This paper proves the nonlinear stability of line solitary waves in the 2D Benney-Luke equation, extending previous linear stability results and employing methods from KP-II soliton stability analysis.
Contribution
It establishes the nonlinear stability of line solitary waves in the 2D Benney-Luke equation, a significant advancement over prior linear stability results.
Findings
01
Nonlinear stability of line solitary waves proven.
02
Method adapted from KP-II soliton stability analysis.
03
Extends understanding of water wave models.
Abstract
The 2D Benney-Luke equation is an isotropic model which describes long water waves of small amplitude in 3D whereas the KP-II equation is a unidirectional model for long waves with slow variation in the transverse direction. In the case where the surface tension is weak or negligible, linearly stability of small line solitary waves of the 2D Benney-Luke equation was proved by Mizumachi and Shimabukuro [Nonlinearity, 30 (2017), 3419--3465]. In this paper, we prove nonlinear stability of the line solitary waves by adopting the argument by Mizumachi ([Mem. Amer. Math. Soc. no. 1125], [Proc. Roy. Soc. Edinburgh Sect. A., 148 (2018), 149--198] and [arXiv:1808.00809]) which prove nonlinear stability of 1-line solitons for the KP-II equation.
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The 2D Benney-Luke equation is an isotropic model
which describes long water waves of small amplitude in 3D whereas
the KP-II equation is a unidirectional model for long waves with
slow variation in the transverse direction.
In the case where the surface tension is weak or negligible,
linearly stability of small line solitary waves of the 2D Benney-Luke
equation was proved by Mizumachi and Shimabukuro [Nonlinearity, 30 (2017),
3419–3465]. In this paper, we prove nonlinear stability of the
line solitary waves by adopting the argument by Mizumachi
([Mem. Amer. Math. Soc. no. 1125],
[Proc. Roy. Soc. Edinburgh Sect. A., 148 (2018), 149–198] and
[https://arxiv.org/abs/1808.00809])
which prove nonlinear stability of 1-line solitons
for the KP-II equation.
Key words and phrases:
line solitary waves, transverse stability, long wave model
2010 Mathematics Subject Classification:
Primary 35B35, 37K45;
Secondary 35Q35
1. Introduction
In this paper, we study nonlinear transverse stability of line solitary waves
for the Benney-Luke equation
[TABLE]
The Benney-Luke equation is an approximation model of small amplitude
long water waves with finite depth originally derived by Benney and
Luke [3] as a model for 3D water waves and its mathematically
rigorous derivation from the water wave equation was given
by [15].
Here
ϕ=ϕ(t,x,y) corresponds to a velocity potential of water waves.
We remark that (1.1) is an isotropic model for the propagation of
water waves whereas KdV, BBM and KP equations are unidirectional
models. See e.g. [5, 6, 7] for the other bidirectional
models of 2D and 3D water waves. Since the Benney-Luke equation is isotropic
as the water wave equation, it could be more useful to describe nonlinear
interactions of waves at a high angle than the KP equations.
The parameters a, b are positive and satisfy a−b=τ^−1/3, where
τ^ is the inverse Bond number.
In this paper, we will assume 0<a<b, which corresponds to the case where
the surface tension is weak or negligible.
If we think of waves propagating in one direction, slowly evolving in
time and having weak transverse variation, then the Benney-Luke equation
can be formally reduced to the KP-II equation if 0<a<b and
to the KP-I equation if a>b>0.
More precisely, the Benney-Luke equation (1.1) is reduced to
[TABLE]
in the coordinate t~=ϵ3t, x~=ϵ(x−t) and
y~=ϵ2y by taking terms only of order ϵ5,
where ϕ(t,x,y)=ϵf(t~,x~,y~).
See e.g. [20] for the details.
On the other hand, the Benney-Luke equation (1.1) can realize the
finite time dynamics of the KP-II equation as in the case of 2-dimensional
Boussinesq equations (see [12] and [28]).
The solution ϕ(t) of the Benney-Luke equation (1.1) formally
satisfies the energy conservation law
[TABLE]
where
[TABLE]
and (1.1) is globally well-posed in the energy class
E:=(H˙2(R2)∩H˙1(R2))×H1(R2) (see
[33]). The Benney Luke equation (1.1) has a 3-parameter
family of line solitary wave solutions
[TABLE]
where
[TABLE]
and
[TABLE]
is a solution of
[TABLE]
Stability of solitary waves to the 1-dimensional Benney-Luke equation
was studied by [31] for the strong surface tension case a>b>0
by using the variational argument ([10, 13]) which was originated by
[2, 4] and by [25] for the weak surface tension case
b>a>0 by adopting the semigroup approach of [30].
If a>b>0, then (1.1) has a stable ground state for c
satisfying 0<c2<1 ([29, 32]).
Note that for the water wave equation with strong surface tension,
orbital stability of solitary waves conditional on global solvability
has been proved by Mielke [19] and Buffoni [8] by the variational argument.
See also [17] for the algebraic decay property of the ground state.
In view of [34, 35],
line solitary waves for the 2-dimensional Benney-Luke equation
are expected to be unstable in this parameter regime.
On the other hand if 0<a<b and c:=1+ϵ2 is close to 1
(the sonic speed), then φc(x−ct) is expected to be
transversally stable because qc(x) is similar to a KdV 1-soliton and
line solitons of the KP-II equation is transversally stable
([14, 22, 23, 27]).
The dispersion relation for the linearized equation of (1.1) around [math] is
[TABLE]
for a plane wave solution ϕ(t,x,y)=ei(xξ+yη−ωt).
If b>a>0, then ∣∇ω∣≤1,
∇ω(ξ,η)∥(ξ,η) and line solitary waves
travel faster than the maximum group velocity of linear waves. Using
this property and transverse linear stability of 1-line solitons for
the KP-II equation ([9, 22]), transverse linear
stability of small line solitary waves of (1.1) was proved by
[26]. The difference between the linear stability result
for solitary waves of the 1-dimensional Benney-Luke equation
([25, Lemma 2.1 and Theorems 2.2 and 2.3]) is that in the
1-dimensional case λ=0 is an isolated eigenvalue in
exponentially weighted spaces whereas λ=0 is not an isolated
eigenvalue of the linearized operator around line solitary waves
because line solitary waves do not decay in the transverse direction.
In [26], we investigate the spectrum of the linearized
operator in a weighted space L2(R2;e2αxdxdy) with α>0 and
find a curve of continuous spectrum
{λ∣±iλ1,c+λ2,cη2+O(η3),η∈[−η∗,η∗]}, where λ1,c, λ2,c,
η∗ are positive constants. We remark that the continuous
eigenmodes found in [26] grow exponentially as
x→−∞ and cannot be recognized as continuous eigenmodes in the
L2-framework. These resonant continuous eigenmodes have to do with
modulations of line solitary waves. Indeed, we find in
[26] that linear evolution of those resonant continuous
eigenmodes can be approximately described by solutions of
1-dimensional dissipative linear wave equation on the time variable
t and the transverse variable y and that it illustrates phase shifts of
modulating line solitary waves.
