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Increasing stability for the inverse source problems in electrodynamics

Suliang Si School of Mathematics and Statistics, Shandong University of Technology, Shandong, 255049, China ([email protected])
Abstract

We are concerned with increasing stability in the inverse source problems for the time-dependent Maxwell equations in 3{\mathbb{R}}^{3}, where the source term is compactly supported in both time and spatial variables. By using the Fourier transform, sharp bounds of the analytic continuation and the Huygens’ principle, increasing stability estimates of the L2L^{2}-norm of the source function are obtained. The main goal of this paper is to understand increasing stability for the Maxwell equations in the time domain.

1 Introduction

1.1 statement of the problem

Consider the time-dependent Maxwell equations in a homogeneous medium

μtH(x,t)+×E(x,t)=0,εtE(x,t)×H(x,t)=σE+F~(x,t),x3,t>0,\mu\partial_{t}\textbf{H}(\textbf{x},t)+\nabla\times\textbf{E}(\textbf{x},t)=0,\quad\varepsilon\partial_{t}\textbf{E}(\textbf{x},t)-\nabla\times\textbf{H}(\textbf{x},t)=-\sigma\textbf{E}+\tilde{\textbf{F}}(\textbf{x},t),\ \textbf{x}\in{\mathbb{R}}^{3},\ t>0, (1.1)

where E and H are the electric and magnetic fields, respectively, the source function F~\tilde{\textbf{F}} is known as the electric current density, ε\varepsilon and μ\mu are the dielectric permittivity and the magnetic permeability, respectively, and σ\sigma is the electric conductivity and is assumed to be zero.

Let n=εμn=\frac{\varepsilon}{\mu}. Eliminating the magnetic field H from (1.1), we obtain the Maxwell system for the electric field E:

nt2E(x,t)+×(×E(x,t))=1μtF~(x,t)=:F(x,t),x3,t>0,n\partial_{t}^{2}\textbf{E}(\textbf{x},t)+\nabla\times(\nabla\times\textbf{E}(\textbf{x},t))=\frac{1}{\mu}\partial_{t}\tilde{\textbf{F}}(\textbf{x},t)=:\textbf{F}(\textbf{x},t),\ \textbf{x}\in{\mathbb{R}}^{3},t>0, (1.2)

which is supplemented by the homogeneous initial conditions

E(x,0)=tE(x,0)=0,x3.\textbf{E}(\textbf{x},0)=\partial_{t}\textbf{E}(\textbf{x},0)=0,\ \textbf{x}\in{\mathbb{R}}^{3}. (1.3)

In this work, we consider the following inverse source problems:

IP1: Assume F(x,t)=f(x)g(t)\textbf{F}(\textbf{x},t)=\textbf{f}(\textbf{x})g(t), where f3,g\textbf{f}\in{\mathbb{R}}^{3},\ g\in{\mathbb{R}} have compact supports such that supp f {x3||x|<R}\subset\{\textbf{x}\in\mathbb{R}^{3}|\ |\textbf{x}|<R\} and supp gg (0,T0)\subset(0,T_{0}) where R>0,T0>0R>0,\ T_{0}>0 are constants. Then we concern the inverse problem of recovering the source term f(x)\textbf{f}(\textbf{x}) from the Dirichlet boundary data measured on BR×(0,T0)\partial B_{R}\times(0,T_{0}).

IP2: Assume n(0,b2)n\in(0,b^{2}) for b>1b>1. The source function F(x,t)\textbf{F}(\textbf{x},t) has compact supports. The inverse problem is to determine source term F(x,t)\textbf{F}(\textbf{x},t) from the measurement E(x,t)\textbf{E}(\textbf{x},t), xBR\textbf{x}\in\partial B_{R}, t(0,T0)t\in(0,T_{0}).

IP3: Assume F(x,t)=f(x1,x2,t)g(x3)\textbf{F}(\textbf{x},t)=\textbf{f}(x_{1},x_{2},t)g(x_{3}), where the function f3\textbf{f}\in{\mathbb{R}}^{3} and gg\in{\mathbb{R}} have compact supports. The inverse problem is to determine source term f from the boundary observation data E(x,t)\textbf{E}(\textbf{x},t), xBR\textbf{x}\in\partial B_{R}, t(0,T0)t\in(0,T_{0}).

1.2 Motivations

Motivated by significant applications, the inverse source problems, as an important research subject in inverse scattering theory, have continuously attracted much attention by many researchers [1, 3, 22, 25, 34]. Consequently, a great deal of mathematical and numerical results are available, especially for the acoustic waves or the Helmholtz equations. In general, it is known that there is no uniqueness for the inverse source problem at a fixed frequency due to the existence of non-radiating sources [20]. Therefore, additional information is required for the source in order to obtain a unique solution, such as to seek the minimum energy solution [29]. From the computational point of view, a more challenging issue is the lack of stability. A small variation of the data might lead to a huge error in the reconstruction. Recently, it has been realized that the use of multi-frequency data is an effective approach to overcome the difficulties of non-uniqueness and instability which are encountered at a single frequency. The first increasing stability result in [4] was obtained in a more particular case by quite different (spatial Fourier analysis) methods. A topical review can be found in [10] on the inverse source problems as well as other inverse scattering problems by using multiple frequencies to overcome the ill-posedness and gain increased stability.

For electromagnetic waves, Ammari et al. [11] showed uniqueness and stability, and presented an inversion scheme to reconstruct dipole sources based on a low-frequency asymptotic analysis of the time-harmonic Maxwell equations. In [2], Albanese and Monk discussed uniqueness and non-uniqueness of the inverse source problems for Maxwell’s equations. A monograph can be found in [31] on general inverse problems for Maxwell’s equations. In [5], Bao et al. develop new techniques and establish an increasing stability theory in the inverse source scattering problems for electromagnetic waves. Due to the inverse source problem of electromagnetic waves, there is a phenomenon of increasing stability. A natural question is whether there is also some increasing stability in the inverse source problem of time-dependent Maxwell equations. Thus the main goal of this paper is to understand increasing stability for the Maxwell equations in the time domain.

1.3 Known results

Inverse sourse problems have many significant applications in scientific and engineering areas. For instance, detection of submarines and non-destructive measurement of industrial objects can be regarded as recovery of acoustic sources from boundary measurements of the pressure. Other application include biomedical imaging optical tomography [1, 22], and geophysics. For a mathematical overview of various inverse source problems, we can see that uniqueness and stability are discussed in [22]. For inverse source problems in time domain, it is solved as hyperbolic systems by using Carleman estimate [26] and unique continuation; we refer to [12, 25, 34, 35] for an incomplete list. For time-harmonic inverse source problems, it is well-known that there is no uniqueness for the inverse source problem with a single frequency due to the existence of non-radiating sources [3, 20]. Therefore, the use of multiple frequencies data is an effective way to overcome non-uniqueness and has received a lot of attention in recent years. [16] show the uniqueness and numerical results for Helmholtz equation with multi-frequency data. And in [4], Bao et al. firstly get increasing stability for Helmholtz equation by direct spatial Fourier analysis methods. Then in [13], a different method involving a temporal Fourier transform, sharp bounds of the analytic continuation to higher wave numbers were used to derive increasing stability bounds for the three dimensional Helmholtz equation. Also, [13] firstly combined the Helmholtz equation and associated hyperbolic equations to get the stability results. Later in [27] and [5], increasing stability were extended to Helmholtz equation and Maxwell’s equation in three dimension.

Motivated by those works, we are interested in the increasing stability for the time-dependent Maxwell equations. Since by Fourier transform, inverse source problem of the time-dependent Maxwell equations can be reduced to that of the associated Electromagnetic with multi-frequency data, we derive our increasing stability estimate by using sharp bounds of analytic continuation given in [13]. Instead of Cauchy data on measure boundary used in the works mentioned above, we use only Dirichlet data on the lateral boundary. For the uniqueness, we just prove it in time domain without Carleman estimate.

The rest of this paper is organized as follows. In Section 2 and 3, we state our main results and well-posedness of the direct problem. Sections 3 is devoted to the increasing stability of inverse problem 1. In Section 4, we prove general source terms in homogeneous medium. Section 5, we establish the increasing stability of general source term. Finally, the increasing stability of time-dependent source term can be established by using the boundary Dirichlet data.

2 Main results

Let BR=B(0,R)={x3||x|<R}B_{R}=B(0,R)=\{\textbf{x}\in{\mathbb{R}}^{3}|\ |\textbf{x}|<R\} for R>0R>0. We always assume that the source function F(x,t)\textbf{F}(\textbf{x},t) is required to be real-valued, which implies that F^(ξ,ω)=F¯(ξ,ω)\widehat{\textbf{F}}(-\xi,-\omega)=\overline{\textbf{F}}(\xi,\omega) for all (ξ,ω)3×(\xi,\omega)\in{\mathbb{R}}^{3}\times{\mathbb{R}}. In addition, we also assume that F(x,t)=0\nabla\cdot\textbf{{F}}(\textbf{x},t)=0. It follows from that the source term F(x,t)\textbf{F}(\textbf{x},t) can be decomposed into a sum of radiation and non-radiating parts. The non-radiating part cannot be determined and gives rise to the non-uniqueness issue. By the divergence-free condition of F(x,t)\textbf{F}(\textbf{x},t), we eliminate non-radiating sources in order to ensure the uniqueness of the inverse problem. First we show increasing stability result for the time-dependent inverse problem (IP1). Let F(x,t)=f(x)g(t)\textbf{F}(\textbf{x},t)=\textbf{f}(\textbf{x})g(t), where f3\textbf{f}\in{\mathbb{R}}^{3} is compactly supported in BRB_{R} and gg\in{\mathbb{R}} is supported in (0,T0)(0,T_{0}) for some T0>0T_{0}>0. It is supposed that f(x)H1(3)3\textbf{f}(\textbf{x})\in H^{1}({\mathbb{R}}^{3})^{3} and g(t)H4(0,)g(t)\in H^{4}(0,\infty). The one-dimensional Fourier transform of gg with respect to the time variable tt is defined as

g^(ω):=12πg(t)eiωt𝑑t=12π0g(t)eiωt𝑑t.\widehat{g}(\omega):=\frac{1}{\sqrt{2\pi}}\int_{\mathbb{R}}g(t)e^{-i\omega t}dt=\frac{1}{\sqrt{2\pi}}\int_{0}^{\infty}g(t)e^{-i\omega t}dt.

We suppose there exist a number b>1b>1 and a constant δ>0\delta>0 such that

|g^(ω)|δ>0for allω(0,b).\displaystyle|\widehat{g}(\omega)|\geq\delta>0\quad\mbox{for all}\quad\omega\in(0,b). (2.4)

Physically, the parameter bb in (2.4) is associated with the bandwidth of the temporal signal g(t)g(t). The condition (2.4) covers a large class of functions. For example, if g(t)=e(t1)2/ηχ(t)g(t)=e^{-(t-1)^{2}/\eta}\chi(t) with some η>0\eta>0 and χ(t)C0()\chi(t)\in C_{0}^{\infty}({\mathbb{R}}) such that χ(t)=0\chi(t)=0 for t[0,T0]t\notin[0,T_{0}], the one can always find the parameters b>0b>0 and δ>0\delta>0 such that (2.4) holds true. Since the source function is real valued, (2.4) holds true for all ω(b,b)\omega\in(-b,b). We remark that the interval (0,b)(0,b) in (2.4) can be replaced by (ω0b,ω0+b)(\omega_{0}-b,\omega_{0}+b) for some ω00\omega_{0}\geq 0. In this paper we take ω0=0\omega_{0}=0 for simplicity. The condition (2.8) is also similar.

Define a boundary operator

T(E×ν)=(×E)×νonBR×(0,T0),T(\textbf{E}\times\nu)=(\nabla\times\textbf{E})\times\nu\quad\mbox{on}\ \partial B_{R}\times(0,T_{0}), (2.5)

where ν\nu is the unit normal vector on BR\partial B_{R}.

In the following theorem, we establish increasing stability estimate of the L2L^{2}-norm of f about bb.

Theorem 2.1.

Let the condition (2.4) hold and let T>2R+T0T>2R+T_{0}. Assume that g(t)g(t) is given and fH1(3)3M||\textbf{f}||_{H^{1}({\mathbb{R}}^{3})^{3}}\leq M where M>1M>1 is a constant. If f(x)=0\nabla\cdot\textbf{f}(x)=0, then there exists a constant C>0C>0 depending on δ\delta, T0T_{0}, nn and RR such that

fL2(3)32C(b5ϵ2+M2b43|lnϵ|12),||\textbf{f}||_{L^{2}({\mathbb{R}}^{3})^{3}}^{2}\leq C(b^{5}\epsilon^{2}+\frac{M^{2}}{b^{\frac{4}{3}}|\ln\epsilon|^{\frac{1}{2}}}), (2.6)

where ϵ=(0TBR(|T(E×ν)|2+|E×ν|2)𝑑s(x)𝑑t)12\epsilon=\Big{(}\int_{0}^{T}\int_{\partial B_{R}}\big{(}|T(\textbf{E}\times\nu)|^{2}+|\textbf{E}\times\nu|^{2}\big{)}ds(\textbf{x})dt\Big{)}^{\frac{1}{2}}.

Remark 2.2.

There are two parts in the stability estimates: the first parts are the data discrepancy, while this second parts comes from the high frequency tail of the function. The coefficient appearing in the Lipschitz part of (2.6)(\ref{es0}) is polynomial type. However, since bb is fixed in practice, these coefficients are constants and do not pose any problem. It is clear to conclude that the ill-posedness of the inverse time-dependent source problem decreases as the parameter bb increases. This is in consistent with the increasing stability results of [5] in the frequency domain: the ill-posedness decreases when the width of the wavenumber interval (0,b)(0,b) increases.

Next, we state the stability estimate for the second inverse problem (IP2). Let n(0,b2)n\in(0,b^{2}), b>1b>1. In the following theorem, we establish the increasing stability estimate of L2L^{2}-norm of F about bb. Let E=E(x,t;n)\textbf{E}=\textbf{E}(\textbf{x},t;n) satisfy (1.2) and (1.3).

Theorem 2.3.

