An Averaging Theorem for Perturbed KdV Equation
Abstract
We consider a perturbed KdV equation:
For any periodic function , let be the vector, formed by the KdV integrals of motion, calculated for the potential . Assuming that the perturbation is a smoothing mapping (e.g. it is a smooth function , independent from ), and that solutions of the perturbed equation satisfy some mild apriori assumptions, we prove that for solutions with typical initial data and for , the vector may be well approximated by a solution of the averaged equation.
ams:
35Q53, 70K65, 34C29, 37K10, 74H400 Introduction
We consider a perturbed Kortewegde Vries (KdV) equation with zero meanvalue periodic boundary condition:
(0.1) 
Here is a nonlinear perturbation, specified below. For any we denote by the Sobolev space of order , formed by realvalued periodic functions with zero meanvalue, provided with the homogeneous norm . Particularly, if we have
For any , the operator defines a linear isomorphism: . Denoting by its inverse, we provide the spaces , , with a symplectic structure by means of the 2form :
(0.2) 
where is the scalar product in . Then in any space , , the KdV equation (0.1) may be written as a Hamiltonian system with the Hamiltonian , given by . That is, KdV may be written as
It is wellknown that KdV is integrable. It means that the function space admits analytic symplectic coordinates , where , such that the quantities , , are actions (integrals of motion), while , , are angles. In the variables, KdV takes the integrable form
(0.3) 
where is the frequency vector (see [1, 2]). The integrating transformation , called the nonlinear Fourier transform, for any defines an analytic isomorphism , where
It is well established that for a perturbed integrable finitedimensional system,
where , , on time intervals of order the actions may be well approximated by solutions of the averaged equation:
provided that the initial data are typical (see [3, 4, 5, 6]). This assertion is known as the averaging principle. But in the infinite dimensional case, there is no similar general result. In [7, 8], S. Kuksin and A. Piatniski proved that the averaging principle holds for the randomly perturbed KdV equation of the form:
(0.4) 
where the force is a white noise in , is smooth in and is nondegenerate. Our goal in this work is to justify the averaging principle for the KdV equation with deterministic perturbations, using the Anosov scheme (see [3]), exploited earlier in the finite dimensional situation. The main technical difficulty to achieve this goal comes from the fact that to perform the scheme one has to use a measure in the function space which is quasiinvariant under the flow of the perturbed equation (it is needed to guarantee that a small ’bad’ set which we have to prohibit for a solution of the perturbed equation at a time corresponds to a small set of initial data). For a reason, explained in Section 3, to construct such a quasiinvariant measure we have to assume that the perturbation is smoothing. More precisely, we assume that:
Assumption A. (i) For any , the mapping defined by the perturbation in (0.1):
(0.5) 
is analytic. Here is a constant.
(ii) For any and , the perturbed KdV equation (0.1) with initial data
has a unique solution in the time interval , and
We are mainly concerned with the behavior of the actions for . For this end, it is convenient to pass to the slow time and write the perturbed KdV equation (0.1) in the actionangle coordinates :
(0.6) 
Here , and is the infinitedimensional torus, endowed with the Tikhonov topology. The two functions and are the perturbation term , written in actionangle variables, see below (1.3) and (1.4). The corresponding averaged equation is
(0.7) 
where is the Haar measure on . It turns out that the (0.7) is a Lipschitz equation, see below (4.17). We denote by the image of the space under the actionmapping
Clearly, , where is the weighted space
and is its positive octant, . This is a closed subset of .
For any , let us denote by the linear operator on the space of sequences which rotates each component by the angle .
Definition 0.1 A Gaussian measure on the Hilbert space is said to be admissible (where is the same as in assumption A), if the following conditions are fulfilled:
(i) It is nondegenerate and has zero mean value.
(ii) It has a diagonal correlation operator , where every , and . In particular, is invariant under the rotations .
Such measures can be written as:
(0.8) 
where , , is the Lebesgue measure on (see [9, 10]). Clearly, they are invariant under the KdV flow (0.3).
The main result of this work is the following theorem:
Theorem 0.2. Fix any and . Let the curve , be a solution of equation (0.1) and , , . If assumption A is fulfilled and is a admissible Gaussian measure on , then
(i) For any , there exists a Borel subset of and such that , and for we have
(0.9) 
where , , is a solution of the averaged equation (0.7) with the inital data .
(ii) There is a full measure subset of with the following property:
If , then for any the image of the probability measure on under the mapping converges weakly, as , to the Haar measure on .
The assertion (ii) of the theorem means that for any bounded continuous function on ,
In particular, we have
Proposition 0.3. The assumption A holds if in (0.1) is a smooth function, independent from .
It is unknown for us that if the result of Theorem 0.2 remains true for equation (0.1) with nonsmoothing perturbations, e.g. if the right hand side of equation (0.1) is or . So we do not know whether a suitable analogy of the result in [7, 8] holds true if in equation (0.4) the noise vanishes.
The paper has the following structure: Section 1 is about the transformation which integrates the KdV and its Birkhoff normal form. In Section 2 we discuss the averaged equation. We prove that the admissible Gaussian measures are quasiinvariant under the flow of equation (0.1) in Section 3. Finally in Section 4 and Section 5 we establish the main theorem and Proposition 0.3.
Agreements. Analyticity of maps between Banach spaces and , which are the real parts of complex spaces and , is understood in the sense of Fréchet. All analytic maps that we consider possess the following additional property: for any , a map extends to a bounded analytical mapping in a complex ()neighborhood of the ball in .
Notation. We use capital letters or to denote positive constants that depend on the parameters , , but not on the unknown function . We denote For an infinitedimensional vector and any we denote . We often identify with a corresponding vector.
1 Preliminaries on the KdV equation
In this section we discuss integrability of the KdV equation (0.1).
1.1 Nonlinear Fourier transform for KdV
We provide the space with the Hilbert basis ,
Theorem 1.1. There exists an analytic diffeomorphism and an analytic functional on of the form , where the function is analytic in a suitable neighborhood of the octant in , with the following properties:
(i) The mapping defines an analytic diffeomorphism , for any . This is a symplectomorphism of the spaces (see (0.2) and , where .
(ii) The differential takes the form .
(iii) A curve is a solution of the KdV equation (0.1) if and only if satisfies the equation
(1.1) 
Since the maps and are analytic, then for , we have
where and are continuous functions (cf. the agreements).
We denote
Lemma 1.2. For any , if , then
Let be the Banach space of all real sequences with the norm
Denote , where .
Lemma 1.3. The normalized frequency map
is real analytic as a map from to .
1.2 Equation (0.1) in the Birkhoff coordinates.
For we denote:
where . Let be a solution of equation (0.1). We get
(1.2) 
where . Since is an integral of motion of KdV equation (0.1), we have
(1.3) 
Here and below indicates the scalar product in .
For define if , and if . Using equation (1.1), we get
(1.4) 
where . Denoting for brevity, the vector field in equation (1.4) by , we rewrite the equation for the pair as
(1.5) 
We set
In the following lemma and are some fixed continuous functions.
Lemma 1.4. For , we have for any

