On discrete boundary value problems with nonlocal conditions in a quarter-plane
Abstract.
We consider discrete analogue of model pseudo-differential equations in discrete plane sector using discrete variant of Sobolev–Slobodetskii spaces. Starting from the concept of wave factorization for elliptic periodic symbol we describe solvability conditions for the equations and corresponding discrete boundary value problems. We give also a comparison between discrete and continuous solutions in appropriate discrete normed spaces.
Key words and phrases:
elliptic symbol, invertibility, two-dimensional periodic Riemann problem, digital pseudo-differential operator, discrete equation, periodic wave factorization2010 Mathematics Subject Classification:
Primary: 35S15; Secondary: 65T501. Introduction
A theory of pseudo-differential operators and equations [9, 16, 17, 6] not so long history than other mathematical subjects of analysis. Nevertheless, these operators and related boundary value problems widely arise in a lot of applied problems in physics and technique (see, for example [14] and references therein). Discrete aspects of the theory are reflected in mathematical papers more weak [11, 2] although these studies are closely related to the theory of Fourier series [5]. In our opinion the discrete theory is very important since it permits to use computer calculations to solve concrete applied problems.
We interested in studying discrete pseudo-differential equations and their solvability in appropriate discrete functional spaces. There are certain approaches to studying discrete boundary value problems for partial differential equations including finite difference method [13, 12]. But these approaches are not applicable to studying discrete boundary value problems for elliptic pseudo-differential equations. According to this statement the first author with colleagues has started to develop discrete theory for elliptic pseudo-differential equations [21, 15]. This is main motivation, and we have started from certain canonical domains. First considerations were related to discrete -dimensional space and half-space, and here we consider discrete quadrant.
We consider a special type of boundary conditions, namely integral conditions on a boundary. These conditions are nonlocal, and it seems, such conditions are artificial. But there are a lot of applied problems for partial differential equations with such boundary conditions [1, 4, 3], therefore it is natural way. Moreover, these conditions appear in a natural way to determine arbitrary functions in a general solution of an elliptic pseudo-differential equation.
2. Cones, periodic symbols, digital operators and equations
2.1. Discrete spaces and transforms
Let be an integer lattice in a plane. Let be a quadrant, . We consider functions of discrete variable .
Let us denote . We consider functions defined in as periodic functions defined in with basic square of periods .
One can define the discrete Fourier transform for the function
if the latter series converges, and the function is a periodic function in with basic square of periods . Such discrete Fourier transform preserves all properties of integral Fourier transform, and the inverse discrete Fourier transform looks as follows
The discrete Fourier transform gives one-to-one correspondence between spaces and with norms
We need more general discrete functional spaces and we introduce such spaces using divided differences [13].
The divided differences of first order look as follows
and their discrete Fourier transforms are given by formulas
The divided difference of second order is a divided difference of first order from divided difference of first order
with the Fourier transform
Discrete analogue of the Laplacian is the following
so that its Fourier transform is
We use such discrete objects for constructing discrete Sobolev–Slobodetskii spaces to study wide class of discrete equations.
First, we introduce discrete analogue of the Schwartz space as a set of discrete functions with finite semi-norms
for arbitrary ,
Definition 1. A discrete distribution is called a linear continuous functional defined on the space .
A set of such distributions will be denoted by , and a value of the discrete distribution on the test discrete function will be denoted by .
One can introduce a concept of a support for a discrete distribution. Namely, a support of the discrete function is a subset of the set such that for all points from this subset. For an arbitrary set we denote , and then one says that in the discrete domain if where consists of discrete functions with supports in . If is a union of such where then support of the discrete distribution is the set .
Similarly [26] we can define standard operations in the space , but differentiation will be changed by divided difference of first order. These operations are described in [21] in details, a convergence is meant as a weak convergence in the space .
Example 1. If the function is locally summable then it generates the discrete distribution
(1) |
But there are different possibilities, for example, analogue of the Dirac mass-function
which can not be represented by the formula (1).
Let . We introduce the following definition.
Definition 2. The space consists of discrete distributions and it is a closure of the space with respect to the norm
(2) |
Let us remind that a lot of properties of such discrete spaces were studied in [7], Varying the parameter in (2) we obtain different norms which are equivalent to the -norm. But constants in this equivalence depend on . In our constructions all constants do not depend on .
Definition 3. T͡he space consists of discrete distributions from such that their supports belong to the set . A norm in the space is induced by the norm of the space . The space consists of discrete distributions with supports inside of , and these discrete distributions must admit a continuation into the space . A norm in the space is given by the formula
where infimum is taken for all continuations .
The Fourier image of the space will be denoted by .
2.2. Symbols, operators and projectors
Let be a measurable periodic function in with basic square of periods . Such functions we call symbols.
Definition 4. A digital pseudo-differential operator with the symbol in the discrete quadrant is called an operator of the following type
(3) |
We say that the operator is elliptic one if
A more general digital pseudo-differential operator with the symbol depending on a spatial variable
can be defined in the same way, but here we consider only operators of type (3).
We consider symbols satisfying the condition
(4) |
with constants non-depending on . The number is called an order of digital pseudo-differential operator .