Let F(x,t)H4([0,);H1(3))3\textbf{F}(\textbf{x},t)\in H^{4}([0,\infty);H^{1}({\mathbb{R}}^{3}))^{3} be such that supp F(x,t)\textbf{F}(\textbf{x},t) BR×(0,T0)\subset B_{R}\times(0,T_{0}) and let T>2Rn+T0T>2Rn+T_{0}. Assume that there exists M>1M>1 and FH4([0,);H1(3))3M\|\textbf{F}\|_{H^{4}([0,\infty);H^{1}({\mathbb{R}}^{3}))^{3}}\leq M. Then there exists a constant C>0C>0 depending on T0T_{0} and RR such that

FL2(4)2C(b11ϵ2+M2b|lnϵ|25).\displaystyle\|\textbf{F}\|^{2}_{L^{2}({\mathbb{R}}^{4})}\leq C\Big{(}b^{11}\,\epsilon^{2}+\frac{M^{2}}{b|\ln\epsilon|^{\frac{2}{5}}}\Big{)}. (2.7)

where ϵ=supn(0,b2)(0TBR(|T(E×ν)|2+|E×ν|2)𝑑s(x)𝑑t)12\epsilon=\sup\limits_{n\in(0,b^{2})}\Big{(}\int_{0}^{T}\int_{\partial B_{R}}\big{(}|T(\textbf{E}\times\nu)|^{2}+|\textbf{E}\times\nu|^{2}\big{)}ds(\textbf{x})dt\Big{)}^{\frac{1}{2}}.

Finally, we present the increasing stability for the third inverse problem (IP3). Assume that F(x,t)\textbf{F}(\textbf{x},t) takes the form

F(x,t)=f(x~,t)g(x3),x~=(x1,x2)2,t(0,+),\textbf{F}(\textbf{x},t)=\textbf{f}(\tilde{x},t)g(x_{3}),\quad\tilde{x}=(x_{1},x_{2})\in{\mathbb{R}}^{2},\quad t\in(0,+\infty), (2.8)

where f(x~,t)\textbf{f}(\tilde{x},t) has compact supports such that supp f \subset B~R0×(0,T0):={(x~,t)2×||x~|<R0, 0<t<T0}\widetilde{B}_{R_{0}}\times(0,T_{0}):=\{(\tilde{x},t)\in{\mathbb{R}}^{2}\times{\mathbb{R}}|\ |\tilde{x}|<R_{0},\ 0<t<T_{0}\}. Suppose that gg is given and supported in (R0,R0)(-R_{0},R_{0}) for some 0<R0<R/20<R_{0}<R/\sqrt{2}.

The Fourier transform of g(x3)g(x_{3}) of space variable x3x_{3} is given by

g^(ξ3)=12π3g(x3)eiξ3x3𝑑x3.\widehat{g}(\xi_{3})=\frac{1}{\sqrt{2\pi}}\int_{{\mathbb{R}}^{3}}g(x_{3})e^{-i\xi_{3}\cdot x_{3}}dx_{3}. (2.9)

We suppose

|g^(ξ3)|δ>0for allξ3(b,b),\displaystyle|\widehat{g}(\xi_{3})|\geq\delta>0\quad\mbox{for all}\quad\xi_{3}\in(-b,b), (2.10)

where b>1b>1.

Theorem 2.4.

Let f(x~,t)H4([0,);H1(2))3\textbf{f}(\tilde{x},t)\in H^{4}([0,\infty);H^{1}({\mathbb{R}}^{2}))^{3} be such that suppf(x~,t)B~R0×(0,T0)\textbf{f}(\tilde{x},t)\subset\widetilde{B}_{R_{0}}\times(0,T_{0}) and let T>2R+T0T>2R+T_{0}. Assume that there exists M>1M>1 such that fH4([0,);H1(2))3M\|\textbf{f}\|_{H^{4}([0,\infty);H^{1}({\mathbb{R}}^{2}))^{3}}\leq M. Then there exist constants α(0,1)\alpha\in(0,1) and C>0C>0 depending on nn, δ\delta, MM, T0T_{0} and RR such that

fL2(3)32C(b7ϵ2+b5e2b(1α)ϵ2α+M2b43|αlnϵ|12).\displaystyle\|\textbf{f}\|^{2}_{L^{2}({\mathbb{R}}^{3})^{3}}\leq C\Big{(}b^{7}\,\epsilon^{2}+b^{5}\,\,e^{2b(1-\alpha)}\epsilon^{2\alpha}+\frac{M^{2}}{b^{\frac{4}{3}}|\alpha\ln\epsilon|^{\frac{1}{2}}}\Big{)}. (2.11)

where ϵ=(0TBR(|T(E×ν)|2+|E×ν|2)𝑑s(x)𝑑t)12\epsilon=\Big{(}\int_{0}^{T}\int_{\partial B_{R}}\big{(}|T(\textbf{E}\times\nu)|^{2}+|\textbf{E}\times\nu|^{2}\big{)}ds(\textbf{x})dt\Big{)}^{\frac{1}{2}}.

3 Preliminaries and Proof of Theorem 2.1

In this section. The electric current density is assumed to take the form

F(x,t)=f(x)g(t)\textbf{F}(\textbf{x},t)=\textbf{f}(\textbf{x})g(t)

where gg is given. Let Einc\textbf{E}^{inc} and Hinc\textbf{H}^{inc} be the electric and magnetic plane waves. Explicitly, we have

Einc=pei(κpxd+ωt),Hinc=qei(κpxd+ωt)\textbf{E}^{inc}=\textbf{p}e^{-i(\kappa_{p}\textbf{x}\cdot\textbf{d}+\omega t)},\quad\textbf{H}^{inc}=\textbf{q}e^{-i(\kappa_{p}\textbf{x}\cdot\textbf{d}+\omega t)}

where d𝕊2\textbf{d}\in{\mathbb{S}}^{2} is a unit vector and p, q are two unit polarization vectors satisfying pd=0\textbf{p}\cdot\textbf{d}=0, q=d×p\textbf{q}=\textbf{d}\times\textbf{p}.

If κp2nω2=0\kappa_{p}^{2}-n\omega^{2}=0, it is easy to verify that Einc\textbf{E}^{inc} and Hinc\textbf{H}^{inc} satisfy the homogeneous Maxwell equations in 3{\mathbb{R}}^{3}:

nt2E(x,t)+×(×E(x,t))=0n\partial_{t}^{2}\textbf{E}(\textbf{x},t)+\nabla\times(\nabla\times\textbf{E}(\textbf{x},t))=0

and

nt2H(x,t)+×(×H(x,t))=0.n\partial_{t}^{2}\textbf{H}(\textbf{x},t)+\nabla\times(\nabla\times\textbf{H}(\textbf{x},t))=0.

Multiplying the both sides of (1.2) by Einc\textbf{E}^{inc}, we obtain

0TBR(nt2E+×(×E)Eincdxdt=0TBRf(x)g(t)Einc(x,t)dxdt.\int_{0}^{T}\int_{B_{R}}(n\partial_{t}^{2}\textbf{E}+\nabla\times(\nabla\times\textbf{E})\textbf{E}^{inc}\ \mathrm{d}\textbf{x}\mathrm{d}t=\int_{0}^{T}\int_{B_{R}}\textbf{f}(\textbf{x})g(t)\textbf{E}^{inc}(\textbf{x},t)\ \mathrm{d}\textbf{x}\mathrm{d}t. (3.12)

Integrating by parts, one deduces from the left hand side of (3.12) that

0TBR\displaystyle\int_{0}^{T}\int_{B_{R}} (nt2E+×(×E)Eincdxdt\displaystyle(n\partial_{t}^{2}\textbf{E}+\nabla\times(\nabla\times\textbf{E})\textbf{E}^{inc}\ \mathrm{d}\textbf{x}\mathrm{d}t
=\displaystyle= BRn(tE(x,t)Einc(x,t)E(x,t)tEinc(x,t))|0Tdx\displaystyle\int_{B_{R}}n(\partial_{t}\textbf{E}(\textbf{x},t)\textbf{E}^{inc}(\textbf{x},t)-\textbf{E}(\textbf{x},t)\partial_{t}\textbf{E}^{inc}(\textbf{x},t))\big{|}_{0}^{T}\;\mathrm{d}\textbf{x}
+0TBR(ν×(×E)Eincν×(×Einc)E)𝑑s(x)𝑑t.\displaystyle\quad+\int_{0}^{T}\int_{\partial B_{R}}\big{(}\nu\times(\nabla\times\textbf{E})\cdot\textbf{E}^{inc}-\nu\times(\nabla\times\textbf{E}^{inc})\cdot\textbf{E}\big{)}ds(\textbf{x})dt.
=\displaystyle= 0TBR((T(E×ν)Einc)+(E×ν)(×Einc))𝑑s(x)𝑑t.\displaystyle-\int_{0}^{T}\int_{\partial B_{R}}\big{(}(T(\textbf{E}\times\nu)\cdot\textbf{E}^{inc})+(\textbf{E}\times\nu)\cdot(\nabla\times\textbf{E}^{inc})\big{)}ds(\textbf{x})dt.

Note that, in the last step we have used the fact that E(x,t)=0\textbf{E}(\textbf{x},t)=0 when |x|<R|\textbf{x}|<R and t>T0+2Rt>T_{0}+2R, which follows straightforwardly from Huygens’ principle (see e.g., [9, Lemma 2.1]). This implies E(x,T)=tE(x,T)=0\textbf{E}(\textbf{x},T)=\partial_{t}\textbf{E}(\textbf{x},T)=0 for xBR\textbf{x}\in B_{R} and T>T0+2RT>T_{0}+2R. Hence, the integral over BRB_{R} on the left hand side of the previous identity vanishes.

BRpeiκpxdf(x)𝑑x0Tg(t)eiωt𝑑t=0TBR((T(E×ν)Einc)+(E×ν)(×Einc))𝑑s(x)𝑑t\int_{B_{R}}\textbf{p}e^{-i\kappa_{p}\textbf{x}\cdot\textbf{d}}\textbf{f}(\textbf{x})d\textbf{x}\int_{0}^{T}g(t)e^{-i\omega t}dt=-\int_{0}^{T}\int_{\partial B_{R}}\big{(}(T(\textbf{E}\times\nu)\cdot\textbf{E}^{inc})+(\textbf{E}\times\nu)\cdot(\nabla\times\textbf{E}^{inc})\big{)}ds(x)dt (3.13)

By the definition of Einc\textbf{E}^{inc}, one can check that

×Einc=iκpd×pei(κpxd+ωt)\nabla\times\textbf{E}^{inc}=-i\kappa_{p}\textbf{d}\times\textbf{p}e^{-i(\kappa_{p}\textbf{x}\cdot\textbf{d}+\omega t)}

which gives

|×Einc|=nω.|\nabla\times\textbf{E}^{inc}|=\sqrt{n}\omega.

Using the assumption about gg and the fact that f is supported in BRB_{R}, we derive from (3.13) together with the previous two relations that

|pf^(κpd)g^(ω)|\displaystyle|\textbf{p}\cdot\widehat{\textbf{f}}(\kappa_{p}\textbf{d})\widehat{g}(\omega)| =\displaystyle= |(2π)20T3pf(x)g(t)eiκpxdiωtdxdt|\displaystyle\Big{|}(2\pi)^{-2}\int_{0}^{T}\int_{\mathbb{R}^{3}}\textbf{p}\cdot\textbf{f}(\textbf{x})g(t)e^{-i\kappa_{p}\textbf{x}\cdot\textbf{d}-i\omega t}\ \mathrm{d}\textbf{x}\mathrm{d}t\Big{|}
=\displaystyle= |(2π)20TBRpf(x)g(t)Einc(x,t)dxdt|\displaystyle\Big{|}(2\pi)^{-2}\int_{0}^{T}\int_{B_{R}}\textbf{p}\cdot\textbf{f}(\textbf{x})g(t)\textbf{E}^{inc}(\textbf{x},t)\ \mathrm{d}\textbf{x}\mathrm{d}t\Big{|}
\displaystyle\leq C(1+ω)ϵ,\displaystyle C(1+\omega)\epsilon,

where ϵ=(0TBR(|T(E×ν)|2+|E×ν|2)𝑑s(x)𝑑t)12\epsilon=\Big{(}\int_{0}^{T}\int_{\partial B_{R}}\big{(}|T(\textbf{E}\times\nu)|^{2}+|\textbf{E}\times\nu|^{2}\big{)}ds(\textbf{x})dt\Big{)}^{\frac{1}{2}} represents the measurement data on BR×(0,T)\partial B_{R}\times(0,T). In view of the assumption (2.4), one obtains for ω(0,b)\omega\in(0,b), b>1b>1 and κp2=nω2\kappa_{p}^{2}=n\omega^{2} that

|pf^(κpd)|Cωϵ|g^(ω)|Cδ1(1+ω)ϵCbϵ,\begin{split}|\textbf{p}\cdot\widehat{\textbf{f}}(\kappa_{p}\textbf{d})|\leq C\frac{\omega\epsilon}{|\hat{g}(\omega)|}&\leq C\,\delta^{-1}(1+\omega)\epsilon\\ &\leq Cb\epsilon,\end{split} (3.14)

where C>0C>0 depends on nn, δ\delta, T0T_{0} and RR.

