hyperbolic equations, Lorentzian manifolds. The first author was partially supported by NSF, a Walker Professorship at UW and a Si-Yuan Professorship at IAS, HKUST. ∗ Corresponding author: [email protected]. 455 456 GUNTHER UHLMANN AND JIAN ZHAI this direction of work. Microlocal analysis is then used as a powerful tool to ana- lyze the propagation of singularities of solutions. Nonlinear waves have even richer geometric behaviors, which can be utilized to solve inverse problems. For an inverse problem for a nonlinear equation, usually the nonlinear equation is linearized, and the results for the linearized equation are applied when available. For example, a semilinear parabolic equation is treated in [15]; the nonlinear Calder´on problem in the isotropic case is reduced to the linear one [32]; the inverse problem for the nonlinear Navier-Stokes equation is reduced to the problem for the linear Stokes equation [24]. Since the paper [20], the nonlinearity has been used to solve some inverse prob- lems, whereas the results for the associated linearized equations are not available. What is used is the interaction of several waves to produce new waves that give information not available for the linearized equation. The technique of higher order linearization is a necessary part in the treatment. We shall briefly explain this. The higher order linearization can be explained as follows. Assume Λ(f) is the measured response of a medium with an input f. For example, Λ can be the Dirichlet-to- Neumann map associated to some partial differential equation. One can take an PN input of the form f = i=1 ifi, where i, i = 1; ··· ;N are small parameters. If the response of the medium to the input is nonlinear, then Λ is a nonlinear map, and PN consequently Λ( i=1 ifi) contains extra information other than what is contained in fΛ(fi)gi=1;··· ;N . Therefore useful information can possibly be extracted from the higher order linearization of the map Λ: N @N X Λ( ifi): @ ··· @ =···= =0 1 N 1 N i=1 For hyperbolic equations modeling waves, one usually chooses input sources of the PN form f = i=1 ifi such that fi, i = 1; 2; ··· N produce distorted plane waves or Gaussian beams. The outline of this paper is as follows. In Section 2 we consider the inverse problem of determining a globally hyperbolic Lorentzian metric by measuring the source-to-solution map in a neighborhood of a time-like geodesic for the wave equa- tion plus a quadratic term. The result of [17] is reviewed. The concept of earliest light observation set is defined and the result that the earliest light observation sets determine the conformal class of a globally hyperbolic Lorentzian metric in 3+1 dimensions is reviewed. In Section 3 more general semilinear equations are con- sidered. In Section 4, several results for other equations like Einstein equations, a simpler analog of Yang-Mills equations and nonlinear elasticity are formulated. 2. Quadratic non-linearities. We first introduce some notations and definitions. Let (M; g) be a C1-smooth (1 + 3)-dimensional globally hyperbolic Lorentzian manifold, where the metric g is of signature (−; +; +; +). By [3], (M; g) is isometric to a smooth manifold (R × N; h), where N is a 3-dimensional manifold and the metric h has the form h = −β(t; y)dt2 + κ(t; y): (1) Here β : R × N ! (0; +1) is a smooth function and κ(t; ·) is a Riemannian metric on N depending smoothly on t 2 R. A smooth curve µ :(a; b) ! M is called causal if g(_µ(s); µ_ (s)) ≤ 0 andµ _ (s) 6= 0 for all s 2 (a; b). Given p; q 2 M, we denote p ≤ q if p = q or p can be joined to q by a future-pointing causal curve. We say p < q if p ≤ q + and p 6= q. We denote the causal future of p 2 M to be Jg (p) = fq 2 M : p ≤ qg NONLINEAR HYPERBOLIC EQUATIONS 457 − and the causal past of q 2 M to be Jg (q) = fp 2 M : p ≤ qg. The curve µ is called time-like if g(_µ(s); µ_ (s)) < 0 for all s 2 (a; b). We denote p q if p 6= q and there is a future-pointing time-like path from p to q. Then the chronological + future of p 2 M is the set Ig (p) = fq 2 M; p qg and the chronological past of − + − q 2 M is Ig (q) = fp 2 M; p qg. We also denote Jg(p; q) := Jg (p) \ Jg (q) and + − Ig(p; q) := Ig (p) \ Ig (q). Take t0 > 0 to be a fixed number and denote M(t0) = (−∞; t0) × N: Consider the semilinear wave equations with source terms 2 gu(x) + a(x)u(x) = f(x); on M(t0); + (2) u = 0 in M(t0) n Jg (supp(f)); where g is the Laplacian-Beltrami operator on (M; g) and a(x) is nowhere vanish- ing. In local coordinates, 1 p jk g := @j( j det gjg @k): pj det gj For p 2 M, denote the set of light-like vectors at p by LpM = fζ 2 TpM n f0g : g(ζ; ζ) = 0g: ∗ Also, the set of light-like covectors at p is denoted by LpM. The future and past + − ∗;+ ∗;− light-like vectors (covectors) are denoted by Lp M and Lp M (Lp M and Lp M). Assume V ⊂ M(t0) is an open, relatively compact, connected neighborhood of a future-pointing time-like pathµ ^ =µ ^([−1; 1]) ⊂ M(t0).Take −1 < s− < s+ < 1, ± and denote p =µ ^(s±). 6 Definition 2.1. Let W = ff 2 C0 (V ); kfkC6(V ) < "g, where " > 0 is so small 2 that the equation (2) has a unique solution u 2 C (M(t0)) for all f 2 W. The source-to-solution map LV : W! C(V ) is the nonlinear operator defined as LV : f 7! ujV ; f 2 W; (3) where u satisfies the wave equation (2) on (M(t0); g). Kurylev, Lassas and Uhlmann [20] first studied the inverse problem of determin- ing the Lorentzian metric g from the source-to-solution operator LV . The main result is: Theorem 2.2. Let (M (j); g(j)), j = 1; 2 be two smooth, globally hyperbolic Lorentzian manifolds of dimension (1 + 3) that are represented in the form M (j) = R × N (j) withe a metric of the form (1). (j) + − Let µ^j :[−1; 1] ! M (t0) be smooth time-like paths, pj =µ ^j(s+), pj =µ ^j(s−), (j) where −1 < s− < s+ < 1, and Vj ⊂ M be neighborhoods of µ^j([−1; 1]). Let LVj , j = 1; 2 be the source-to-solution maps for wave equations (2) on man- (j) (j) (j) ifolds (M ; g ) with a = aj, where aj : M ! R n f0g are nowhere vanishing C1-smooth functions, j = 1; 2. − − Assume that there is a diffeomorphism Φ: V1 ! V2 such that Φ(p1 ) = p2 , + + Φ(p1 ) = p2 and the source-to-solution maps satisfy −1 ∗ ∗ ((Φ ) ◦ LV1 ◦ Φ )f = LV2 f 6 for f 2 W, where W is a neighborhood of the zero function in C0 (V2). 458 GUNTHER UHLMANN AND JIAN ZHAI − + − + Then there is a diffeomorphism Ψ: Ig(1) (p1 ; p1 ) ! Ig(2) (p2 ; p2 ) and the metric ∗ (2) (1) − + (1) (1) Ψ g is conformal to g in Ig(1) (p1 ; p1 ) ⊂ M , that is, there is b : M ! R+ (1) ∗ (2) − + such that g (x) = b(x)(Ψ g )(x) in Ig(1) (p1 ; p1 ).
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