In this paper, we show that motion of the local amplitude c(t,y) and the local phase shift γ(t,y)
of a modulating line solitary wave φc(t,y)(x−γ(t,y)) is described by 1-dimensional a system of nonlinear dissipative
wave equations and prove nonlinear transverse stability of line solitary waves.
The nonlinear stability of line solitary waves in the entire domain has been proved only for the KP-II equation ([22, 23, 24])
and it is interesting to give its mathematical proof for non-integrable system such as the Benny-Luke equations.
Since the arguments in [22, 23, 24] are based on PDE methods and integrability of the KP-II equation is used only to prove linear stability of
line solitary waves, we are able to extend the arguments for the Benney-Luke equation.
Our plan of the present paper is as follows. In
Section 2.1, we recall the linear stability
property of line solitary waves in [26]
(Theorem 2.1) and introduce our main result
(Theorem 2.2) in Section 2.2. In
Section 3, we introduce L2−F−1L∞ estimates
of solutions for the linearized modulation equations as well as
a substitute of d’Alembert’s formula to prove the L∞-bound of the phase shifts of line solitary waves.
We also investigate the large time behavior of the solutions
to the linearized equation.
In Section 4, we decompose a solution around line
solitary waves into a sum of the modulating line solitary wave, a
small freely propagating solution of (1.1), exponentially
localized remainder part and an auxiliary function. We will impose
the secular term condition to the exponentially localized part to make
use of linear stability property of line solitary waves. We split
small solutions of (1.1) from solutions around line solitary
waves so that the remainder part is exponentially localized because as
in [23], resonant continuous eigenmodes of the adjoint
linearized operator grow exponentially as x→∞ and the secular
term condition makes sense only for exponentially localized
perturbations. Since φc(−∞) differs as c varies,
we need a correction term to keep the remainder terms in the energy class.
In Section 5,
we compute time derivative of the secular term condition
and derive a system of PDEs that describe the motion of the local amplitude
c(t,y) and the local phase shift γ(t,y) whose linearized
equation is
[TABLE]
The modulation equation derived from the secular term condition
has a critical nonlinear term whose L1(Ry)-norm decays like t−1
and a term coming from the freely propagating remainder part
whose L1(Ry)-norm is expected to grow as t→∞.
These terms are harmful to estimate modulation parameters c(t,y) and
γ(t,y).
As in [23, 24], we use a change of variables to transform these terms into harmless forms.
In Section 6, we prove decay estimates of the local amplitude
c(t,y) and the local orientation γy(t,y) of the modulating
line solitary wave φc(t,y)(x−c0t−γ(t,y)) by applying
linear estimates obtained in Section 3,
where c0 is the amplitude of the unperturbed line solitary wave.
In Section 7, we estimate a renormalized energy
of perturbations which we find by removing infinite energy parts
from solutions around line solitary wave and making use of the
orthogonality condition imposed on the exponentially localized part
in Section 4.2.
In Section 8, we prove virial identities for (1.1)
and prove decay estimates for localized energies of small solutions to
(1.1).
In Section 9, we estimate an exponentially localized norm
of perturbations by using linear stability property of line solitary waves
(Theorem 2.1).
If we linearize (1.1) around a modulating line solitary wave
and use the moving coordinate z=x−c0t−γ(t,y), we have
a space-time dependent advection term. Since (1.1)
is a 2-dimensional wave equation with dispersion in the low frequency regime,
the smoothing effect of (1.1) is not strong enough to treat
the advection term as a remainder part.
To avoid the appearance of the advection term,
we prove that ∥γ(t,⋅)∥L∞(Ry) remains small for polynomially localized perturbations
to line solitary waves by using an estimate similar to d’Alembert’s formula following the idea of [24].
In our paper, it remains open whether the phase shift γ(t,y)
can grow as t, y→±∞ for perturbations in the energy class.
See [18] for the growth of phase shifts of gKdV solitary waves.
In Section 10, we show that the large time behavior
of c(t,y) and γy(t,y) can be expressed by a linear combination
of self-similar solutions of the Burgers’ equation with spatial phase shift
±λ1,c0t and prove transverse stability of line solitary
waves for polynomially localized perturbations.
Finally, let us introduce several notations.
We denote by σ(T) the spectrum of the operator T.
For Banach spaces V and W, let B(V,W) be the space of all
linear continuous operators from V to W and
∥T∥B(V,W)=sup∥u∥V=1∥Tu∥W for A∈B(V,W).
We abbreviate B(V,V) as B(V).
For f∈S(Rn) and m∈S′(Rn), let
[TABLE]
and (m(D)f)(x)=(2π)−n/2(mˇ∗f)(x).
We denote ⟨f,g⟩ by
[TABLE]
for Cm-valued functions f=(f1,⋯,fm) and
g=(g1,⋯,gm).
Let Lα2(R2)=L2(R2;e2αxdxdy), Lα2(R)=L2(R;e2αxdx).
For k≥1, let Hαk(R2) and Hαk(R) be Hilbert spaces with the norms
[TABLE]
and let Xk=Hαk+1(R2)×Hαk(R2) with the norm
[TABLE]
and let X=X0.
The symbol ⟨x⟩ denotes 1+x2 for x∈R.
Let 1A be the characteristic function of the set A.
We use a≲b and a=O(b) to mean that there exists a
positive constant such that a≤Cb.
Let a∧b=min{a,b} and a∨b=max(a,b).
2. Statement of results
2.1. Linear stability of line solitary waves
To begin with, we recall the linear stability of line solitary waves for (1.1) ([26]).
Let ϕ1=ϕ, ϕ2=∂tϕ, A=I−aΔ and B=I−bΔ.
Then the Benney-Luke equation (1.1) can be rewritten as a system
[TABLE]
[TABLE]
Since (1.1) is isotropic and translation invariant,
we may assume θ=γ=0 in (1.3) without loss of generality.
Let rc(x)=−cqc(x) and Φc=(φc,rc)T.
By (1.4),
[TABLE]
and Φc(x−ct) is a planar traveling wave solution of (2.1).
Linearizing (2.1) around Φc, we have
in the moving coordinate z=x−ct,
[TABLE]
where Lc=c∂z+L+Vc and
[TABLE]
Let
A(η)=1+aη2−a∂z2, B(η)=1+bη2−b∂z2 and
[TABLE]
Then
Lc(η)=e−iyηLc(⋅)=c∂x+L(η)+Vc(η).
We expand L(η) and Lc(η) as
[TABLE]
where L0=L(0), A0=A(0), B0=B(0) and
Eij (i, j=1, 2) is a 2×2 matrix whose entry in row i
and column j equals to 1 and the other entries are zero.
We will abbreviate Eii as Ei.