Repeating similar steps, we get

|qf^(κpd)|Cbϵfor all|κp|<nb.\displaystyle|\textbf{q}\cdot\hat{\textbf{f}}(\kappa_{p}\textbf{d})|\leq C\,b\,\epsilon\quad\mbox{for all}\ |\kappa_{p}|<\sqrt{n}b. (3.15)

On the other hand, Since f=0\nabla\cdot\textbf{f}=0, we obtain that

iκpdf^(κpd)=iκpBRdeiκpxdf(x)𝑑x=BReiκpxdf(x)𝑑x=BReiκpxdf(x)𝑑x=0,-i\kappa_{p}\textbf{d}\cdot\widehat{\textbf{f}}(-\kappa_{p}\textbf{d})=-i\kappa_{p}\int_{B_{R}}\textbf{d}e^{-i\kappa_{p}\textbf{x}\cdot\textbf{d}}\cdot\textbf{f}(\textbf{x})d\textbf{x}=\int_{B_{R}}\nabla e^{-i\kappa_{p}\textbf{x}\cdot\textbf{d}}\cdot\textbf{f}(\textbf{x})d\textbf{x}=\int_{B_{R}}e^{-i\kappa_{p}\textbf{x}\cdot\textbf{d}}\nabla\cdot\textbf{f}(\textbf{x})d\textbf{x}=0, (3.16)

which means df^(κpd)=0\textbf{d}\cdot\widehat{\textbf{f}}(-\kappa_{p}\textbf{d})=0. Using the Pythagorean theorem yields

|f^(κpd)|2=|pf^(κpd)|2+|qf^(κpd)|2+|df^(κpd)|2=|pf^(κpd)|2+|qf^(κpd)|2.|\widehat{\textbf{f}}(\kappa_{p}\textbf{d})|^{2}=|\textbf{p}\cdot\widehat{\textbf{f}}(\kappa_{p}\textbf{d})|^{2}+|\textbf{q}\cdot\widehat{\textbf{f}}(\kappa_{p}\textbf{d})|^{2}+|\textbf{d}\cdot\widehat{\textbf{f}}(\kappa_{p}\textbf{d})|^{2}=|\textbf{p}\cdot\widehat{\textbf{f}}(\kappa_{p}\textbf{d})|^{2}+|\textbf{q}\cdot\widehat{\textbf{f}}(\kappa_{p}\textbf{d})|^{2}. (3.17)

Let ξp=κpd\xi_{p}=\kappa_{p}\textbf{d}, we obtain from the Parseval theorem that

fL2(3)32=f^L2(3)32=3|f^(ξp)|2𝑑ξp=3|pf^(ξp)|2𝑑ξp+3|qf^(ξp)|2𝑑ξp.\|\textbf{f}\|_{L^{2}({\mathbb{R}}^{3})^{3}}^{2}=\|\widehat{\textbf{f}}\|_{L^{2}({\mathbb{R}}^{3})^{3}}^{2}=\int_{{\mathbb{R}}^{3}}|\widehat{\textbf{f}}(\xi_{p})|^{2}d\xi_{p}=\int_{{\mathbb{R}}^{3}}|\textbf{p}\cdot\widehat{\textbf{f}}(\xi_{p})|^{2}d\xi_{p}+\int_{{\mathbb{R}}^{3}}|\textbf{q}\cdot\widehat{\textbf{f}}(\xi_{p})|^{2}d\xi_{p}. (3.18)

Denote

I(s)=|ξp|ns|pf^(ξp)|2𝑑ξp.I(s)=\int_{|\xi_{p}|\leq\sqrt{n}s}|\textbf{p}\cdot\widehat{\textbf{f}}(\xi_{p})|^{2}d\xi_{p}.

Since the integrand I(s)I(s) is an entire analytic function of ξ\xi, the integral I(s)I(s) with respect to ξp\xi_{p} can be taken over by any path joining points 0 and ns\sqrt{n}s in complex plane. Thus I(s)I(s) is an entire analytic function of s=s1+is2s=s_{1}+is_{2} (s1,s2)(s_{1},s_{2}\in\mathbb{R}) and the following estimate holds.

Lemma 3.1.

Let f(x)L2(3)3\textbf{f}(\textbf{x})\in L^{2}(\mathbb{R}^{3})^{3}, suppfBR\mathrm{supp}\ \textbf{f}\subset B_{R}. Then

|I(s)|(4π3)2R3n3|s|3e2Rn|s2|fL2(3)32,s=s1+is2.|I(s)|\leq(\frac{4\pi}{3})^{2}\,R^{3}\,\sqrt{n}^{3}|s|^{3}e^{2R\sqrt{n}|s_{2}|}||\textbf{f}||^{2}_{L^{2}(\mathbb{R}^{3})^{3}},\qquad s=s_{1}+is_{2}\in{\mathbb{C}}. (3.19)
Proof.

Set l=nsll=\sqrt{n}sl^{\prime} for l(0,1)l^{\prime}\in(0,1). Then it is easy to get

I(s)\displaystyle I(s) |ξp|ns|f^|2(ξp)𝑑ξp\displaystyle\leq\int_{|\xi_{p}|\leq\sqrt{n}s}|\widehat{\textbf{f}}|^{2}(\xi_{p})d\xi_{p}
=0ns𝕊2|f^(lθ^)|2l2dθ^dl\displaystyle=\int_{0}^{\sqrt{n}s}\int_{\mathbb{S}^{2}}|\widehat{\textbf{f}}(l\hat{\theta})|^{2}l^{2}\mathrm{d}\hat{\theta}\mathrm{d}l
=01𝕊2|f^(cnslθ^)|2(ns)3l2dθ^dl.\displaystyle=\int_{0}^{1}\int_{\mathbb{S}^{2}}|\widehat{\textbf{f}}(c_{n}sl^{\prime}\hat{\theta})|^{2}(\sqrt{n}s)^{3}l^{\prime 2}\mathrm{d}\hat{\theta}\mathrm{d}l^{\prime}.

Noting the elementary inequality |einslθ^x|en|s2|R|e^{-i\sqrt{n}sl^{\prime}\hat{\theta}\cdot\textbf{x}}|\leq e^{\sqrt{n}|s_{2}|R} for all xBRx\in B_{R} and θ^𝕊2\hat{\theta}\in\mathbb{S}^{2}, we have

|I(s)|\displaystyle|I(s)| |01𝕊2|BRf(x)einslθ^xdx|2(cns)3l2dθ^dl|\displaystyle\leq\left|\int_{0}^{1}\int_{\mathbb{S}^{2}}\left|\int_{B_{R}}\textbf{f}(\textbf{x})e^{-i\sqrt{n}sl^{\prime}\hat{\theta}\cdot\textbf{x}}\mathrm{d}\textbf{x}\right|^{2}(c_{n}s)^{3}l^{\prime 2}\mathrm{d}\hat{\theta}\mathrm{d}l^{\prime}\right|
4π3R301𝕊2n3|s|3(BR|f(x)|2|e2nR|s2||dx)dθ^dl\displaystyle\leq\frac{4\pi}{3}R^{3}\int_{0}^{1}\int_{\mathbb{S}^{2}}\sqrt{n}^{3}|s|^{3}\left(\int_{B_{R}}|\textbf{f}(\textbf{x})|^{2}|e^{2\sqrt{n}R|s_{2}|}|\,\mathrm{d}\textbf{x}\right)\mathrm{d}\hat{\theta}\mathrm{d}l^{\prime}
(4π3)2R3n3|s|3e2Rn|s2|fL2(3)32.\displaystyle\leq(\frac{4\pi}{3})^{2}\,R^{3}\,\sqrt{n}^{3}\,|s|^{3}e^{2R\sqrt{n}|s_{2}|}||\textbf{f}||^{2}_{L^{2}(\mathbb{R}^{3})^{3}}.

This completes the Lemma 3.1. ∎

The following Lemma is essential to show the relation between I(s)I(s) for s(b,)s\in(b,\infty) with I(b).I(b). Its proof can be found in [13].

Lemma 3.2.

Let J(z)J(z) be an analytic function in S={z=x+iy:π4<argz<π4}S=\{z=x+iy\in\mathbb{C}:-\frac{\pi}{4}<\arg z<\frac{\pi}{4}\} and continuous in S¯\overline{S} satisfying

{|J(z)|ϵ,z(0,L],|J(z)|V,zS,|J(0)|=0.\begin{cases}|J(z)|\leq\epsilon,\ &z\in(0,L],\\ |J(z)|\leq V,\ &z\in S,\\ |J(0)|=0.\end{cases}

Then there exists a function μ(z)\mu(z) satisfying

{μ(z)12,z(L,214L),μ(z)1π((zL)41)12,z(214L,)\begin{cases}\mu(z)\geq\frac{1}{2},\ \ &z\in(L,2^{\frac{1}{4}}L),\\ \mu(z)\geq\frac{1}{\pi}((\frac{z}{L})^{4}-1)^{-\frac{1}{2}},\ \ &z\in(2^{\frac{1}{4}}L,\infty)\end{cases}

such that

|J(z)|Vϵμ(z),z(L,).|J(z)|\leq V\epsilon^{\mu(z)},\ \ \forall z\in(L,\infty).

Let the sector SS\subset{\mathbb{C}} be given as in Lemma 3.2. Now, it follows from Lemma 3.1 that

|I(s)e(2Rn+1)s|CM2for allsS,|I(s)e^{-(2R\sqrt{n}+1)s}|\leq CM^{2}\quad\mbox{for all}\quad s\in S,

where C>0C>0 depends on nn and RR. Recalling from a priori estimate (3.14), we obtain

I(s)=|ξp|ns|pf^(ξp)|2𝑑ξpCs3b2ϵ2,s(0,b]I(s)=\int_{|\xi_{p}|\leq\sqrt{n}s}|\textbf{p}\cdot\widehat{\textbf{f}}(\xi_{p})|^{2}d\xi_{p}\leq C\,s^{3}\,b^{2}\,\epsilon^{2},\quad s\in(0,b]

where C>0C>0 depends on nn, T0T_{0} and RR. Hence

|I(s)e(2Rn+1)s|Cb2ϵ2,s(0,b].|I(s)e^{-(2R\sqrt{n}+1)s}|\leq Cb^{2}\,\epsilon^{2},\ \ s\in(0,b].

Then applying Lemma 3.2 with L=bL=b to the function J(s):=1b2I(s)e(2Rn+1)sJ(s):=\frac{1}{b^{2}}I(s)e^{-(2R\sqrt{n}+1)s} , we know that there exists a function μ(s)\mu(s) satisfying

{μ(s)12,s(b,214b),μ(s)1π((sb)41)12,s(214b,)\begin{cases}\mu(s)\geq\frac{1}{2},\ \ &s\in(b,2^{\frac{1}{4}}b),\\ \mu(s)\geq\frac{1}{\pi}((\frac{s}{b})^{4}-1)^{-\frac{1}{2}},\ \ &s\in(2^{\frac{1}{4}}b,\infty)\end{cases}

such that

|1b2I(s)e(2Rn+1)s|CM2ϵ2μfor alls(b,),|\frac{1}{b^{2}}I(s)e^{-(2R\sqrt{n}+1)s}|\leq CM^{2}\epsilon^{2\mu}\ \ \quad\mbox{for all}\quad s\in(b,\infty),

where C>0C>0 depends on nn, T0T_{0} and RR.

Now we show the proof of Theorem 2.1. We assume that ϵ<e1\epsilon<e^{-1}, otherwise the estimate is obvious. Let

s={1((2Rn+3)π)13b23|lnϵ|14,if214((2Rn+3)π)13b13<|lnϵ|14,b,if|lnϵ|14214((2Rn+3)π)13b13.s=\begin{cases}\frac{1}{((2R\sqrt{n}+3)\pi)^{\frac{1}{3}}}b^{\frac{2}{3}}|\ln\epsilon|^{\frac{1}{4}},\qquad&\mbox{if}\quad 2^{\frac{1}{4}}((2R\sqrt{n}+3)\pi)^{\frac{1}{3}}b^{\frac{1}{3}}<|\ln\epsilon|^{\frac{1}{4}},\\ b,\qquad&\mbox{if}\quad|\ln\epsilon|^{\frac{1}{4}}\leq 2^{\frac{1}{4}}((2R\sqrt{n}+3)\pi)^{\frac{1}{3}}b^{\frac{1}{3}}.\end{cases}

Case (i): 214((2Rn+3)π)13b13<|lnϵ|142^{\frac{1}{4}}((2R\sqrt{n}+3)\pi)^{\frac{1}{3}}b^{\frac{1}{3}}<|\ln\epsilon|^{\frac{1}{4}}. Then we have

|I(s)|\displaystyle|I(s)| \displaystyle\leq CM2b2ϵ2μe(2Rn+1)s\displaystyle CM^{2}b^{2}\epsilon^{2\mu}e^{(2R\sqrt{n}+1)s}
=\displaystyle= CM2b2e(2Rn+1)s2μ(s)|lnϵ|\displaystyle CM^{2}b^{2}e^{(2R\sqrt{n}+1)s-2\mu(s)|\ln\epsilon|}
\displaystyle\leq CM2b2e(2Rn+3)((2R+3)π)13b23|lnϵ|142|lnϵ|π(bs)2\displaystyle CM^{2}b^{2}e^{\frac{(2R\sqrt{n}+3)}{((2R+3)\pi)^{\frac{1}{3}}}b^{\frac{2}{3}}|\ln\epsilon|^{\frac{1}{4}}-\frac{2|\ln\epsilon|}{\pi}(\frac{b}{s})^{2}}
=\displaystyle= CM2b2e2((2Rn+3)2π)13b23|lnϵ|12(112|lnϵ|14),\displaystyle CM^{2}b^{2}e^{-2\big{(}\frac{(2R\sqrt{n}+3)^{2}}{\pi}\big{)}^{\frac{1}{3}}b^{\frac{2}{3}}|\ln\epsilon|^{\frac{1}{2}}(1-\frac{1}{2}|\ln\epsilon|^{-\frac{1}{4}})},

where C>0C>0 depends on nn, T0T_{0} and RR. Noting that |lnϵ|14<1|\ln\epsilon|^{-\frac{1}{4}}<1 and ((2Rn+3)2π)13>1\big{(}\frac{(2R\sqrt{n}+3)^{2}}{\pi}\big{)}^{\frac{1}{3}}>1, we obtain

|I(s)|CM2b2eb23|lnϵ|12.|I(s)|\leq CM^{2}b^{2}e^{-b^{\frac{2}{3}}|\ln\epsilon|^{\frac{1}{2}}}.