The function is analytic in each space .

For any , , the function is bounded by .

For any , the function is bounded by .

The function is bounded by , and for any and , the function is analytic on .
Proof: Items (i) and (ii) follow directly from Theorem 1.1. Items (iii) and (iv) follow from item (i) and the chainrule:
From this lemma we know that equation (1.5) may have singularities at . We denote
Abusing notation, we will identify with .
Definition 1.5. For , we say that a curve , , is a regular solution of equation (1.5), if there exists a solution of equation (0.1) such that and
If is a regular solution of (1.5) and , then by assumption A we have
(1.6) 
2 Averaged equation
For a function on a Hilbert space , we write if
(2.1) 
for a suitable continuous function which depends on . Clearly, the set of functions is an algebra. By the Cauchy inequality, any analytic function on belongs to (see agreements). In particularly, for any ,
In the further analysis, we systematically use the fact that the functional only weakly depends on the tail of the vector . Now we state the corresponding results. Let and , . Denoting by , the projection
we have . Accordingly,
(2.2) 
The torus acts on the space by linear transformations , , where . Similarly, the torus acts on by linear transformations with .
For a function and a positive integer we define the average of in the first angles as the function
and define the averaging in all angles as
where is the Haar measure on . The estimate (2.2) readily implies that
Let , then is a function independent of , and is independent of . Thus can be written as .
Lemma 2.1. (See [7]). Let , then

The functions and satisfy (2.1) with the same function as and take the same value at the origin.

These two functions are smooth (analytic) if is. If is smooth, then is a smooth function with respect to vector , for any . If is analytic in the space , then is analytic in the space .
We recall that a vector is nonresonant if
Denote by the set of all Lipschitz functions on .
Lemma 2.2. Let for some . Then for any nonresonant vector we have
uniformly in . The rate of convergence depends on , and .
Proof: Let us write as the Fourier series . Since the Fourier series of a Lipschitz function converges uniformly (see [11]), for any we may find such that for all . Now it is enough to show that
(2.3) 
for a suitable , where . Observing that
for each nonzero . Therefore the l.h.s of (2.3) is smaller than
The assertion of the lemma follows.
3 Quasiinvariance of Gaussian measures
Fix any integer , and let be a admissible Gaussian measure on the Hilbert space . In this section we will discuss how this measure evolves under the flow of the perturbed KdV equation (0.1). We follow a classical procedure based on finite dimensional approximations (see e.g. [12, 10]).
We suppose the assumption A holds. Let us write the equation (0.1) in the Birkhoff normal form, using the slow time :
(3.1) 
where and .
For any , we consider the dimensional subspace of with coordinates . On , we define the following finitedimensional systems:
(3.2) 
where and .
We denote and . By assumption A and Theorem 1.1, for any the mapping
(3.3) 
Theorem 3.2. For any , converges to as in , where and are, respectively, solutions of (3.1) and (3.2) with initial data and .
Proof: Fix any . From (1.6) we know that there exists a constant such that if , then
(3.4) 
The equation (3.2) yields that
(3.5) 
We define
By (3.3), we know that there exists a constant such that
(3.6) 
Denote , then if , then
(3.7) 
Lemma 3.3. In the space , we have the convergence
Proof: Denote , and . Since , using equations (3.1) and (3.2), for , we get
By Lemma 1.3 and Cauchy’s inequality, we know that
Using (3.3) we get that
where
Obviously, as uniformly for .
The lemma now follows directly from Gronwall’s Lemma.
Lemma 3.4. If strongly in and , , as , then