By Theorem 2.1 in [26], there exist an η0>0,
λc(η)∈C∞([−η0,η0]) and
[TABLE]
such that for η∈[−η0,η0] and z∈R,
[TABLE]
where φc∗(x)=φc(x)+2β(c) and
[TABLE]
We remark that Lc(0) is the same with the linearized operator of
1-dimensional Benney-Luke equation around solitary waves and that
Lc(0)ζ1,c=0, Lc(0)ζ2,c=ζ1,c.
Now we introduce spectral projections associated with continuous eigenvalues
{λ(η)}−η0≤η≤η0.
As in [26, Section 8], let
κc(η)=21ℑ⟨g(⋅,η,c),g∗(⋅,η,c)⟩ and
[TABLE]
Note that gk(z,η,c) and gk∗(z,η,c) are R2-valued functions
that are even in η and that
[TABLE]
Let α∈(0,αc) and η0 be a small positive number
such that for k=1, 2,
[TABLE]
Then for η∈[−η0,η0],
[TABLE]
Let Pc(η0) and Qc(η0):X→X
be projections defined by
[TABLE]
Then Pc(η0) is a spectral projection for Lc
corresponding to a family of continuous eigenvalues
{λc(η)}−η0≤η≤η0.
Let Z=QcX and Lc∣Z be the restriction
of the operator Lc to Z.
Assuming spectral stability of Lc∣Z, we have exponential
stability of etLcQc.
Let 0<a<b, c>1 and α∈(0,αc). Consider the operator Lc
in the space X. Assume that there exist positive
constants β and η0 such that*
[TABLE]
Then for any β′<β, there exists a positive constant C such that
[TABLE]
Remark 2.1*.*
If c>1 is sufficiently close to 1, then the assumption
(S) is valid and the spectrum of Lc near [math] is
similar to that of the linearized KP-II operator around a line
soliton solution. See [26, Theorem 2.4].
2.2. Main Result
Now let us introduce our main result.
Theorem 2.2**.**
Let 0<a<b and c0>1. Assume (S) for c=c0.
Suppose that Φ(t,x,y) is a solution of (2.1)
satisfying
[TABLE]
Then there exist positive constants C and ϵ0 such that if
[TABLE]
then there exist C1-functions c(t,y) and γ(t,y) such that
for every t≥0 and k≥0,
[TABLE]
and for any R>0,
[TABLE]
Moreover, there exists a γ∞∈R such that
for any δ>0,
[TABLE]
In the case where γ∞=0 in (2.33),
the distance between the solution u and the set of line solitary waves
in the energy space grows like t1/2 or faster.
Corollary 2.3**.**
Let c0>1. Suppose that (S) holds for c=c0.
Then for any ϵ0>0, there exists a solution of (2.1) satisfying
(2.27), (2.28) and
[TABLE]
where
K={Φc(xcosθ+ysinθ−ct+γ)∣±c>1,γ∈R,θ∈[0,2π)}.
3. Decay estimates for linearized modulation equations
Modulation of the local amplitude and the local phase shift of line solitary
waves can be described by a system of Burgers’ equations.
In this subsection, we introduce decay estimates for linearized
modulation equations following [22, 24].
Let ν be a real number,
\omega(\eta)=\bigl{\{}1-(\nu/\lambda_{1,c_{0}})^{2}\eta^{2}\bigr{\}}^{1/2} and
[TABLE]
Then A∗(η)Π(η)=diag(λ+(η),λ−(η))Π(η) and
[TABLE]
Let η0 be a positive number satisfying
[TABLE]
and let
χ1(η) and χ2(η) be nonnegative smooth functions such that
χ1(η)+χ2(η)=1,
χ1(η)=1 if ∣η∣≤21η0 and χ1(η)=0 if
∣η∣≥43η0.
Then
[TABLE]
Next, we will estimate the low frequency part of etA∗(η).
Let
[TABLE]
Then
[TABLE]
We can prove the following estimates for K1, K2 and K3
in the same way as [24, Lemma 2.2].
Let Y and Z be closed subspaces of L2(R) defined by
[TABLE]
and let Y1=Fη−1Z1 and
Z1={U∈Z∣∥U∥Z1:=∥U∥L∞<∞}.
By the definition,
[TABLE]
Especially, we have ∥U∥L∞≲∥U∥L2 for any U∈Y.
Let P1 be a projection defined by
P1U=Fη−11[−η0,η0]FyU.
Then ∥P1U∥Y1≤(2π)−1/2∥U∥L1 for any U∈L1(R).
In particular, for any U1, U2∈Y,
[TABLE]
Let χ(η) be a smooth function
such that χ(η)=1 if η∈[−4η0,4η0]
and χ(η)=0 if η∈[−2η0,2η0].
We will use the following estimates to investigate large time
behavior of modulation parameters.
Lemma 3.2**.**
Let k≥0. Then for every t≥0,
[TABLE]
where c1 is a positive constant.
Lemma 3.2 follows immediately from
Lemma 3.1, (3.3) and
(3.4).
Now we will show decay estimates for linearly perturbed equations
of ∂tu=A∗u.
Suppose that δ1, δ2 and κ are positive constants
and that dij(η) and bij(t,η) are
continuous functions satisfying for η∈[−η0,η0] and t≥0,
[TABLE]
Let A(t,Dy)=A0(Dy)+A1(t,Dy),
[TABLE]
and let U(t,s) a solution operator of
[TABLE]
Then we have the following.
Lemma 3.3**.**
Let k≥0.
If δ1 is sufficiently small, then for every
t≥s≥0 and f=(f1,f2)T∈Y×Y,
[TABLE]
where μ(t,s)=exp(−∫stb22(s,0)ds),
C=C(η0) and limsupη0↓0C(η0)<∞.
Remark 3.1*.*
Since χ(Dy)P1=χ(Dy) is bounded on L1(R),
we have χ(Dy)f2∈L1(R)
if f2=P1f~2 and f~2∈L1(R).
Let u=(u1,u2)T be a solution of (3.16) and
v=(∂yu1,u2). Then(3.16) can be read as
[TABLE]
Applying a standard energy method to (3.25)
as in [22, Lemma 4.2], we have (3.17) and (3.18).
We have (3.19) and (3.20)
immediately from (3.17) and (3.18).
Next, we will prove (3.21).
Let w=(w1,w2)T and w(t,y)=μ(t,s)u(t,y). Since Y⊂L∞
and 0<inft≥s≥0μ(t,s)≤supt≥s≥0μ(t,s)<∞,
it suffices to show
∥w1(t)∥L∞≲∥f2∥Y1+∥χ(Dy)f2∥L1.
By (3.16),
Since
∣E1B(t,η)∣+∣E2η−1B(t,η)∣=O(δ2e−κt),
it follows from Lemma 3.2, (H), (3.18) and
(3.26) that
[TABLE]
Next, we will prove (3.22).
Using Lemma 3.2 and (3.19), we have
for w=(w1,w2)T=μ(t,s)U(t,s)diag(1,∂y)f,
[TABLE]
We can prove (3.23) and (3.24) in the same way.
Thus we complete the proof.