Using the inequality et6!t6e^{-t}\leq\frac{6!}{t^{6}} for t>0t>0, we get

|I(s)|CM2b2|lnϵ|3.|I(s)|\leq C\frac{M^{2}}{b^{2}|\ln\epsilon|^{3}}. (3.20)

Since b2|lnϵ|3b43|lnϵ|12b^{2}|\ln\epsilon|^{3}\geq b^{\frac{4}{3}}|\ln\epsilon|^{\frac{1}{2}} when b>1b>1 and |lnϵ|>1|\ln\epsilon|>1. Hence

I(s)+|ξp|>ns|pf^(ξp)|2dξpI(s)+M2n2s2C(M2b4|lnϵ|3+M2b43|lnϵ|12)CM2b43|lnϵ|12,\begin{split}I(s)+\int_{|\xi_{p}|>\sqrt{n}s}|\textbf{p}\cdot\widehat{\textbf{f}}(\xi_{p})|^{2}\,\mathrm{d}\xi_{p}&\leq I(s)+\frac{M^{2}}{n^{2}s^{2}}\\ &\leq C(\frac{M^{2}}{b^{4}|\ln\epsilon|^{3}}+\frac{M^{2}}{b^{\frac{4}{3}}|\ln\epsilon|^{\frac{1}{2}}})\\ &\leq\frac{CM^{2}}{b^{\frac{4}{3}}|\ln\epsilon|^{\frac{1}{2}}},\end{split} (3.21)

where C>0C>0 depends on nn, T0T_{0} and RR.

Case (ii): |lnϵ|14214((2Rn+3)π)13b13|\ln\epsilon|^{\frac{1}{4}}\leq 2^{\frac{1}{4}}((2R\sqrt{n}+3)\pi)^{\frac{1}{3}}b^{\frac{1}{3}}. In this case we have s=bs=b by the choice of ss and |I(b)|Cb5ϵ2|I(b)|\leq C\,b^{5}\epsilon^{2}. Hence,

I(b)+|ξp|>nb|pf^(ξp)|2dξpC(b5ϵ2+M2b2)C(b5ϵ2+M2b43|lnϵ|12),\begin{split}I(b)+\int_{|\xi_{p}|>\sqrt{n}b}|\textbf{p}\cdot\widehat{\textbf{f}}(\xi_{p})|^{2}\,\mathrm{d}\xi_{p}\leq C(b^{5}\epsilon^{2}+\frac{M^{2}}{b^{2}})\\ \leq C(b^{5}\epsilon^{2}+\frac{M^{2}}{b^{\frac{4}{3}}|\ln\epsilon|^{\frac{1}{2}}}),\end{split} (3.22)

where C>0C>0 depends on nn, δ\delta, T0T_{0} and RR. Combining (3.21) and (3.22), we finally obtain

3|pf^(ξp)|2𝑑ξpC(b5ϵ2+M2b43|lnϵ|12).\int_{{\mathbb{R}}^{3}}|\textbf{p}\cdot\widehat{\textbf{f}}(\xi_{p})|^{2}d\xi_{p}\leq C(b^{5}\epsilon^{2}+\frac{M^{2}}{b^{\frac{4}{3}}|\ln\epsilon|^{\frac{1}{2}}}).

Repeating similar steps by multiplying Hinc\textbf{H}^{inc} on both sides of the equation (1.2), we get

3|qf^(ξp)|2𝑑ξpC(b5ϵ2+M2b43|lnϵ|12),\int_{{\mathbb{R}}^{3}}|\textbf{q}\cdot\widehat{\textbf{f}}(\xi_{p})|^{2}d\xi_{p}\leq C(b^{5}\epsilon^{2}+\frac{M^{2}}{b^{\frac{4}{3}}|\ln\epsilon|^{\frac{1}{2}}}),

where C>0C>0 depends on nn, δ\delta, T0T_{0} and RR. Combining the above estimates and (3.18), we complete the proof.

4 Proof of Theorem 2.3

In this section. Let n(0,b2)n\in(0,b^{2}) for b>1b>1. Through this section, C>0C>0 denotes a generic constant which is independent of nn, may vary from line to line. Consider the equation

{nt2E(x,t)+×(×E(x,t))=F(x,t),(x,t)3×(0,),E(x,0)=0,tE(x,0)=0,x3.\begin{cases}n\partial_{t}^{2}\textbf{E}(\textbf{x},t)+\nabla\times(\nabla\times\textbf{E}(\textbf{x},t))=\textbf{F}(\textbf{x},t),\ &(\textbf{x},t)\in{\mathbb{R}}^{3}\times(0,\infty),\\ \textbf{E}(\textbf{x},0)=0,\quad\partial_{t}\textbf{E}(\textbf{x},0)=0,\ &\textbf{x}\in{\mathbb{R}}^{3}.\end{cases} (4.23)

Assume that E(x,t):=E(x,t;n)\textbf{E}(\textbf{x},t):=\textbf{E}(\textbf{x},t;n).

Multiplying the both sides of (4.23) by Einc\textbf{E}^{inc} and using the integration by parts over BRB_{R}, we obtain

0TBR(nt2E+×(×E)Eincdxdt=0TBRF(x,t)Einc(x,t)dxdt.\int_{0}^{T}\int_{B_{R}}(n\partial_{t}^{2}\textbf{E}+\nabla\times(\nabla\times\textbf{E})\textbf{E}^{inc}\ \mathrm{d}\textbf{x}\mathrm{d}t=\int_{0}^{T}\int_{B_{R}}\textbf{F}(\textbf{x},t)\textbf{E}^{inc}(\textbf{x},t)\ \mathrm{d}\textbf{x}\mathrm{d}t. (4.24)

Integrating by parts, one deduces from the left hand side of (4.24) that

0TBR\displaystyle\int_{0}^{T}\int_{B_{R}} (nt2E+×(×E)Eincdxdt\displaystyle(n\partial_{t}^{2}\textbf{E}+\nabla\times(\nabla\times\textbf{E})\textbf{E}^{inc}\ \mathrm{d}\textbf{x}\mathrm{d}t
=\displaystyle= BRn(tE(x,t)Einc(x,t)E(x,t)tEinc(x,t))|0Tdx\displaystyle\int_{B_{R}}n(\partial_{t}\textbf{E}(\textbf{x},t)\textbf{E}^{inc}(\textbf{x},t)-\textbf{E}(\textbf{x},t)\partial_{t}\textbf{E}^{inc}(\textbf{x},t))\big{|}_{0}^{T}\;\mathrm{d}\textbf{x}
+0TBR(ν×(×E)Eincν×(×Einc)E)𝑑s(x)𝑑t.\displaystyle\quad+\int_{0}^{T}\int_{\partial B_{R}}\big{(}\nu\times(\nabla\times\textbf{E})\cdot\textbf{E}^{inc}-\nu\times(\nabla\times\textbf{E}^{inc})\cdot\textbf{E}\big{)}ds(\textbf{x})dt.
=\displaystyle= 0TBR((T(E×ν)Einc)+(E×ν)(×Einc))𝑑s(x)𝑑t.\displaystyle-\int_{0}^{T}\int_{\partial B_{R}}\big{(}(T(\textbf{E}\times\nu)\cdot\textbf{E}^{inc})+(\textbf{E}\times\nu)\cdot(\nabla\times\textbf{E}^{inc})\big{)}ds(\textbf{x})dt.

Note that, in the last step we have used the fact that E(x,t)=0\textbf{E}(\textbf{x},t)=0 when |x|<R|\textbf{x}|<R and t>T0+2Rt>T_{0}+2R, which follows straightforwardly from Huygens’ principle (see e.g., [9, Lemma 2.1]). This implies E(x,T)=tE(x,T)=0\textbf{E}(\textbf{x},T)=\partial_{t}\textbf{E}(\textbf{x},T)=0 for xBR\textbf{x}\in B_{R} and T>T0+2RT>T_{0}+2R. Hence, the integral over BRB_{R} on the left hand side of the previous identity vanishes. Thus

BR0Tpei(ξpx+ωt)F(x,t)𝑑x𝑑t=0TBR((T(E×ν)Einc)+(E×ν)(×Einc))𝑑s(x)𝑑t.\int_{B_{R}}\int_{0}^{T}\textbf{p}e^{-i(\xi_{p}\cdot\textbf{x}+\omega t)}\cdot\textbf{F}(\textbf{x},t)d\textbf{x}dt=-\int_{0}^{T}\int_{\partial B_{R}}\big{(}(T(\textbf{E}\times\nu)\cdot\textbf{E}^{inc})+(\textbf{E}\times\nu)\cdot(\nabla\times\textbf{E}^{inc})\big{)}ds(\textbf{x})dt. (4.25)

Define

F^(ξ,ω)=(2π)24F(x,t)ei(ξx+ωt)𝑑x𝑑t,\widehat{\textbf{F}}(\xi,\omega)=(2\pi)^{-2}\int_{{\mathbb{R}}^{4}}\textbf{F}(\textbf{x},t)e^{-i(\xi\cdot\textbf{x}+\omega t)}d\textbf{x}dt,

with (ξ,ω)=(ξ1,ξ2,ξ3,ω)4(\xi,\omega)=(\xi_{1},\xi_{2},\xi_{3},\omega)\in{\mathbb{R}}^{4}. Since supp F(x,t)\textbf{F}(\textbf{x},t) BR×(0,T0)\subset B_{R}\times(0,T_{0}), we have

(2π)2pF^(ξp,ω)=0TBRpF(x,t)ei(ξpx+ωt)𝑑x𝑑t=0TBR((T(E×ν)Einc)+(E×ν)(×Einc))𝑑s(x)𝑑t.\begin{split}(2\pi)^{2}\textbf{p}\cdot\widehat{\textbf{F}}(\xi_{p},\omega)&=\int_{0}^{T}\int_{B_{R}}\textbf{p}\cdot\textbf{F}(\textbf{x},t)e^{-i(\xi_{p}\cdot\textbf{x}+\omega t)}d\textbf{x}dt\\ &=-\int_{0}^{T}\int_{\partial B_{R}}\big{(}(T(\textbf{E}\times\nu)\cdot\textbf{E}^{inc})+(\textbf{E}\times\nu)\cdot(\nabla\times\textbf{E}^{inc})\big{)}ds(\textbf{x})dt.\end{split} (4.26)

Consider the set (see Figure 1)

Es={(ξ,ω)4||ξ|2nω2=0,|ω|<s,n(0,s2)}.E_{s}=\{(\xi,\omega)\in{\mathbb{R}}^{4}|\ |\xi|^{2}-n\omega^{2}=0,\ |\omega|<s,\ n\in(0,s^{2})\}.
Refer to caption
Figure 1: EsE_{s} is the shadow area, ζ2=|ξ|2\zeta^{2}=|\xi|^{2}.

Combining (4.26)(\ref{pF}), we have

|pF^(ξp,ω)|Cb2ϵ,(ξp,ω)Eb|\textbf{p}\cdot\widehat{\textbf{F}}(\xi_{p},\omega)|\leq Cb^{2}\epsilon,\quad(\xi_{p},\omega)\in{E_{b}} (4.27)

where ϵ=supn(0,b2)(0TBR(|T(E×ν)|2+|E×ν|2)𝑑s(x)𝑑t)12\epsilon=\sup\limits_{n\in(0,b^{2})}\Big{(}\int_{0}^{T}\int_{\partial B_{R}}\big{(}|T(\textbf{E}\times\nu)|^{2}+|\textbf{E}\times\nu|^{2}\big{)}ds(\textbf{x})dt\Big{)}^{\frac{1}{2}}. Denote

I(s):=Es|pF^(ξp,ω)|2𝑑ξp𝑑ω.I(s):=\int_{E_{s}}|\textbf{p}\cdot\widehat{\textbf{F}}(\xi_{p},\omega)|^{2}d\xi_{p}\,d\omega. (4.28)

It is easy to verify from (4.28) that

|I(s)|C|Es|b4ϵ2,s[0,b]\displaystyle|I(s)|\leq C\,|E_{s}|\,b^{4}\,\epsilon^{2},\quad s\in[0,b] (4.29)

and

I(s)Es|F^(ξp,ω)|2𝑑ξp𝑑ω.I(s)\leq\int_{E_{s}}|\widehat{\textbf{F}}(\xi_{p},\omega)|^{2}d\xi_{p}\,d\omega. (4.30)

Using the polar coordinates, we deduce that

Es{(ξ,ω)|ω0}|F^(ξ,ω)|2𝑑ξ𝑑ω=0s(02π0π0sω|F^(rξ^,ω)|2r2sinφdrdθdφ)𝑑ω.\int_{E_{s}\cap\{(\xi,\omega)|\ \omega\geq 0\}}|\widehat{\textbf{F}}(\xi,\omega)|^{2}d\xi d\omega=\int_{0}^{s}\big{(}\int_{0}^{2\pi}\int_{0}^{\pi}\int_{0}^{s\omega}|\widehat{\textbf{F}}(r\hat{\xi},\omega)|^{2}r^{2}\sin\varphi drd\theta d\varphi\big{)}d\omega.

Let r=sωr^r=s\omega\hat{r} and ω=sω^\omega=s\hat{\omega} for r^,ω^(0,1)\hat{r},\hat{\omega}\in(0,1). A simple calculation yields

Es{(ξ,ω)|ω0}|F^(ξ,ω)|2dξdω=0s(02π0π01|F^(sωr^ξ^,ω)|2(sω)3r^2sinφdrdθdφ)𝑑ω=01(02π0π01|F^(s2ωr^ξ^,ω)|2s(s2ω^)3r^2sinφdrdθdφ)𝑑ω^=01(02π0π01|4F^(x,t)ei(s2ω^r^ξ^x+sω^t)𝑑x𝑑t|2s(s2ω^)3r^2sinφdrdθdφ)𝑑ω^.\begin{split}\int_{E_{s}\cap\{(\xi,\omega)|\ \omega\geq 0\}}&|\widehat{\textbf{F}}(\xi,\omega)|^{2}d\xi d\omega=\int_{0}^{s}\big{(}\int_{0}^{2\pi}\int_{0}^{\pi}\int_{0}^{1}|\widehat{\textbf{F}}(s\omega\hat{r}\hat{\xi},\omega)|^{2}(s\omega)^{3}\hat{r}^{2}\sin\varphi drd\theta d\varphi\big{)}d\omega\\ &=\int_{0}^{1}\big{(}\int_{0}^{2\pi}\int_{0}^{\pi}\int_{0}^{1}|\widehat{\textbf{F}}(s^{2}\omega\hat{r}\hat{\xi},\omega)|^{2}s(s^{2}\hat{\omega})^{3}\hat{r}^{2}\sin\varphi drd\theta d\varphi\big{)}d\hat{\omega}\\ &=\int_{0}^{1}\big{(}\int_{0}^{2\pi}\int_{0}^{\pi}\int_{0}^{1}|\int_{{\mathbb{R}}^{4}}\widehat{\textbf{F}}(x,t)e^{-i(s^{2}\hat{\omega}\hat{r}\hat{\xi}\cdot x+s\hat{\omega}t)}dxdt|^{2}s(s^{2}\hat{\omega})^{3}\hat{r}^{2}\sin\varphi drd\theta d\varphi\big{)}d\hat{\omega}.\end{split}

This integrals are analytic functions of s=s1+is2s=s_{1}+is_{2}, s1,s2s_{1},s_{2}\in{\mathbb{R}}. Noting that ei(s2ω^r^ξ^x+sω^t)e2R|s1s2|+T|s2|e^{-i(s^{2}\hat{\omega}\hat{r}\hat{\xi}\cdot x+s\hat{\omega}t)}\leq e^{2R|s_{1}s_{2}|+T|s_{2}|}. We have for all sSs\in S that

|Es{(ξ,ω)|ω0}|F^(ξ,ω)|2𝑑ξ𝑑ω|CM2|s|6e2R|s1s2|+T|s2|.\big{|}\int_{E_{s}\cap\{(\xi,\omega)|\omega\geq 0\}}|\widehat{\textbf{F}}(\xi,\omega)|^{2}d\xi d\omega\big{|}\leq CM^{2}|s|^{6}e^{2R|s_{1}s_{2}|+T|s_{2}|}.

Hence we also obtain

|I(s)|CM2|s|6e2R|s1s2|+T|s2|,sS.|I(s)|\leq C\,M^{2}|s|^{6}e^{2R|s_{1}s_{2}|+T|s_{2}|},\quad s\in S.

Let Δ=max{2R,T}\Delta=\max\{2R,T\}, it follows for all sSs\in S that

|e(Δ+1)s(Δ+1)s2I(s)|CM2.|e^{-(\Delta+1)s-(\Delta+1)s^{2}}I(s)|\leq CM^{2}.

Recalling from (4.29) a prior estimate, we obtain

|e(Δ+1)s(Δ+1)s2I(s)|Cb4ϵ2for alls[0,b].|e^{-(\Delta+1)s-(\Delta+1)s^{2}}I(s)|\leq C\,b^{4}\,\epsilon^{2}\quad\mbox{for all}\quad s\in[0,b].

Then applying Lemma 3.2 with L=bL=b to the function 1b4e(Δ+1)s(Δ+1)s2I(s)\frac{1}{b^{4}}e^{-(\Delta+1)s-(\Delta+1)s^{2}}I(s), we know that

|I(s)|CM2b4e2(Δ+1)s2ϵ2μ,s(b,).|I(s)|\leq CM^{2}\,b^{4}\,e^{2(\Delta+1)s^{2}}\epsilon^{2\mu},\quad\forall s\in(b,\infty).

Consider the set

Es1={(ξ,ω)4||ω|s,|ξ|s|ω|},E^{1}_{s}=\{(\xi,\omega)\in{\mathbb{R}}^{4}|\ \ |\omega|\geq s,\ |\xi|\leq s|\omega|\},

we have by using the Parseval’s identity that

I1(s):=Es1|pF^|2𝑑ξp𝑑ω1s23|(pF)^|2𝑑ξp𝑑ωCM2s2.\begin{split}I_{1}(s):=\int_{E^{1}_{s}}|\textbf{p}\cdot\widehat{\textbf{F}}|^{2}d\xi_{p}\,d\omega\leq\frac{1}{s^{2}}\int_{{\mathbb{R}}^{3}}|\widehat{\nabla(\textbf{p}\cdot\textbf{F})}|^{2}d\xi_{p}\,d\omega\leq\,C\,\frac{M^{2}}{s^{2}}.\end{split}

Denote

I2(s):=Es2|pF^|2𝑑ξp𝑑ω,I_{2}(s):=\int_{E^{2}_{s}}|\textbf{p}\cdot\widehat{\textbf{F}}|^{2}d\xi_{p}\,d\omega,

where

Es2={(ξ,ω)4||ξ|s|ω|}.E^{2}_{s}=\{(\xi,\omega)\in{\mathbb{R}}^{4}|\ \ |\xi|\geq s|\omega|\}.

It is easy to obtain

I2(s)Es2|F^|2𝑑ξ𝑑w,I_{2}(s)\leq\int_{E^{2}_{s}}|\widehat{\textbf{F}}|^{2}d\xi\,dw,

Similarly, by using the polar coordinates. Let r=sr^r=s\hat{r} and ω=s2r^ω^\omega=s^{2}\hat{r}\hat{\omega} for r^,ω^(0,1)\hat{r},\hat{\omega}\in(0,1). We get

Es2{(ξ,ω)|ω0}|pF^(ξ,ω)|2𝑑ξ𝑑ω=02π0π0(0rs|pF^(rξ^,ω)|2𝑑ω)r2sinφdrdθdφ=02π0π0(01|pF^(rξ^,1srω^)|21sr𝑑ω^)r2sinφdrdθdφ=02π0π01(01|pF^(rξ^,1srω^)|21sr𝑑ω^)r2sinφdrdθdφ+02π0π1(01|pF^(rξ^,1srω^)|21sr𝑑ω^)r2sinφdrdθdφ.\begin{split}&\int_{E^{2}_{s}\cap\{(\xi,\omega)|\ \omega\geq 0\}}|\textbf{p}\cdot\widehat{\textbf{F}}(\xi,\omega)|^{2}d\xi d\omega\\ &=\int_{0}^{2\pi}\int_{0}^{\pi}\int_{0}^{\infty}\big{(}\int_{0}^{\frac{r}{s}}|\textbf{p}\cdot\widehat{\textbf{F}}(r\hat{\xi},\omega)|^{2}d\omega\big{)}r^{2}\sin\varphi dr\,d\theta\,d\varphi\\ &=\int_{0}^{2\pi}\int_{0}^{\pi}\int_{0}^{\infty}\big{(}\int_{0}^{1}|\textbf{p}\cdot\widehat{\textbf{F}}(r\hat{\xi},\frac{1}{s}r\hat{\omega})|^{2}\frac{1}{s}rd\hat{\omega}\big{)}r^{2}\sin\varphi dr\,d\theta\,d\varphi\\ &=\int_{0}^{2\pi}\int_{0}^{\pi}\int_{0}^{1}\big{(}\int_{0}^{1}|\textbf{p}\cdot\widehat{\textbf{F}}(r\hat{\xi},\frac{1}{s}r\hat{\omega})|^{2}\frac{1}{s}rd\hat{\omega}\big{)}r^{2}\sin\varphi dr\,d\theta\,d\varphi\\ &+\int_{0}^{2\pi}\int_{0}^{\pi}\int_{1}^{\infty}\big{(}\int_{0}^{1}|\textbf{p}\cdot\widehat{\textbf{F}}(r\hat{\xi},\frac{1}{s}r\hat{\omega})|^{2}\frac{1}{s}rd\hat{\omega}\big{)}r^{2}\sin\varphi dr\,d\theta\,d\varphi.\end{split}

Since

01|pF^(rξ^,1nrω^)|2𝑑ω^=1r601|4pΔF(x,t)ei(rξ^x+1nrω^t)𝑑x𝑑t|2𝑑ω^M2r3,\begin{split}\int_{0}^{1}|\textbf{p}\cdot\widehat{\textbf{F}}(r\hat{\xi},\frac{1}{\sqrt{n}}r\hat{\omega})|^{2}d\hat{\omega}=\frac{1}{r^{6}}\int_{0}^{1}|\int_{{\mathbb{R}}^{4}}\textbf{p}\cdot\Delta\textbf{F}(x,t)e^{-i(r\hat{\xi}\cdot x+\frac{1}{\sqrt{n}}r\hat{\omega}t)}dxdt|^{2}d\hat{\omega}\leq\frac{M^{2}}{r^{3}},\end{split}

which gives

|Es2{(ξ,ω)|ω0}|pF^(ξ,ω)|2𝑑ξ𝑑ω|CM2s.\big{|}\int_{E^{2}_{s}\cap\{(\xi,\omega)|\ \omega\geq 0\}}|\textbf{p}\cdot\widehat{\textbf{F}}(\xi,\omega)|^{2}d\xi d\omega\big{|}\leq C\,\frac{M^{2}}{s}.

Consequently

I2(s)CM2s.I_{2}(s)\leq C\,\frac{M^{2}}{s}.

Now we show the proof of Theorem 2.3. We assume that ϵ<e1\epsilon<e^{-1}, otherwise the estimate is obvious. Let

s={1(2(Δ+2)π)14b12|lnϵ|15if|lnϵ|15>214b12(2(Δ+2)π)14,bif|lnϵ|15214b12(2(Δ+2)π)13.\displaystyle s=\begin{cases}\frac{1}{(2(\Delta+2)\pi)^{\frac{1}{4}}}b^{\frac{1}{2}}|\ln\epsilon|^{\frac{1}{5}}&\textrm{if}\ |\ln\epsilon|^{\frac{1}{5}}>2^{\frac{1}{4}}b^{\frac{1}{2}}(2(\Delta+2)\pi)^{\frac{1}{4}},\\ b&\textrm{if}\ |\ln\epsilon|^{\frac{1}{5}}\leq 2^{\frac{1}{4}}b^{\frac{1}{2}}(2(\Delta+2)\pi)^{\frac{1}{3}}.\end{cases} (4.31)

Case (i): |lnϵ|15>214b12(2(Δ+2)π)14|\ln\epsilon|^{\frac{1}{5}}>2^{\frac{1}{4}}b^{\frac{1}{2}}(2(\Delta+2)\pi)^{\frac{1}{4}}. One can check that

s>214b.s>2^{\frac{1}{4}}b.

Thus, using Lemma 3.2, we obtain

|I(s)|\displaystyle|I(s)| \displaystyle\leq CM2b4e2(Δ+2)s2ϵ2μ(s)\displaystyle C\,M^{2}\,b^{4}\,e^{2(\Delta+2)s^{2}}\epsilon^{2\mu(s)} (4.32)
\displaystyle\leq CM2b4e2μ(s)|lnϵ|+2(Δ+2)s2\displaystyle C\,M^{2}\,b^{4}\,e^{-2\mu(s)|\ln\epsilon|+2(\Delta+2)s^{2}} (4.33)
\displaystyle\leq CM2b4e(2|lnϵ|π(bs)2+2(Δ+2)s2)\displaystyle C\,M^{2}\,b^{4}\,e^{-\big{(}\frac{-2|\ln\epsilon|}{\pi}(\frac{b}{s})^{2}+2(\Delta+2)s^{2}\big{)}} (4.34)
\displaystyle\leq CM2b4e2(2(Δ+2)π)12b|lnϵ|35(112|lnϵ|15).\displaystyle C\,M^{2}\,b^{4}\,e^{-2(\frac{2(\Delta+2)}{\pi})^{\frac{1}{2}}b|\ln\epsilon|^{\frac{3}{5}}(1-\frac{1}{2}|\ln\epsilon|^{-\frac{1}{5}})}. (4.35)

Noting that 12|lnϵ|α<12\frac{1}{2}|\ln\epsilon|^{-\alpha}<\frac{1}{2} and (2(Δ+2)π)12>1(\frac{2(\Delta+2)}{\pi})^{\frac{1}{2}}>1, we have

|I(s)|CM2b4eb|lnϵ|35.|I(s)|\leq C\,M^{2}\,b^{4}\,e^{-b|\ln\epsilon|^{\frac{3}{5}}}.

Using the elementary inequality

et5!t5,t>0,e^{-t}\leq\frac{5!}{t^{5}},\quad t>0,

we get

|I(s)|Cb4M2b5|lnϵ|3CM2b|lnϵ|3.|I(s)|\leq C\frac{b^{4}M^{2}}{b^{5}|\ln\epsilon|^{3}}\leq C\frac{M^{2}}{b|\ln\epsilon|^{3}}.

Case (ii): |lnϵ|15214b12(2(Δ+2)π)14|\ln\epsilon|^{\frac{1}{5}}\leq 2^{\frac{1}{4}}b^{\frac{1}{2}}(2(\Delta+2)\pi)^{\frac{1}{4}}. In this case we have for s=bs=b that

|I(s)|=|I(b)|b11ϵ2.|I(s)|=|I(b)|\leq b^{11}\,\epsilon^{2}.

Combining estimates of I1(s)I_{1}(s) and I2(s)I_{2}(s) , we obtain

Es|pF^|2𝑑ξp𝑑ω+Es1|pF^|2𝑑ξp𝑑ω+Es2|pF^|2𝑑ξp𝑑ω\displaystyle\int_{E_{s}}|\textbf{p}\cdot\widehat{\textbf{F}}|^{2}d\xi_{p}\,d\omega+\int_{E^{1}_{s}}|\textbf{p}\cdot\widehat{\textbf{F}}|^{2}d\xi_{p}\,d\omega+\int_{E^{2}_{s}}|\textbf{p}\cdot\widehat{\textbf{F}}|^{2}d\xi_{p}\,d\omega =\displaystyle= I(s)+I1(s)+I2(s)\displaystyle I(s)+I_{1}(s)+I_{2}(s) (4.36)
\displaystyle\leq C(b11ϵ2+M2b|lnϵ|3+M2b12|lnϵ|15)\displaystyle C\Big{(}b^{11}\epsilon^{2}+\frac{M^{2}}{b|\ln\epsilon|^{3}}+\frac{M^{2}}{b^{\frac{1}{2}}|\ln\epsilon|^{\frac{1}{5}}}\Big{)} (4.37)
\displaystyle\leq C(b11ϵ2+M2b12|lnϵ|15)\displaystyle C\Big{(}b^{11}\epsilon^{2}+\frac{M^{2}}{b^{\frac{1}{2}}|\ln\epsilon|^{\frac{1}{5}}}\Big{)} (4.38)

Since (b|lnϵ|3)>(b|lnϵ|15)\big{(}b|\ln\epsilon|^{3}\big{)}>\big{(}b|\ln\epsilon|^{\frac{1}{5}}\big{)} when b>1b>1 and |lnϵ|>1|\ln\epsilon|>1.