∎
Lemma 3.4**.**
Let f=(f1,f2)T.
For every t≥0,
[TABLE]
[TABLE]
[TABLE]
where
Ht(y)=(4πt)−1/2exp(−y2/4t) and
Wt(y)=(2λ1,c0)−11[−λ1,c0t,λ1,c0t](y).
To investigate the large time behavior of γ(t,y), we need the following.
Lemma 3.5**.**
Suppose that f∈L1(R+×R). Then for any δ>0,
[TABLE]
where γ∗=(2λ1,c0)−1∫0∞∫Rf(s,y)dyds.
Lemmas 3.4 and 3.5 can be shown in exactly
the same way as [24, (2.20)–(2.22) and Lemma 2.4].
4. Decomposition of the perturbed line solitary waves
4.1. Ansatz for solutions around line solitary waves
Let us decompose a solution around φc(x−c0t)
into a sum of a modulating line solitary wave
and a dispersive part plus a small wave which is caused by amplitude
changes of the line solitary wave:
[TABLE]
Here h is a large positive constant (see Lemma 4.3).
The modulation parameters c(t0,y0) and γ(t0,y0) denote
the speed and the phase shift of the modulating line solitary wave
qc(t,y)(x−c0t−γ(t,y)) along the line y=y0 at the time t=t0,
U is a remainder part which is expected to behave like an
oscillating tail and Ψc is an auxiliary function
such that
[TABLE]
with ψ∈C0∞(−1,1) and ∫Rψ(x)dx=1.
Note that
[TABLE]
We need the adjustment by Ψc in order to obtain
the energy identity in Section 7.
Note that N(Ψc)=0.
Let c~(t,y)=c(t,y)−c0 and
N0(Φ)=−B0−1(ϕ2∂x2ϕ1+2∂xϕ1∂xϕ2)e2
with Φ=ϕ1e1+ϕ2e2,
e1=(1,0)T and e2=(0,1)T.
In view of (2.2) and the fact that L=L0−∂y2L1,
we have ℓ1=ℓ11+ℓ12+ℓ13,
[TABLE]
Now we introduce a symplectic orthogonality condition to
fix the decomposition (4.1).
Since the adjoint resonant modes are exponentially increasing
as x→∞, we further decompose U into a small solution of
(2.1) and an exponentially localized part following the idea of
[21] and [25, 27, 23] in order to use
exponential linear stability in [26].
Let Φ(t,x,y) be a solution of (2.1) with Φ(0,x,y)=Φc0(x)+U0(x,y)
and let U1 be a solution of
where N1,0=N(Φc(t,y)(z)−Ψc(t,y)(z1)+U)−N(Φc(t,y)(z)−Ψc(t,y)(z1))−N(U) and
[TABLE]
Lemma 4.1 below implies that
U2(t,x,y), as well as U2(t,z,y), are exponentially localized
as x→∞ provided the phase shift γ(t,y) is uniformly bounded.
Lemma 4.1**.**
Let α∈(0,αc0) and U0∈E. Suppose that Φ(t) is a
solution of (2.1) with Φ(0)=Φc0+U0
and that U1(t) is a solution of (4.6). Then
We remark that 0<pn′(x)≤2αpn(x)≤4αe2αx.
By Claim A.2,
[TABLE]
[TABLE]
In the last line, we use the energy identity
[TABLE]
Combining the above, we have
[TABLE]
Using Gronwall’s inequality, we see that for any T>0, there exists a C>0 such that
[TABLE]
By passing to the limit n→∞, we have supt∈[0,T]∥W(t)∥X1≲∥U0∥E since 0<pn(x)↑2e2αx.
Moreover, we can prove that ∥W(t)∥X1 is continuous.
Since W(t)∈C([0,∞;E) and W(t) is weakly continuous in X1,
we have (4.9). Thus we complete the proof.
∎
4.2. The orthogonality condition
We impose a secular term condition for U2(t,z,y) to fix
the decomposition (4.1) with (4.7).
[TABLE]
where η0 is a sufficiently small positive number.
Now we introduce functionals to prove the existence of
the decomposition (4.1) that satisfies (4.7) and
(4.13).
For U∈X and γ, c~∈Y and h≥0, let
c(y)=c0+c~(y) and
[TABLE]
To begin with, we will show that F=(F1,F2) maps
Lα2(R2)×Y×Y×R into Z×Z.
Lemma 4.2**.**
Let α∈(0,αc0), U∈Lα2(R2), c~, γ∈Y and h≥0.
Then there exists a δ>0 such that if
∥c~∥Y+∥γ∥Y≤δ, then
Fk[u,c~,γ,h]∈Z for k=1, 2.
and it follows from the Plancherel theorem and (4.14) that
[TABLE]
Since supy(∣c~(y)∣+∣γ(y)∣)≲∥c~∥Y+∥γ∥Y, we have
[TABLE]
where C is a positive constant depending only on δ.
Combining the above, we obtain
[TABLE]
Since C0∞(R2) is dense in Lα2(R2), it follows that for any
u∈Lα2(R2),
[TABLE]
Thus we complete the proof.
∎
Next, we will prove the existence of parameters c and γ that satisfy
(4.1) and (4.13).
Lemma 4.3**.**
Let α∈(0,αc0).
There exist positive constants δ0, δ1, h0 and C such that
if ∥U∥Lα2<δ0 and h≥h0, then there exists a unique
(c~,γ) with c=c0+c~ satisfying
[TABLE]
Moreover, the mapping {U∈Lα2(R2)∣∥U∥Lα2(R2)<δ0}∋U↦(c~,γ)=:Ω(U)∈Y×Y is C1.
Proof.
We have (F1,F2)∈C1(Lα2(R2)×Y×Y×R;Z×Z)
and for c~, γ~∈Y,
Suppose η0 and e−hα are sufficiently small.
Then D(c,γ)(F1,F2)(0,0,0,h)∈B(Y×Y,Z×Z)
has a bounded inverse and by the implicit function theorem,
there exists a unique (c~,γ)∈Y×Y
satisfying (4.15) and (4.16) for any U satisfying
∥U∥Lα2(R2)<δ0 and the mapping (c~,γ)=Ω(U)
is C1.
∎
Remark 4.1*.*
If U0∈E and Φ(0,x,y)=Φc0(x)+U0(x,y),
then a solution of (2.1) is in the class
and it follows from Lemma 4.3 that
(c~(t),γ(t))=Ω(W(t))∈C1 as long as
∥W(t)∥Lα2 remains small. Since W(0)=0, there exists a T>0 such
that the decomposition (4.1) satisfying (4.7) and
(4.13) persists for t∈[0,T] and
[TABLE]
By a standard argument, we have the following continuation principle for
the decomposition (4.1) satisfying (4.7)
and (4.13).
Proposition 4.4**.**
Let α, δ0 and h be the same as in Lemma 4.3
and let Φ(t) and U1(t) be as in Lemma 4.1.