Repeating similar steps, we get

Es|qF^|2𝑑ξp𝑑ω+Es1|qF^|2𝑑ξp𝑑ω+Es2|qF^|2𝑑ξp𝑑ωC(b11ϵ2+M2b12|lnϵ|15).\int_{E_{s}}|\textbf{q}\cdot\widehat{\textbf{F}}|^{2}d\xi_{p}\,d\omega+\int_{E^{1}_{s}}|\textbf{q}\cdot\widehat{\textbf{F}}|^{2}d\xi_{p}\,d\omega+\int_{E^{2}_{s}}|\textbf{q}\cdot\widehat{\textbf{F}}|^{2}d\xi_{p}\,d\omega\leq C\Big{(}b^{11}\epsilon^{2}+\frac{M^{2}}{b^{\frac{1}{2}}|\ln\epsilon|^{\frac{1}{5}}}\Big{)}. (4.39)

On the other hand, since F=0\nabla\cdot\textbf{F}=0, we have that

iκpdF^(κpd,ω)=4ei(κpxd+ωt)F(x,t)𝑑x𝑑t=0TBRei(κpxd+ωt)F(x,t)𝑑x𝑑t=0-i\kappa_{p}\textbf{d}\cdot\widehat{\textbf{F}}(\kappa_{p}\textbf{d},\omega)=\int_{{\mathbb{R}}^{4}}\nabla e^{-i(\kappa_{p}\textbf{x}\cdot\textbf{d}+\omega t)}\cdot\textbf{F}(\textbf{x},t)d\textbf{x}dt=\int_{0}^{T}\int_{B_{R}}e^{-i(\kappa_{p}\textbf{x}\cdot\textbf{d}+\omega t)}\nabla\cdot\textbf{F}(\textbf{x},t)d\textbf{x}dt=0

Using the Pythagorean theorem yields

|F^(ξp,ω)|2=|pF^(ξp,ω)|2+|qF^(ξp,ω)|2+|dF^(ξp,ω)|2.|\widehat{\textbf{F}}(\xi_{p},\omega)|^{2}=|\textbf{p}\cdot\widehat{\textbf{F}}(\xi_{p},\omega)|^{2}+|\textbf{q}\cdot\widehat{\textbf{F}}(\xi_{p},\omega)|^{2}+|\textbf{d}\cdot\widehat{\textbf{F}}(\xi_{p},\omega)|^{2}.

According to 4=EsEs1Es2{\mathbb{R}}^{4}=E_{s}\cup E^{1}_{s}\cup E^{2}_{s}, we get

FL2(4)32=F^L2(4)32=Es|pF^|2𝑑ξp𝑑ω+Es1|pF^|2𝑑ξp𝑑ω+Es2|pF^|2𝑑ξp𝑑ω+Es|qF^|2𝑑ξp𝑑ω+Es1|qF^|2𝑑ξp𝑑ω+Es2|qF^|2𝑑ξp𝑑ω.\begin{split}||\textbf{F}||^{2}_{L^{2}({\mathbb{R}}^{4})^{3}}=||\widehat{\textbf{F}}||^{2}_{L^{2}({\mathbb{R}}^{4})^{3}}&=\int_{E_{s}}|\textbf{p}\cdot\widehat{\textbf{F}}|^{2}d\xi_{p}\,d\omega+\int_{E^{1}_{s}}|\textbf{p}\cdot\widehat{\textbf{F}}|^{2}d\xi_{p}\,d\omega+\int_{E^{2}_{s}}|\textbf{p}\cdot\widehat{\textbf{F}}|^{2}d\xi_{p}\,d\omega\\ &+\int_{E_{s}}|\textbf{q}\cdot\widehat{\textbf{F}}|^{2}d\xi_{p}\,d\omega+\int_{E^{1}_{s}}|\textbf{q}\cdot\widehat{\textbf{F}}|^{2}d\xi_{p}\,d\omega+\int_{E^{2}_{s}}|\textbf{q}\cdot\widehat{\textbf{F}}|^{2}d\xi_{p}\,d\omega.\end{split} (4.40)

Combining the above estimates (4.36)-(4.40), we obtain the stability estimate (2.7). This completes the proof.

5 Proof of Theorem 2.4

In this section, we assume that F takes the form

F(x1,x2,x3,t)=f(x~,t)g(x3),x~=(x1,x2)2,x3,t(0,T0).\textbf{F}(x_{1},x_{2},x_{3},t)=\textbf{f}(\tilde{x},t)g(x_{3}),\quad\tilde{x}=(x_{1},x_{2})\in{\mathbb{R}}^{2},\ x_{3}\in{\mathbb{R}},\quad t\in(0,T_{0}). (5.41)

Then the equation (1.2)(\ref{eq1}) becomes

nt2E+×(×E)=f(x~,t)g(x3).n\partial_{t}^{2}\textbf{E}+\nabla\times(\nabla\times\textbf{E})=\textbf{f}(\tilde{x},t)\,g(x_{3}). (5.42)

Assume that gg is known, we establish an increasing stability estimate about f from the Dirichlet data {E(x,t)|xBR,t(0,T0)}\{\textbf{E}(\textbf{x},t)|\ \textbf{x}\in\partial B_{R},\ t\in(0,T_{0})\}.

Multiplying the both sides of (5.42) by Einc\textbf{E}^{inc}, we obtain

0TBR(nt2E+×(×E)Eincdxdt=0TBRf(x~,t)g(x3)Einc(x,t)dxdt.\int_{0}^{T}\int_{B_{R}}(n\partial_{t}^{2}\textbf{E}+\nabla\times(\nabla\times\textbf{E})\textbf{E}^{inc}\ \mathrm{d}\textbf{x}\mathrm{d}t=\int_{0}^{T}\int_{B_{R}}\textbf{f}(\tilde{x},t)\,g(x_{3})\textbf{E}^{inc}(\textbf{x},t)\ \mathrm{d}\textbf{x}\mathrm{d}t. (5.43)

Integrating by parts, one deduces from the left hand side of (5.43) that

0TBR\displaystyle\int_{0}^{T}\int_{B_{R}} (nt2E+×(×E)Eincdxdt\displaystyle(n\partial_{t}^{2}\textbf{E}+\nabla\times(\nabla\times\textbf{E})\textbf{E}^{inc}\ \mathrm{d}\textbf{x}\mathrm{d}t
=\displaystyle= BRn(tE(x,t)Einc(x,t)E(x,t)tEinc(x,t))|0Tdx\displaystyle\int_{B_{R}}n(\partial_{t}\textbf{E}(\textbf{x},t)\textbf{E}^{inc}(\textbf{x},t)-\textbf{E}(\textbf{x},t)\partial_{t}\textbf{E}^{inc}(\textbf{x},t))\big{|}_{0}^{T}\;\mathrm{d}\textbf{x}
+0TBR(ν×(×E)Eincν×(×Einc)E)𝑑s(x)𝑑t.\displaystyle\quad+\int_{0}^{T}\int_{\partial B_{R}}\big{(}\nu\times(\nabla\times\textbf{E})\cdot\textbf{E}^{inc}-\nu\times(\nabla\times\textbf{E}^{inc})\cdot E\big{)}ds(\textbf{x})dt.
=\displaystyle= 0TBR((T(E×ν)Einc)+(E×ν)(×Einc))𝑑s(x)𝑑t.\displaystyle-\int_{0}^{T}\int_{\partial B_{R}}\big{(}(T(\textbf{E}\times\nu)\cdot\textbf{E}^{inc})+(\textbf{E}\times\nu)\cdot(\nabla\times\textbf{E}^{inc})\big{)}ds(\textbf{x})dt.

Note that, in the last step we have used the fact that E(x,t)=0\textbf{E}(\textbf{x},t)=0 when |x|<R|\textbf{x}|<R and t>T0+2Rt>T_{0}+2R, which follows straightforwardly from Huygens’ principle (see e.g., [18, Lemma 2.1]). This implies E(x,T)=tE(x,T)=0\textbf{E}(\textbf{x},T)=\partial_{t}\textbf{E}(\textbf{x},T)=0 for xBR\textbf{x}\in B_{R} and T>T0+2RT>T_{0}+2R. Hence, the integral over BRB_{R} on the left hand side of the previous identity vanishes. Thus (5.43) becomes

BRpei(κpd1x1+κpd2x2+ωt)f(x1,x2,t)dx~0Tg(x3)eiξ3x3𝑑t=0TBR((T(E×ν)Einc)+(E×ν)(×Einc))𝑑s(x)𝑑t\begin{split}\int_{B_{R}}\textbf{p}e^{-i(\kappa_{p}d_{1}x_{1}+\kappa_{p}d_{2}x_{2}+\omega t)}\cdot&\textbf{f}(x_{1},x_{2},t)d\tilde{x}\int_{0}^{T}g(x_{3})e^{-i\xi_{3}x_{3}}dt\\ &=-\int_{0}^{T}\int_{\partial B_{R}}\big{(}(T(\textbf{E}\times\nu)\cdot\textbf{E}^{inc})+(\textbf{E}\times\nu)\cdot(\nabla\times\textbf{E}^{inc})\big{)}ds(\textbf{x})dt\end{split} (5.44)

Let ξ~2=ξ12+ξ22\tilde{\xi}^{2}=\xi_{1}^{2}+\xi_{2}^{2}. Define the set (see Figure 2)

Es={(ξ1,ξ2,ω)3|nω2|ξ1|2|ξ2|2=|ξ3|2,|ω|sn,|ξ3|s}.E_{s}=\{(\xi_{1},\xi_{2},\omega)\in{\mathbb{R}}^{3}|\ n\omega^{2}-|\xi_{1}|^{2}-|\xi_{2}|^{2}=|\xi_{3}|^{2},\ |\omega|\leq\frac{s}{\sqrt{n}},\ |\xi_{3}|\leq s\}.
Refer to caption
Figure 2: EsE_{s} is the shadow area, ξ~2=ξ12+ξ22\tilde{\xi}^{2}=\xi_{1}^{2}+\xi_{2}^{2}.

Let ξp=ξ=κpd=(κpd1,κpd2,κpd3)\xi_{p}=\xi=\kappa_{p}\textbf{d}=(\kappa_{p}d_{1},\kappa_{p}d_{2},\kappa_{p}d_{3}). Combining (5.44) and |g^(ξ3)|δ>0|\widehat{g}(\xi_{3})|\geq\delta>0 for ξ3(b,b)\xi_{3}\in(-b,b), we get that for (κpd1,κpd2,ω)Eb(\kappa_{p}d_{1},\kappa_{p}d_{2},\omega)\in E_{b}

|pf^(κpd1,κpd2,ω)|C(1+κp)ϵ|g^(ξ3)|Cδ1(1+κp)ϵCbϵ.\begin{split}|\textbf{p}\cdot\widehat{\textbf{f}}(\kappa_{p}d_{1},\kappa_{p}d_{2},\omega)|\leq C\frac{(1+\kappa_{p})\epsilon}{|\hat{g}(\xi_{3})|}&\leq C\delta^{-1}(1+\kappa_{p})\epsilon\\ &\leq\,C\,b\epsilon.\end{split} (5.45)

Given

I(s)=Es|pf^(ξ1,ξ2,ω)|2𝑑ξ1𝑑ξ2𝑑ω,I(s)=\int_{E_{s}}|\textbf{p}\cdot\widehat{\textbf{f}}(\xi_{1},\xi_{2},\omega)|^{2}d\xi_{1}d\xi_{2}d\omega,

it is easy to verify that

I(s)Es|f^(ξ1,ξ2,ω)|2𝑑ξ1𝑑ξ2𝑑ω.I(s)\leq\int_{E_{s}}|\widehat{\textbf{f}}(\xi_{1},\xi_{2},\omega)|^{2}d\xi_{1}d\xi_{2}d\omega. (5.46)

Using the polar coordinates ξ1=rsinθ\xi_{1}=r\sin\theta, ξ2=rcosθ\xi_{2}=r\cos\theta for 0rs0\leq r\leq s, 0θ2π0\leq\theta\leq 2\pi, we obtain that

Es{(ξ1,ξ2,ω)|ω0}|f^|2𝑑ξ1𝑑ξ2𝑑ω=0s02π1nr1ns|f^|2r𝑑ω𝑑r𝑑θ.\begin{split}\int_{E_{s}\cap\{(\xi_{1},\xi_{2},\omega)|\ \omega\geq 0\}}|\widehat{\textbf{f}}|^{2}d\xi_{1}d\xi_{2}d\omega=\int_{0}^{s}\int_{0}^{2\pi}\int_{\frac{1}{\sqrt{n}}r}^{\frac{1}{\sqrt{n}}s}|\widehat{\textbf{f}}|^{2}r\,d\omega\,dr\,d\theta.\end{split}

Let r=sr^r=s\hat{r}, rξ^=(ξ1,ξ2)r\hat{\xi}=(\xi_{1},\xi_{2}) and ω^(0,1)\hat{\omega}\in(0,1). A simple calculation yields