Then there exists a constant δ2>0 such that if (4.1),
(4.7) and (4.13) hold for t∈[0,T) and
[TABLE]
then either T=∞ or T is not the maximal time of
the decomposition (4.1) satisfying (4.7),
(4.13), (4.21) and (4.22).
5. Modulation equations
In this section, we will derive a system of PDEs which describe the motion
of c(t,y) and γ(t,y).
Let U1(t,z,y)=U1(t,x,y), U(t,z,y)=U(t,x,y) and
τ be a shift operator defined by (τγf)(x,y)=f(x+γ,y).
Then (4.6) and (4.8) are transformed into
[TABLE]
where
[TABLE]
Suppose that the decomposition (4.1), (4.7)
satisfying (4.13) persists for t∈[0,T].
Differentiating (4.13) with respect to t, we have
in L2(−η0,η0),
[TABLE]
where
[TABLE]
The modulation equations of c(t,y) and γ(t,y) can be obtained by
taking the inverse Fourier transform of (5.3).
decays like
∥∂yk+1γ∥Y+∥∂ykc~∥Y≲⟨t⟩−(2k+1)/4
for k≥0 (see Lemma 3.2).
Therefore we expect that the modulation equations for
c(t,y) and γ(t,y) can be reduced to
[TABLE]
To estimate ∥c~(t)∥Y by using Lemma 3.2,
we need to translate the nonlinear term 2m23(c)cyγy into
a divergent form because ∥m23(c)cyγy∥L1=O(t−1).
Let
[TABLE]
We remark that ρ′(c0)=1 and b≃c~
(see Claim C.1 in Appendix C).
Let a~22(c)=ρ′(c)a22(c).
Since a~21(c)=ρ′(c)a21(c) and
a~21′(c)=2ρ′(c)a23(c),
[TABLE]
where p2(c)=a~21(c)−a~21(c0)=O(c~) and
R2G,1=a~22(c)cyy−a~22(c0)byy.
Now we will translate the principal part of (G1,G2) in terms of
b and γ. Let B2(c)=diag(1,ρ′(c)),
B3(c)=B2(c)B1(c)−1, B4(c)=P1B2(c)P1(P1B1(c)P1)−1P1,
We set
Rℓ1,j=(R1ℓ1,j,R2ℓ1,j)T for j=1, 2, r
and Rℓ1=∂y2(Rℓ1,1+Rℓ1,2)+Rℓ1,r.
We rewrite ℓ2 as ℓ2=ct∂cΨc0−c~Ψc0+ℓ~2N+∂y2ℓ~2r,
[TABLE]
Let
Skj[p]=Sk1j[p]−∂y2Sk2j[p] for j=3, 4,
p(z)∈C0∞(R;R2) and
[TABLE]
[TABLE]
Then S3=S31−∂y2S32, A1(t,Dy)=A1(t,0)−∂y2A2(t,Dy) and
[TABLE]
where
Rℓ2=Rℓ2,1−∂y2Rℓ2,2+∂yRℓ2,r,
Rℓ2,j=(R1ℓ2,j,R2ℓ2,j)T for j=1, 2 and r,
[TABLE]
We set
Rkj(t,y)=2π1∫−η0η0IIkj(t,η)eiyηdη
and Rj=(R1j,R2j)T for 0≤j≤5.
5.3. Modulation equations
Let pα(x)=1+tanhαx,
∥U∥W(t)=pα(z1)1/2E(U)1/2L2(R2) and
M∞(T)=sup0≤t≤T,y∈R∣γ(t,y)∣,
[TABLE]
Suppose that ∥U0∥E, Mc,γ(T), M1(T),
M2(T) and M∞(T) and M2(T) are sufficiently small.
Then by Proposition 4.4,
the decomposition (4.1)
satisfying (4.7) and (4.13) persists for t∈[0,T]
and it follows from (5.3), (5.11), (5.19),
(5.21), (5.22) and (5.27)
that for t∈[0,T],
[TABLE]
where B5=I−B4(c0)(∂y2S1−S3),
[TABLE]
Next, we will show that B5−1 can be decomposed
into a sum of a time-dependent matrix multiplied by P1
and an operator which belongs to ∂y2(B(Y)∩B(Y1)).
Let
[TABLE]
By the definition of S1 and (5.23),
[∂y,B∙5]=[∂y,B∘5]=O and
B5−1=B∙5−∂y2B∘5.
Claim 5.2**.**
There exist positive constants η1, h0, δ and C such that
if η0∈(0,η1], h≥h0 and Mc,γ(T)≤δ,
then for t∈[0,T],
[TABLE]
Using Claim B.3 in Appendix B,
we can prove Claim 5.2 in the same way as [24, Claim 5.2].
Finally, we consider B5−1B4(c)R3. In order to prove
∥c~(t,⋅)∥Y+∥γy(t,⋅)∥Y≲⟨t⟩−1/4
by using Lemma 3.3, a crude estimate (C.5)
is insufficient. To distinguish a problematic part of
B5−1B4(c)R3 in Section 6, we decompose
B5−1B4(c)R3 as follows.
Let
[TABLE]
Then B5−1B4(c)R3=−NU1+III1+III2−∂y2III3.
By Claims 5.2, C.2 and (C.5),
[TABLE]
and IIIi(i=1,2,3) are good terms.
Using a change of variable, we will eliminate the bad part from NU1
in Section 6 following the lines of [23, 24].
It follows from Claims C.3–C.13 and the above that
that nonlinear terms of (5.28) satisfy
[TABLE]
[TABLE]
[TABLE]
Proposition 5.3**.**
There exists a positive number δ3 such that if
Mc,γ(T)+M1(T)\linebreak+M2(T)+η0+e−αh<δ3,
then
[TABLE]
where A(t,Dy)=E12+B5−1{A(c0,Dy)−E12+B4(c0)A1(t,Dy)+∂y4B4(c0)S1′}and Nj(2≤j≤4) satisfy (5.29)–(5.31).
6. À priori estimates for modulation parameters
In this section, we will estimate Mc,γ(T) and M∞(T).
Lemma 6.1**.**
There exist positive constants δ4 and C such that if
Mc,γ(T)+M1(T)+M2(T)+η0+e−αh≤δ4, then
[TABLE]
Proof.
Let A∗(Dy)=A(c0,Dy), A(t,Dy)=A0(Dy)+A1(t,Dy) and
[TABLE]
Then A(t,Dy) satisfies (H) and
we can apply Lemma 3.3 to the solution operator U(t,s)
of (3.16).
The Y1-norm of E2NU1 does not necessarily decay
as t→∞. We will express a bad part of NU1
as a time derivative of
[TABLE]
and eliminate that part from (5.32) by the change of variable
[TABLE]
where k~(t,y)=(β1(c0)+S213)−1P1k(t,y).