Es{(ξ1,ξ2,ω)|ω0}|f^(ξ1,ξ2,ω)|2𝑑ξ1𝑑ξ2𝑑ω=0s02π1nr1ns|f^(ξ1,ξ2,ω)|2𝑑ωr𝑑r𝑑θ=0102π(1nsr^1ns|f^(rξ^,ω)|2𝑑ω)s2r^𝑑r^𝑑θ=0102π(01ns|f^(sr^ξ^,ω)|2𝑑ω01nsr^|f^(sr^ξ^,ω)|2𝑑ω)s2r^𝑑r^𝑑θ=0102π(01|f1(sr^ξ^,1nsω^)|21ns3r^𝑑ω^01|f2(sr^ξ^,1nsr^ω^)|21ns3r^2𝑑ω^)𝑑r^𝑑θ\begin{split}&\int_{E_{s}\cap\{(\xi_{1},\xi_{2},\omega)|\ \omega\geq 0\}}|\widehat{\textbf{f}}(\xi_{1},\xi_{2},\omega)|^{2}d\xi_{1}d\xi_{2}d\omega\\ &=\int_{0}^{s}\int_{0}^{2\pi}\int_{\frac{1}{\sqrt{n}}r}^{\frac{1}{\sqrt{n}}s}|\widehat{\textbf{f}}(\xi_{1},\xi_{2},\omega)|^{2}d\omega rdrd\theta\\ &=\int_{0}^{1}\int_{0}^{2\pi}\big{(}\int_{\frac{1}{\sqrt{n}}s\hat{r}}^{\frac{1}{\sqrt{n}}s}|\widehat{\textbf{f}}(r\hat{\xi},\omega)|^{2}d\omega\big{)}s^{2}\hat{r}d\hat{r}d\theta\\ &=\int_{0}^{1}\int_{0}^{2\pi}\big{(}\int_{0}^{\frac{1}{\sqrt{n}}s}|\widehat{\textbf{f}}(s\hat{r}\hat{\xi},\omega)|^{2}d\omega-\int_{0}^{\frac{1}{\sqrt{n}}s\hat{r}}|\widehat{\textbf{f}}(s\hat{r}\hat{\xi},\omega)|^{2}d\omega\big{)}s^{2}\hat{r}d\hat{r}d\theta\\ &=\int_{0}^{1}\int_{0}^{2\pi}\big{(}\int_{0}^{1}|\textbf{f}_{1}(s\hat{r}\hat{\xi},\frac{1}{\sqrt{n}}s\hat{\omega})|^{2}\frac{1}{\sqrt{n}}s^{3}\hat{r}d\hat{\omega}-\int_{0}^{1}|\textbf{f}_{2}(s\hat{r}\hat{\xi},\frac{1}{\sqrt{n}}s\hat{r}\hat{\omega})|^{2}\frac{1}{\sqrt{n}}s^{3}\hat{r}^{2}d\hat{\omega}\big{)}d\hat{r}d\theta\end{split}

where

f1(sr^ξ^,1nsω^)=3f(x1,x2,t)ei(sr^ξ^x~+1nsω^t)𝑑x~𝑑t\textbf{f}_{1}(s\hat{r}\hat{\xi},\frac{1}{\sqrt{n}}s\hat{\omega})=\int_{{\mathbb{R}}^{3}}\textbf{f}(x_{1},x_{2},t)e^{-i(s\hat{r}\hat{\xi}\cdot\tilde{x}+\frac{1}{\sqrt{n}}s\hat{\omega}t)}d\tilde{x}dt

and

f2(sr^ξ^,1nsr^ω^)=3pf(x1,x2,t)ei(sr^ξ^x~+1nsr^ω^t)𝑑x~𝑑t.\textbf{f}_{2}(s\hat{r}\hat{\xi},\frac{1}{\sqrt{n}}s\hat{r}\hat{\omega})=\int_{{\mathbb{R}}^{3}}\textbf{p}\cdot\textbf{f}(x_{1},x_{2},t)e^{-i(s\hat{r}\hat{\xi}\cdot\tilde{x}+\frac{1}{\sqrt{n}}s\hat{r}\hat{\omega}t)}d\tilde{x}dt.

This integral is an analytic function of s=s1+is2s=s_{1}+is_{2}\in{\mathbb{C}}, s1,s2s_{1},s_{2}\in{\mathbb{R}}. Noting that |i(sr^ξ^x~+1nsω^t|(R+1nT)|s2||-i(s\hat{r}\hat{\xi}\cdot\tilde{x}+\frac{1}{\sqrt{n}}s\hat{\omega}t|\leq(R+\frac{1}{\sqrt{n}}T)|s_{2}| and |i(sr^ξ^x~+1nsr^ω^t)|(R+1nT)|s2||-i(s\hat{r}\hat{\xi}\cdot\tilde{x}+\frac{1}{\sqrt{n}}s\hat{r}\hat{\omega}t)|\leq(R+\frac{1}{\sqrt{n}}T)|s_{2}|, we deduce

|I(s)|CM2|s|3e((R+cT)+1)|s2|,sS\begin{split}|I(s)|\leq CM^{2}|s|^{3}e^{((R+cT)+1)|s_{2}|},\ s\in S\end{split}

where c:=1nc:=\frac{1}{\sqrt{n}} and C>0C>0 depends on nn, T0T_{0} and RR.

From estimate (5.45), we have

|I(s)|C|Es|b2ϵ2for alls[0,b],\begin{split}|I(s)|\leq C\,|E_{s}|\,b^{2}\,\epsilon^{2}\quad\mbox{for all}\quad s\in[0,b],\end{split} (5.47)

where C>0C>0 depends on nn, δ\delta, T0T_{0} and RR. Then applying Lemma 3.2, we know for all s>bs>b that

|I(s)|CM2b2e((R+cT)+1)sϵ2μ(s),\begin{split}|I(s)|\leq CM^{2}\,b^{2}\,e^{((R+cT)+1)s}\epsilon^{2\mu(s)},\end{split}

where C>0C>0 depends on nn, δ\delta, T0T_{0} and RR.

Define Es1={(ξ1,ξ2,ω)3||ω|>1ns,ξ12+ξ22nω2}E_{s}^{1}=\{(\xi_{1},\xi_{2},\omega)\in{\mathbb{R}}^{3}|\,|\omega|>\frac{1}{\sqrt{n}}s,\ \xi_{1}^{2}+\xi_{2}^{2}\leq n\omega^{2}\}. The Parseval’s identity yields

I1(s)=Es1|pf^(ξ1,ξ2,ω)|2𝑑ξ1𝑑ξ2𝑑ωCs2Es1|(pf)^(ξ1,ξ2,ω)|2𝑑ξ1𝑑ξ2𝑑ωCM2s2,I_{1}(s)=\int_{E^{1}_{s}}|\textbf{p}\cdot\widehat{\textbf{f}}(\xi_{1},\xi_{2},\omega)|^{2}d\xi_{1}d\xi_{2}d\omega\leq\frac{C}{s^{2}}\int_{E^{1}_{s}}|\widehat{\nabla(\textbf{p}\cdot\textbf{f})}(\xi_{1},\xi_{2},\omega)|^{2}d\xi_{1}d\xi_{2}d\omega\leq\,C\,\frac{M^{2}}{s^{2}},

where C>0C>0 depends on nn. Consider the set

Es2={(ξ1,ξ2,ω)3|ω2+ξ12+ξ221ns2,ξ12+ξ22nω2}.E^{2}_{s}=\{(\xi_{1},\xi_{2},\omega)\in{\mathbb{R}}^{3}|\,\omega^{2}+\xi_{1}^{2}+\xi_{2}^{2}\leq\frac{1}{n}s^{2},\ \xi_{1}^{2}+\xi_{2}^{2}\geq n\omega^{2}\}.

Now we estimate

I2(s)=Es2|pf^(ξ1,ξ2,ω)|2𝑑ξ1𝑑ξ2𝑑ω.I_{2}(s)=\int_{E^{2}_{s}}|\textbf{p}\cdot\widehat{\textbf{f}}(\xi_{1},\xi_{2},\omega)|^{2}d\xi_{1}d\xi_{2}d\omega.

The following Lemma 5.1 is essential to estimate I2(s)I_{2}(s). For r>0r>0, denote B(0,r)={xd:|x|<r}B(0,r)=\{x\in{\mathbb{R}}^{d}:|x|<r\}. Below we state a stability estimate for analytic continuation problems, which can be seen in [8, 33].

Lemma 5.1.

Let 𝒪\mathcal{O} be a non empty open set of the unit ball B(0,1)dB(0,1)\subset\mathbb{R}^{d}, d2d\geq 2, and let GG be an analytic function in B(0,2),B(0,2), that satisfy

γGL(B(0,2))M0|γ|!η|γ|,γ({0})d,\|\partial^{\gamma}G\|_{L^{\infty}(B(0,2))}\leq M_{0}\,|\gamma|!\;{\eta^{-|\gamma|}},\,\,\,\,\forall\,\gamma\in(\mathbb{N}\cup\{0\})^{d},

for some M0>0M_{0}>0 and η>0\eta>0. Then, we have

GL(B(0,1))NM01μGL(𝒪)μ,\|G\|_{L^{\infty}(B(0,1))}\leq N\,M_{0}^{1-\mu}\;\|G\|_{L^{\infty}(\mathcal{O})}^{\mu},

where μ(0,1)\mu\in(0,1) depends on dd, η\eta and |𝒪||\mathcal{O}| and N=N(η)>0N=N(\eta)>0.

Define Fs(ξ1,ξ2,ω)=pf^(sξ1,sξ2,sω)F_{s}(\xi_{1},\xi_{2},\omega)=\textbf{p}\cdot\widehat{\textbf{f}}(s\xi_{1},s\xi_{2},s\omega) for any (ξ1,ξ2,ω)3(\xi_{1},\xi_{2},\omega)\in\mathbb{R}^{3} and s>0s>0. Since f is compactly supported, one can see that the function FsF_{s} is analytic and it satisfies for γ({0})3\gamma\in({\mathbb{N}}\cup\{0\})^{3} that

|γFs(ξ1,ξ2,ω)|=|γF(sξ1,sξ2,sω)|=|γ3pf(x1,x2,t)eis(ξ1x1+ξ2x2+ωt)𝑑x1𝑑x2𝑑t|\displaystyle|\partial^{\gamma}F_{s}(\xi_{1},\xi_{2},\omega)|=|\partial^{\gamma}F(s\xi_{1},s\xi_{2},s\omega)|=\Big{|}\partial^{\gamma}\int_{\mathbb{R}^{3}}\textbf{p}\cdot\textbf{f}(x_{1},x_{2},t)e^{-is(\xi_{1}\cdot x_{1}+\xi_{2}\cdot x_{2}+\omega t)}\,dx_{1}dx_{2}dt\Big{|}
=|α+β=γα,β03(i)|γ|s|γ|x~αtβpf(x1,x2,t)eib(ξ1x1+ξ2x2+ωt)𝑑x1𝑑x2𝑑t|.\displaystyle=\Big{|}\sum_{\alpha+\beta=\gamma\atop\alpha,\beta\in{\mathbb{N}}\cup 0}\int_{\mathbb{R}^{3}}(-i)^{|\gamma|}s^{|\gamma|}\tilde{x}^{\alpha}t^{\beta}\textbf{p}\cdot\textbf{f}(x_{1},x_{2},t)e^{-ib(\xi_{1}\cdot x_{1}+\xi_{2}\cdot x_{2}+\omega t)}\,dx_{1}dx_{2}dt\Big{|}.

Using s|γ|<|γ|!ess^{|\gamma|}<|\gamma|!\,e^{s} and η=max{R,T}1\eta=\max\{R,T\}^{-1}, we obtain

|γFs(ξ1,ξ2,ω)|fL2(BR×(0,T))η|γ|s|γ|CfL2(BR×(0,T))η|γ||γ|!esCMη|γ||γ|!es,\displaystyle|\partial^{\gamma}F_{s}(\xi_{1},\xi_{2},\omega)|\leq\|\textbf{f}\|_{L^{2}(B_{R}\times(0,T))}\,\eta^{-|\gamma|}\,s^{|\gamma|}\leq C\|\textbf{f}\|_{L^{2}(B_{R}\times(0,T))}\,\eta^{-|\gamma|}\,|\gamma|!\,e^{s}\leq CM\,\eta^{-|\gamma|}\,|\gamma|!\,e^{s},

where C>0C>0 depends on RR and TT. Applying Lemma 5.1 to the set 𝒪\mathcal{O} defined as 𝒪:=Es2\mathcal{O}:=E_{s}^{2}, we find a constant α(0,1)\alpha\in(0,1) such that

FsL(B(0,1))CMes(1α)FsL(𝒪)α.\|F_{s}\|_{L^{\infty}(B(0,1))}\leq C\,M\,e^{s(1-\alpha)}\|F_{s}\|^{\alpha}_{L^{\infty}(\mathcal{O})}.

Using the fact that pf^(ξ)=Fs(s1ξ)\textbf{p}\cdot\widehat{\textbf{f}}(\xi)=F_{s}(s^{-1}\xi), one gets the following estimate

pf^L(B(0,s))\displaystyle\|\textbf{p}\cdot\widehat{\textbf{f}}\|_{L^{\infty}(B(0,s))} =\displaystyle= FsL(B(0,1))CMes(1α)FsL(𝒪)α\displaystyle\|F_{s}\|_{L^{\infty}(B(0,1))}\leq CMe^{s(1-\alpha)}\|F_{s}\|_{L^{\infty}(\mathcal{O})}^{\alpha} (5.48)
\displaystyle\leq CMes(1α)pf^L(Es2)αCMes(1α)bαϵα,\displaystyle C\,M\,e^{s(1-\alpha)}\|\textbf{p}\cdot\widehat{\textbf{f}}\|_{L^{\infty}(E_{s}^{2})}^{\alpha}\leq C\,M\,e^{s(1-\alpha)}b^{\alpha}\epsilon^{\alpha},

where C>0C>0 depends on RR, TT, δ\delta and nn. Combining (5.45), we know for s[0,b]s\in[0,b] that

|I2(s)|CM2|Es2|e2s(1α)b2αϵ2α|I_{2}(s)|\leq CM^{2}|E^{2}_{s}|\,e^{2s(1-\alpha)}\,b^{2\alpha}\,\epsilon^{2\alpha}

and similarly

|I2(s)|CM2|s|3e((R+cT)+1)|s2|for allsS.\begin{split}|I_{2}(s)|\leq CM^{2}|s|^{3}\,e^{\big{(}(R+cT)+1\big{)}|s_{2}|}\quad\mbox{for all}\quad s\in S.\end{split}

Thus applying Lemma 3.2, we have

|e((R+cT)+3)sI2(s)|CM2b2α(ϵα)2μfor alls>b,\begin{split}|e^{-((R+cT)+3)s}I_{2}(s)|\leq CM^{2}b^{2\alpha}(\epsilon^{\alpha})^{2\mu}\quad\mbox{for all}\quad s>b,\end{split} (5.49)

where C>0C>0 depends on RR, TT, δ\delta and nn.