Since E2B∙5=(1+β1(c0)−1S213)−1E2 and
E2B4(c0)=β1(c0)−1E2P1, it follows from Claim C.9 that
[TABLE]
and
[TABLE]
where A2(t,η)=η−2{A1(t,η)−A1(t,0)} and
[TABLE]
Now we will estimate the right hand side of
[TABLE]
by using Lemma 3.3.
Since ∥k~(0)∥Y1+∥χ(Dy)k~(0)∥L1≲∥⟨y⟩U0∥L2(R2), it follows
that for k≥0 and t≥0,
[TABLE]
By (5.20), we have
∥∂ykn1(s)∥Y+∥∂ykn2(s)∥Y≲Mc,γ(T)2⟨s⟩−(2k+3)/4 and for t∈[0,T],
[TABLE]
It follows from (5.29)–(5.31) that
for k=0, 1, 2 and t∈[0,T],
[TABLE]
[TABLE]
[TABLE]
[TABLE]
Since ∣S213∣+∣∂tS213∣≲e−α((c0−1)t/2+h) and
[TABLE]
it follows from Claims C.9, D.1 and D.2
that for t∈[0,T] and k satisfying 0≤k≤2,
[TABLE]
and that
[TABLE]
[TABLE]
[TABLE]
By the definition and Claim C.1, we have for k=0, 1, 2 and t∈[0,T],
In this section, we will derive an energy estimate for solutions around
modulating line solitary waves.
Lemma 7.1**.**
Let α∈(0,αc0) and δ4 be as in Lemma 6.1.
Suppose that Mc,γ(T)+M1(T)+M2(T)+η0+e−αh≤δ4.
Then there exists a positive constant C such that
[TABLE]
To prove Lemma 7.1, we will derive an energy identity
of (4.3). Let Ay=1−a∂y2 and
[TABLE]
and let ∥U∥Ex=⟨U,U⟩Ex1/2.
The energy of solutions around line solitary waves is infinite since line solitary waves do not
decay in the y-direction. Moreover, the velocity potential φc(x)
tends to a negative constant as x→−∞.
Subtracting infinite energy part from E(Φ) and having
the orthogonality condition (4.13) for η=0 and k=2 in mind,
we find the quantity
[TABLE]
Lemma 7.2**.**
[TABLE]
Proof.
Let Φ=(ϕ1,ϕ2)T, Ψ=(ψ1,ψ2)T and
J=B−1(E12−E21).
Since LΦ=JE′(Φ) and J is skew-symmetric,
[TABLE]
Similarly,
[TABLE]
By integration by parts,
[TABLE]
We remark that
N′(Φc)Ψc=−B−1(rcΔψ~c+2∇rc⋅∇ψ~c)e2∈E and E1N′(Ψc)=O.
Since N is quadratic,
[TABLE]
and it follows from (4.3), (7.1), (7.3) and
(7.4) that
[TABLE]
By (4.3), (7.1), (7.5) and the fact that
N⋅e1=0 and Ψc⋅e2=0,
[TABLE]
Combining the above, we have
[TABLE]
Since (d∂x+L0)Φc+N0(Φd)=0 for d=c0 and d=c(t,y),
it follows from (4.3) and (4.5) that
We have
∣⟨c∂xΨc,Ψc⟩Ey∣≲Mc,γ(T)2⟨t⟩−3/2 because
[TABLE]
Since e2⋅Φc=rc=O(e−2αc∣z∣),
N⋅e1=0 and E1N′(Ψc)=O,
[TABLE]
In view of ∂y2Φc0(z)=−γyy∂xΦc0(z)+(γy)2∂x2Φc0(z), we have
∥sech(αz)∂y2L1Φc0∥E≲∥γyy∥Y+∥(γy)2∥Y and
[TABLE]
We can estimate the rest of the terms in a similar manner.
∎
8. Virial identities
In this section, we will prove virial identities for small solutions
to (1.1). They give bounds on the transport of energy and
the rate of decay of the energy density in the region x>c1t
with c1>1.
If the initial data is small in the energy space and polynomially localized,
we can prove time decay estimates by using virial identities.
Lemma 8.1**.**
Let Φ(t) be a solution of (2.1).
For any c1>1, there exist positive constants α0 and δ
such that if α∈(0,α0) and ∥Φ(0)∥E<δ,
then
[TABLE]
[TABLE]
where ρ1 and ρ2 are constants satisfying ρ2>ρ1≥0.
To start with, we observe the energy conservation law of the Benney-Luke
equation. Let E and Fquad be as
in Section 4.1 and let
Now let p~α=sechα(x−c1t). Then pα′(x−c1t)=αp~α2
and it follows from Claims 8.2 and A.3 and
(A.1) that
[TABLE]
Here we use the fact that α∥u∥Lα2(R2)≤∥∂xu∥L2(R2).
Moreover,
[TABLE]
Since ∥Φ(t)∥E=∥Φ(0)∥E by the energy conservation law,
we have for t≥0,
[TABLE]
with μ=(c1−1)/2
provided α0 and δ5 are sufficiently small.
Using (8.4), we can prove (8.1) and
(8.2) in the same way as [24, Lemma 7.2].
Thus we complete the proof.
∎
Lemma 8.1 and (4.12) give an upper bound of
M1(T).
Lemma 8.3**.**
There exist positive constants α0, δ5 and C such that
if α∈(0,α0) and ∥U0∥E+M∞(T)≤δ5, then
M1(T)≤C⟨x⟩2E(U0)1/2L2(R2).
9. The decay estimate for the exponentially localized
perturbations
In this section, we will estimate M2(T) using the exponential linear
stability of etLc0Qc0
(Theorem 2.1).
Lemma 9.1**.**
Let α∈(0,αc0) and η0 be a sufficiently small positive number.
Then there exist positive constants δ6 and C
such that if ∥⟨x⟩2E(U0)1/2∥L2+Mc,γ(T)+M∞(T)+M2(T)+MU(T)≤δ6,
Since ∣∇jΦc(t,y)(z)∣+∣∇jΨc(t,y)(z1)∣≲e−2αz∧1 for j≥0,
[TABLE]
Combining the above, we have for t∈[0,T],
[TABLE]
Since ∥Pc0(η0)U2∥X1≲(Mc,γ(T)+M∞(T))∥U2∥X1 by (4.13), we have
[TABLE]
Combining the above with Lemma 8.3, we have
(9.1) provided δ6
is sufficiently small. Thus we complete the proof.
∎
10. Large time behavior of the phase shift of line solitary waves
In this section, we will prove Theorem 2.2 and
Corollary 2.3. To begin with, we remark that
Mc,γ(T), M∞(T), M1(T), M2(T) and
MU(T) remain small for every T∈[0,∞] provided the
initial perturbation U0 is sufficiently small. Combining
Proposition 4.4 and Lemmas 6.1,
7.1, 8.3 and 9.1, we
have the following.
Proposition 10.1**.**
There exist positive constants ϵ0 and C such that if
ϵ:=∥(1+x2+y2)E(U0)1/2∥L2(R2)<ϵ0,
then
Mc,γ(∞)+M1(∞)+M2(∞)+MU(∞)≤Cϵ.
We see that (2.29)–(2.32) follows immediately from
Proposition 10.1.
To prove (2.33), we need the first order asymptotics
of γy and c~ as t→∞.
Let
ν=(a11(c0)−a22(c0))/2 and let
ω(η), λ±(η) and Π(η)
be as in Section 3 and
Π(η)=diag(iη,1)Π(η).
Let
[TABLE]
where b22(t,η) is the (2,2) entry of A1(t,η)
and σ3=diag(1,−1).
Then (6.1) is translated into
[TABLE]
where ω~(η)=ω(η)−1,
N=e−λ1,c0tσ3∂yΠ(Dy)−1(n1,n2)T and
[TABLE]
Note that diag(∂y,1)N2=N2 and diag(∂y,1)N3=∂yN3
since E2N2=N2 and E1N3=N3.
We have for η∈[−η0,η0],
[TABLE]
If η0 is sufficiently small, then Π(Dy) and its
inverse belong to B(Y)
and it follows from Claim D.1 and the definitions of b
and d that
[TABLE]
Moreover, we have ∥d(0)∥Y1+∥χ(Dy)d(0)∥L1≲ϵ.
We will investigate the asymptotic behavior of solutions by using the
compactness argument in [16]. More precisely, we consider the
rescaled solution dλ(t,y)=λd(λ2t,λy)
and prove that for any t1 and t2 satisfying 0<t1<t2<∞,
[TABLE]
where d∞(t,y)=t(d∞,+(t,y),d∞,−(t,y))
and d∞,±(t,y) are self-similar solutions of the Burgers’ equation
[TABLE]
satisfying
[TABLE]
First, we will show that rescaled solutions dλ are
uniformly bounded with respect to λ≥1.
Lemma 10.2**.**
Let ϵ be as in Proposition 10.1.
Then there exists a positive constants C such that
for any λ≥1 and t∈(0,∞),
[TABLE]
Proof.
By Proposition 10.1 and (10.4),
we have and (10.8).
Let
[TABLE]
Then
[TABLE]
and it follows from (H), (5.29)–(5.31)
and the fact that A0(η)−A∗(η)=O(η4) that
Suppose that ϵ is sufficiently small.
Then for every t1 and t2 satisfying 0<t1≤t2<∞,
there exist a positive constant C and a function
δ~(R) satisfying limR→∞δ~(R)=0
such that
[TABLE]
Since we can prove Lemma 10.4 in the same way as
[24, Lemma 10.4], we omit the proof.
The initial data of d∞(t,y) at t=0 is a constant multiple of
the delta function. Using the change of variable
[TABLE]
we can transform (10.1) into a conservative system
[TABLE]
where N′′′=λ2,c0dˉ+∂y−1ω~(Dy)σ3d.
Lemma 10.5**.**
[TABLE]
Using (10.11)–(10.13), we can prove
Lemma 10.5 in the same way as [16].
See also the proof of [24, Lemma 10.3].
Combining Lemmas 10.4 and 10.5,
Corollary 10.3 with Claim C.1
and (10.4), we have the following.
Proposition 10.6**.**
Suppose c0>1 and that (S) holds for c=c0.
Let Φ(t,x,y) be as in Theorem 2.2.
Then there exist positive constants ϵ0 and C such that if
ϵ:=∥(1+x2+y2)E(Φ0)1/2∥L2(R2)<ϵ0,
then
[TABLE]
as t→∞, where
[TABLE]
and m±∈(−2,2) are constants satisfying
[TABLE]
See e.g. [24, Proof of Theorem 1.4] for the proof.
where γ∞,1=−(2λ1,c0)−1μ(0)∫Rk~(0,y)dy.
By Proposition 10.1, (6.3), (6.6)
and (6.7),
[TABLE]
It follows from Lemmas 3.3–3.5,
(5.29) and (6.5) that as t→∞,
[TABLE]
[TABLE]
for any δ>0, where
\gamma_{\infty,2}=(2\lambda_{1,c_{0}})^{-1}\int_{\mathbb{R}_{+}\times\mathbb{R}}\mu(s)\bigl{(}\mathcal{N}_{2}(s)+\overset{\bullet}{\mathcal{N}}_{U_{1}}(s)\bigr{)}\cdot\mathbf{e_{2}}\,dsdy and
Let δ~(t) be a function satisfying
limt↓0δ~(t)=0.
Since ∣u±B(s,y)∣≲Hλ2,c0s(y), we have
for y satisfying
∣y+λ1,c0t∣∧∣y−λ1,c0t∣≥4{λ2,c0t/δ~(t)}1/2,
[TABLE]
as t→∞. Combining the above, we have (10.20).
Thus we complete the proof.
∎
Then b(0)=ϵ(1+β1(c0)−1S213(0))−1(Fη−1ζ)(y)e2 and
[TABLE]
Combining the above with (10.19), we have
γ∞≳ϵ,
where γ∞ is a constant in (2.33).
Corollary 2.3 follows immediately from
(2.33) and the fact that γ∞≳ϵ.
Thus we complete the proof.
∎
Appendix A Miscellaneous estimates for operator norms
Claim A.1**.**
Suppose that α∈(0,1/b). Then
[TABLE]
Proof.
Since ∥f∥Lα2(R2)=∥f^(ξ+iα,η)∥L2(R2),
we can prove (A.1) and (A.2)
by using the Plancherel theorem
(see [25]). We can obtain (A.3) and (A.4)
by using (A.2).
∎
Claim A.2**.**
Let α∈(0,1/b) and 1<q<2. Then there exists a positive constant C such that for any γ∈R,
[TABLE]
Proof.
The green kernel K(x,y) of the operator B satisfies that
for (x,y)=(0,0),
[TABLE]
Let K(x,y,x1,y1)=eα(x−x1)K(x−x1,y−y1).
Since
[TABLE]
and supx,y∥K(x,y,x1,y1)∥(L1∩L2)(Rx1,y12)+supx1,y1∥K(x,y,x1,y1)∥(L1∩L2)(Rx,y2)<∞
for α∈(0,1/b), we have (A.5).
We can prove the rest in the same way.
∎
Claim A.3**.**
Let α∈(0,1/b). There exists a positive constant C such that
for any γ∈R,
[TABLE]
Proof.
Using (A.9),
we can prove Claim A.3 in the same way as
[25, Claim 11.2].
∎
Appendix B Operator norms of Skj
Claim B.1**.**
Let α∈(0,αc0).
There exist positive constants η1 and C such that
for η0∈(0,η1], j∈Z≥0, k=1, 2, t≥0 and
f∈L2(R),
[TABLE]
Claim B.2**.**
Let α∈(0,αc0).
There exist positive constants η1, δ and C such that
if η0∈(0,η1] and Mc,γ(T)≤δ,
then for k=1, 2, t∈[0,T] and f∈L2(R),
[TABLE]
[TABLE]
[TABLE]
We can prove Claims B.1 and B.2 in exactly the same way
as [22, Claims B.1 and B.2].