Consider the set

Es3={(ξ1,ξ2,ω)3|ω2+|ξ1|2+|ξ2|2>1ns2,ξ12+ξ22nω2}.E^{3}_{s}=\{(\xi_{1},\xi_{2},\omega)\in{\mathbb{R}}^{3}|\,\ \omega^{2}+|\xi_{1}|^{2}+|\xi_{2}|^{2}>\frac{1}{n}s^{2},\ \xi_{1}^{2}+\xi_{2}^{2}\geq n\omega^{2}\}.

The Parseval’s identity implies

I3(s)=Es3|pf^(ξ1,ξ2,ω)|2𝑑ξ1𝑑ξ2𝑑ωCM2s2,I_{3}(s)=\int_{E^{3}_{s}}|\textbf{p}\cdot\widehat{\textbf{f}}(\xi_{1},\xi_{2},\omega)|^{2}d\xi_{1}d\xi_{2}d\omega\leq\frac{CM^{2}}{s^{2}}, (5.50)

where C>0C>0 depends on nn.

Now we proof Theorem 2.4. We assume that ϵ<e1\epsilon<e^{-1}, otherwise the estimate is obvious. Let

s={1(((R+cT)+3)π)13b23|lnϵ|14if|lnϵ|14>214b13(((R+cT)+3)π)13,bif|lnϵ|14>214b13(((R+cT)+3)π)13.\displaystyle s=\begin{cases}\frac{1}{(((R+cT)+3)\pi)^{\frac{1}{3}}}b^{\frac{2}{3}}|\ln\epsilon|^{\frac{1}{4}}&\textrm{if}\ |\ln\epsilon|^{\frac{1}{4}}>2^{\frac{1}{4}}b^{\frac{1}{3}}(((R+cT)+3)\pi)^{\frac{1}{3}},\\ b&\textrm{if}\ |\ln\epsilon|^{\frac{1}{4}}>2^{\frac{1}{4}}b^{\frac{1}{3}}(((R+cT)+3)\pi)^{\frac{1}{3}}.\end{cases} (5.51)

Case (i): |lnϵ|14>214b13(((R+cT)+3)π)13|\ln\epsilon|^{\frac{1}{4}}>2^{\frac{1}{4}}b^{\frac{1}{3}}(((R+cT)+3)\pi)^{\frac{1}{3}}. One can check that

s>214b.s>2^{\frac{1}{4}}b.

Thus, using Lemma 3.2 we obtain

|I(s)|\displaystyle|I(s)| \displaystyle\leq CM2b2e((R+cT)+3)s2ϵ2μ(s)\displaystyle CM^{2}\,b^{2}e^{((R+cT)+3)s^{2}}\epsilon^{2\mu(s)} (5.52)
\displaystyle\leq CM2b2e2μ(s)|lnϵ|+((R+cT)+3)s2\displaystyle CM^{2}\,b^{2}\,e^{-2\mu(s)|\ln\epsilon|+((R+cT)+3)s^{2}} (5.53)
\displaystyle\leq CM2b2e2|lnϵ|π(bs)2+((R+cT)+3)(((R+cT)+3)π)13b23|lnϵ|14\displaystyle CM^{2}\,b^{2}\,e^{-\frac{-2|\ln\epsilon|}{\pi}(\frac{b}{s})^{2}+\frac{((R+cT)+3)}{(((R+cT)+3)\pi)^{\frac{1}{3}}}b^{\frac{2}{3}}|\ln\epsilon|^{\frac{1}{4}}} (5.54)
\displaystyle\leq CM2b2e2(((R+cT)+3)2π)13b23|lnϵ|12(112|lnϵ|14),\displaystyle CM^{2}\,b^{2}\,e^{-2\big{(}\frac{((R+cT)+3)^{2}}{\pi}\big{)}^{\frac{1}{3}}b^{\frac{2}{3}}|\ln\epsilon|^{\frac{1}{2}}\big{(}1-\frac{1}{2}|\ln\epsilon|^{-\frac{1}{4}}\big{)}}, (5.55)

where C>0C>0 depends on RR, TT, δ\delta and nn. Noting that 12|lnϵ|14<12\frac{1}{2}|\ln\epsilon|^{-\frac{1}{4}}<\frac{1}{2} and ((2(R+2T)+3)2π)13>1\big{(}\frac{(2(R+2T)+3)^{2}}{\pi}\big{)}^{\frac{1}{3}}>1, we have

|I(s)|CM2b2eb23|lnϵ|12.|I(s)|\leq CM^{2}\,b^{2}\,e^{-b^{\frac{2}{3}}|\ln\epsilon|^{\frac{1}{2}}}.

Using the elementary inequality

et6!t6,t>0,e^{-t}\leq\frac{6!}{t^{6}},\quad t>0,

we get

|I(s)|Cb2M2(b23|lnϵ|12)6CM2b2|lnϵ|3,|I(s)|\leq\frac{C\,b^{2}\,M^{2}}{\big{(}b^{\frac{2}{3}}|\ln\epsilon|^{\frac{1}{2}}\big{)}^{6}}\leq\frac{CM^{2}}{b^{2}|\ln\epsilon|^{3}}, (5.56)

where C>0C>0 depends on RR, TT, δ\delta and nn.

Case (ii): |lnϵ|14>214b13(((R+cT)+3)π)13|\ln\epsilon|^{\frac{1}{4}}>2^{\frac{1}{4}}b^{\frac{1}{3}}(((R+cT)+3)\pi)^{\frac{1}{3}}. In this case we have s=bs=b, and from (5.47),

|I(s)|=|I(b)||Eb|b2ϵ2.|I(s)|=|I(b)|\leq|E_{b}|b^{2}\epsilon^{2}.

Combining the estimates of I(s)I(s) and I1(s)I_{1}(s), we obtain

Es|pf^(ξ~,ω)|2𝑑ξ~𝑑ω\displaystyle\int_{E_{s}}|\textbf{p}\cdot\widehat{\textbf{f}}(\tilde{\xi},\omega)|^{2}\,d\tilde{\xi}\,d\omega +\displaystyle+ Es1|pf^(ξ~,ω)|2𝑑ξ~𝑑ω=I(s)+I1(s)\displaystyle\int_{E_{s}^{1}}|\textbf{p}\cdot\widehat{\textbf{f}}(\tilde{\xi},\omega)|^{2}\,d\tilde{\xi}\,d\omega=I(s)+I_{1}(s) (5.57)
\displaystyle\leq C(b5b2ϵ2++M2b2|lnϵ|3+M2(b23|lnϵ|14)2),\displaystyle C\Big{(}b^{5}\,b^{2}\epsilon^{2}++\frac{M^{2}}{b^{2}|\ln\epsilon|^{3}}+\frac{M^{2}}{\big{(}b^{\frac{2}{3}}|\ln\epsilon|^{\frac{1}{4}}\big{)}^{2}}\Big{)}, (5.58)

where C>0C>0 depends on RR, TT, δ\delta and nn.

Now we estimate I2(s)+I3(s)=Es2|pf^(ξ~,ω)|2𝑑ξ~𝑑ω+Es3|pf^(ξ~,ω)|2𝑑ξ~𝑑ωI_{2}(s)+I_{3}(s)=\int_{E_{s}^{2}}|\textbf{p}\cdot\widehat{\textbf{f}}(\tilde{\xi},\omega)|^{2}\,d\tilde{\xi}\,d\omega+\int_{E_{s}^{3}}|\textbf{p}\cdot\widehat{\textbf{f}}(\tilde{\xi},\omega)|^{2}\,d\tilde{\xi}\,d\omega. Let

s={1(((R+cT)+3)π)13b23|αlnϵ|14if|αlnϵ|14>214b13(((R+cT)+3)π)13,bif|αlnϵ|14>214b13(((R+cT)+3)π)13.\displaystyle s=\begin{cases}\frac{1}{(((R+cT)+3)\pi)^{\frac{1}{3}}}b^{\frac{2}{3}}|\alpha\ln\epsilon|^{\frac{1}{4}}&\textrm{if}\ |\alpha\ln\epsilon|^{\frac{1}{4}}>2^{\frac{1}{4}}b^{\frac{1}{3}}(((R+cT)+3)\pi)^{\frac{1}{3}},\\ b&\textrm{if}\ |\alpha\ln\epsilon|^{\frac{1}{4}}>2^{\frac{1}{4}}b^{\frac{1}{3}}(((R+cT)+3)\pi)^{\frac{1}{3}}.\end{cases}

Repeating similar steps, we find out

Es2|pf^(ξ~,ω)|2𝑑ξ~𝑑ω+Es3|pf^(ξ~,ω)|2𝑑ξ~𝑑ω=I2(s)+I3(s)\displaystyle\int_{E_{s}^{2}}|\textbf{p}\cdot\widehat{\textbf{f}}(\tilde{\xi},\omega)|^{2}\,d\tilde{\xi}\,d\omega+\int_{E_{s}^{3}}|\textbf{p}\cdot\widehat{\textbf{f}}(\tilde{\xi},\omega)|^{2}\,d\tilde{\xi}\,d\omega=I_{2}(s)+I_{3}(s)
C(b5e2b(1α)ϵ2α+M2b2|αlnϵ|3+M2(b23|αlnϵ|14)2),\displaystyle\leq C\Big{(}b^{5}\,e^{2b(1-\alpha)}\epsilon^{2\alpha}+\frac{M^{2}}{b^{2}|\alpha\ln\epsilon|^{3}}+\frac{M^{2}}{\big{(}b^{\frac{2}{3}}|\alpha\ln\epsilon|^{\frac{1}{4}}\big{)}^{2}}\Big{)}, (5.59)

where C>0C>0 depends on RR, TT, δ\delta, MM and nn.

Since b2|lnϵ|3>b43|lnϵ|12b^{2}|\ln\epsilon|^{3}>b^{\frac{4}{3}}|\ln\epsilon|^{\frac{1}{2}} and b2|αlnϵ|3>b43|αlnϵ|12b^{2}|\alpha\ln\epsilon|^{3}>b^{\frac{4}{3}}|\alpha\ln\epsilon|^{\frac{1}{2}} when b>1b>1 and |lnϵ|>1|\ln\epsilon|>1. Applying b43|lnϵ|12>b43|αlnϵ|12b^{\frac{4}{3}}|\ln\epsilon|^{\frac{1}{2}}>b^{\frac{4}{3}}|\alpha\ln\epsilon|^{\frac{1}{2}}, we obtain

3|pf^|2𝑑ξ~𝑑ω=Es|pf^|2𝑑ξ~𝑑ω+Es1|pf^|2𝑑ξ~𝑑ω+Es2|pf^|2𝑑ξ~𝑑ω+Es3|pf^|2𝑑ξ~𝑑ωC(b7ϵ2+b5e2b(1α)ϵ2α+M2b2|lnϵ|3+M2b43|lnϵ|12+M2b2|αlnϵ|3+M2b43|αlnϵ|12)C(b7ϵ2+b5e2b(1α)ϵ2α+M2b43|αlnϵ|12),\begin{split}\int_{{\mathbb{R}}^{3}}|\textbf{p}\cdot\widehat{\textbf{f}}|^{2}d\tilde{\xi}d\omega&=\int_{E_{s}}|\textbf{p}\cdot\widehat{\textbf{f}}|^{2}\,d\tilde{\xi}\,d\omega+\int_{E_{s}^{1}}|\textbf{p}\cdot\widehat{\textbf{f}}|^{2}\,d\tilde{\xi}\,d\omega+\int_{E_{s}^{2}}|\textbf{p}\cdot\widehat{\textbf{f}}|^{2}\,d\tilde{\xi}\,d\omega+\int_{E_{s}^{3}}|\textbf{p}\cdot\widehat{\textbf{f}}|^{2}\,d\tilde{\xi}\,d\omega\\ &\leq C\Big{(}b^{7}\epsilon^{2}+b^{5}e^{2b(1-\alpha)}\,\epsilon^{2\alpha}+\frac{M^{2}}{b^{2}|\ln\epsilon|^{3}}+\frac{M^{2}}{b^{\frac{4}{3}}|\ln\epsilon|^{\frac{1}{2}}}+\frac{M^{2}}{b^{2}|\alpha\ln\epsilon|^{3}}+\frac{M^{2}}{b^{\frac{4}{3}}|\alpha\ln\epsilon|^{\frac{1}{2}}}\Big{)}\\ &\leq C(b^{7}\epsilon^{2}+b^{5}e^{2b(1-\alpha)}\,\epsilon^{2\alpha}+\frac{M^{2}}{b^{\frac{4}{3}}|\alpha\ln\epsilon|^{\frac{1}{2}}}),\end{split} (5.60)

where C>0C>0 depends on RR, TT, δ\delta, MM and nn.

Repeating similar steps, we get that

3|qf^|2𝑑ξ~𝑑ωC(b7ϵ2+b5e2b(1α)ϵ2α+M2b43|αlnϵ|12),\int_{{\mathbb{R}}^{3}}|\textbf{q}\cdot\widehat{\textbf{f}}|^{2}d\tilde{\xi}d\omega\leq C(b^{7}\epsilon^{2}+b^{5}e^{2b(1-\alpha)}\,\epsilon^{2\alpha}+\frac{M^{2}}{b^{\frac{4}{3}}|\alpha\ln\epsilon|^{\frac{1}{2}}}), (5.61)

where C>0C>0 depends on RR, TT, δ\delta, MM and nn. Using the Pythagorean theorem yields

fL2(3)32=f^L2(3)32=3|pf^|2𝑑ξ~𝑑ω+3|qf^|2𝑑ξ~𝑑ω.\begin{split}||\textbf{f}||^{2}_{L^{2}({\mathbb{R}}^{3})^{3}}&=||\widehat{\textbf{f}}||^{2}_{L^{2}({\mathbb{R}}^{3})^{3}}\\ &=\int_{{\mathbb{R}}^{3}}|\textbf{p}\cdot\widehat{\textbf{f}}|^{2}d\tilde{\xi}d\omega+\int_{{\mathbb{R}}^{3}}|\textbf{q}\cdot\widehat{\textbf{f}}|^{2}d\tilde{\xi}d\omega.\end{split} (5.62)

Combining (5.60)-(5.61) and (5.62), we obtain the stability estimate (2.11). This completes the proof.

6 Acknowledgment

The work of S. Si is supported by the Natural Science Foundation of Shandong Province, China(No. ZR202111240173). The author would like to thank Guanghui Hu for helpful discussions.

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