Claim B.3**.**
Let α∈(0,αc0). There exist positive constants C and η1
such that for η∈(0,η1], h≥0, k=1, 2 and t≥0,
[TABLE]
Claim B.4**.**
There exist positive constants η1, δ and C such that
if η0∈(0,η1] and Mc,γ(T)≤δ,
then for k=1, 2, t∈[0,T], h≥0 and f∈L2,
[TABLE]
Let Skj=Sk1j−∂y2Sk2j for j=5, 6 and
[TABLE]
Claim B.5**.**
There exist positive constants η1, δ and C such that
if η0∈(0,η1] and Mc,γ(T)≤δ,
then for k=1, 2, t∈[0,T] and f∈L2,
[TABLE]
We can prove Claims B.3–B.5 in the same way as
[24, Claims A.1–A.3].
Appendix C Estimates of Rj
To start with, we estimate the difference between b and c~ and
the operator norms of δB(c).
Claim C.1**.**
There exist positive constants δ and C such that
if supt∈[0,T]∥c~(t)∥Y≤δ, then for t∈[0,T],
[TABLE]
Proof.
Since
b−c~=P1(ρ(c)−ρ(c0)−ρ′(c0)c~),
we can prove Claim C.1 in exactly the same way as
[22, Claim D.6].
∎
Claim C.2**.**
There exist positive constants C and δ such that if
Mc,γ(T)≤δ, then for t∈[0,T],
[TABLE]
Proof.
The first two estimates follow immediately from the definition of B4.
To prove the last two estimates, we use (5.18),
the fact that ∂y−1(I−P1)∈B(Y) and
Let R2,1G,1=a~22′(c)(cy)2,
R2,2G,1=(a~22(c)−a~22(c0))cy−a~22(c0)(by−cy).
Then R2G,1=∂yR2,2G,1−R2,1G,1 and there exist positive constants
δ and C such that if
Mc,γ(T)≤δ, then for t∈[0,T],
[TABLE]
To prove the last estimate, we use the fact that B4(c) is an upper triangular
matrix.
Let
[TABLE]
Then Rkℓ1,r=Rk1ℓ1,r+∂yRk2ℓ1,r−∂y2Rk3ℓ1,r.
Claim C.4**.**
There exist positive constants δ and C such that if
Mc,γ(T)≤δ, then for t∈[0,T],
[TABLE]
Proof.
We see that (C.1) immediately follows from
Claims B.1, B.2 and 7.3.
Since
There exist Rkj0 (k=1, 2, j=0, 1, 2)
satisfying Rk0=Rk00−2∂yRk10−∂y2Rk20
and positive constants C and δ such that if
Mc,γ(T)≤δ, then for t∈[0,T],
Let α∈(0,αc0). There exist positive constants C, δ and
R2j3(j=1,2) satisfying
[TABLE]
such that if Mc,γ(T)≤δ, then for t∈[0,T],
[TABLE]
Proof.
Let
[TABLE]
Then Rk3=RkU1,1−∂y2RkU1,2 and
[TABLE]
Obviously, we cannot expect that ∥R2U1,0∥Y1 decays as t→∞.
The bad part of R2U1,0 can be extracted as spatial and time derivatives of
L2 functions.
In fact, we have
R2U1,0=RaU1+∂y2RbU1 with
∥RbU1∥Y≲M1(T)⟨t⟩−2 and
[TABLE]
As in [23], we can decompose RaU1 into a sum of an integrable
function and a time derivative of an L2-function.
Since Lc0(0)∗ζ2,c0∗=0, it follows from (5.1) that
[TABLE]
where
RcU1=⟨L1U1,ζ2,c0∗⟩,
RdU1=⟨N(U1),ζ2,c0∗⟩+⟨U1,(γt∂z−[L,τγ]τ−γ)ζ2,c0∗⟩ and
[TABLE]
Thus we complete the proof.
∎
Let Rkj4=Skj5(ct)−Skj6(γt−c~) for j=1, 2.
Then Rk4=Rk14−∂y2Rk24.
By Claims B.4, B.5 and 7.3,
we have the following.
Claim C.10**.**
Let α∈(0,αc0).
There exist positive constants C and δ such that if
Mc,γ(T)≤δ, then for k=1, 2 and t∈[0,T],
[TABLE]
Claim C.11**.**
Let α∈(0,αc0).
There exist positive constants η1, C, δ and Rj5(j=1,2)
such that if η0∈(0,η1] and Mc,γ(T)≤δ,
then for k=1, 2 and t∈[0,T], Rk5=Rk15+∂yRk25 and
[TABLE]
Proof.
Since L∗=B−1AΔE12+E21 and [∂x,τ−γ(t,y)]=0,
[TABLE]
Combining the above with
τ−γ(t,y)[∂y2,τγ(t,y)]=(γy)2∂z2+γyy∂z+2γy∂zy2,
we can find Rk15 and Rk25 satisfying
Rk5=Rk15+∂yRk25 and (C.9).
∎
Claim C.12**.**
Let R6,1=[∂y2,B4(c)]r6 and R6,2=(B4(c)−B4(c0))r6.
Then R6=R6,1+∂y2R6,2 and there exist
positive constants C and δ such that if
Mc,γ(T)≤δ, then for t∈[0,T],
[TABLE]
Proof.
Since
∥r6∥Y≲Mc,γ(T)(Mc,γ(T)+M1(T)+M2(T)2)⟨t⟩−3/4 by ClaimsB.1, 7.3 and
C.1, we have Claim C.12.
∎
Claim C.13**.**
There exist positive constants C, δ and h0 such that if
Mc,γ(T)≤δ and h≥h0, then for t∈[0,T],
[TABLE]
Claim C.13 follows immediately from
Claims B.3, 7.3, C.1 and C.2.
Appendix D Estimates for k(t,y)
By Lemma 8.3,
the L2-norm of k(t,y) decays like t−2 as t→∞.
Claim D.1**.**
Suppose that supy∣γ(t,y)∣≤1 for t∈[0,T].
There exist positive constants δ and C such that if
∥⟨x⟩2E(U0)1/2∥L2<δ, then
[TABLE]
Next, we will give an upper bound of the growth rate of
∥k(t,y)∥L1 when U0(x,y) is polynomially localized in R2.
Claim D.2**.**
Suppose supy∣γ(t,y)∣≤1 for t∈[0,T] and that U1 is a solution of (4.6).
Then there exists a positive constant C such that
[TABLE]
Proof.
Since U1 is a solution of (4.6),
it follows from (8.3) that
Since ∥⟨y⟩k(t,y)∥L2(Ry)≲∥⟨y⟩E(U1)1/2∥L2(R2), we have
Claim D.2.
∎
Acknowledgment
T. M. is supported by JSPS KAKENHI Grant Number 17K05332.
Y. S. would like to express his gratitude to
Institute of Mathematics, Academia Sinica in Taiwan where he worked on this
research.
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