The following simple result can be proved easily.
Lemma 1. A digital pseudo-differential operator with the symbol is a linear bounded operator with a norm non-depending on .
We study a solvability of the discrete equation
(5) |
in the space assuming that .
We will use certain special domain in two-dimensional complex space A domain of the type is called a tube domain over the quadrant , and we will consider analytical functions in the domain .
Lemma 2. For the quadrant the operator has the following form
and is a linear bounded operator for . Moreover, the operator is a projector .
Proof. Corresponding calculations for one-dimensional discrete cone were done in [20]. We use these evaluations adapting to our two-dimensional case. Since
then multiplying two factors and applying the Fourier property on correspondence between a product and convolution we obtain the assertion.
Boundedness of the one-dimensional operator with the kernel for was proved in [7], Theorem 6; two-dimensional case can be considered by the same method.
Remark 1. The operator is so called periodic bi-singular operator. Using classical results for Cauchy type integral [8, 10] one can evaluate the boundary value, but it is not important this time. Since these formulas are very huge we can do some simplifications without lost of generality. For example, we can consider the space with zeroes in coordinate axes and consider the space as closure of the set assuming that all functions of discrete variable vanish on coordinate axes. For this case the first three summands in will be zero.
Lemma 3. If then the space is uniquely represented as the direct sum
Proof. It is simple consequence of Lemma 2. Indeed, the unique representation of the function is the following
A uniqueness of the such representation is possible only for .
To describe a solvability picture for the discrete equation (5) we need some additional elements of multidimensional complex analysis. We give it in the next section.
3. Periodic wave factorization
This concept is a periodic analogue of the wave factorization [18]. Some first preliminary considerations and results were described in [25, 24, 23, 22].
Definition 5. A periodic wave factorization for the elliptic symbol is called its representation in the form
where the factors admit analytical continuation into tube domains respectively with estimates
and constants non-depending on , where
The number is called an index of periodic wave factorization.
Unfortunately, we have no an algorithm to construct the factorization. But the are certain examples of periodic symbols which admit such factorization. We give one of them.
If is an arbitrary function of a discrete variable, , then we have
where are indicators of . Applying the discrete Fourier transform we obtain the representation , and admit an analytical continuation into according to Lemma 2. Thus, we can write , therefore we obtain periodic wave factorization with index zero for the function .
Everywhere below we assume existence of such periodic wave factorization for the symbol with index .
3.1. A unique solvability
This section is devoted to most simple case when a solution of the equation (5) exists and it is unique.
Theorem 1. Let . Then the equation (5) has a unique solution for arbitrary right hand side , and it is given by the formula
where is an arbitrary continuation of into .
Proof Let be an arbitrary continuation of into . Let us introduce the function
so that for .
Now we write the equation (5) in the form
and after applying the discrete Fourier transform and periodic wave factorization we obtain
(6) |
We have the following inclusions according to Lemma 1 and Lemma 2
and then according to Lemma 3 the right hand side of the equality (6) is uniquely represented by the sum
where
.
Further, we rewrite the equality (6)
and using the uniqueness of the representation as the direct sum we conclude that both left hand side and right hand side should be zero. Thus,
and Theorem 1 is proved.
4. Discrete boundary value problem
In this section we consider more interesting case when the equation (5) has a lot of solutions.
4.1. Form of a discrete solution
This section uses some results from [21] concerning a form of a discrete distribution supported at the origin.
Theorem 2. Let . Then a general solution of the equation (5) has the following form
where is an arbitrary polynomial of order of variables satisfying the condition (4) for , – are arbitrary functions from .
The a priori estimate
holds, where denotes a norm in , and does not depend on .
Proof. We start from the equality (6). Let be an arbitrary polynomial of order of variables satisfying the condition (4) for . We multiply the equality (6) by
(7) |
We have in view of Lemma 1
and since then according to Lemma 3 we write the unique decomposition
where
Since then according to Lemma 1 we conclude . Applying the inverse discrete Fourier transform we obtain an equality for two discrete distributions. The left hand side vanishes at least under one condition or , and the right hand side vanishes under the condition ., Thus, it should be a discrete distribution supported on sides of the discrete quadrant . Using corresponding result from [21] we obtain the following form for this discrete distribution
where all summands should be elements of the space .
The left question is how much summands we need in the right-hand side. Counting principle is a very simple because every summand should belong to the space .
Let us consider the summand . Taking into account that order of is we need to verify the finiteness of the -norm for . We have
and the constants do not depend on .
The last summand should be th because for th summand we obtain a positive growth: for we have .
A priori estimates can be obtained in the same way described in [21].
4.2. The Dirichlet discrete boundary condition
We consider here first simple case with discrete Dirichlet boundary conditions. We suppose in this section that It follows from Theorem 2 that we have the following general solution of the equation (5)
(8) |
where are arbitrary functions. To determine uniquely these functions we add the discrete Dirichlet conditions on angle sides
(9) |
First, we apply the discrete Fourier transform to discrete conditions (9) and obtain the following form
(10) |
Let us denote
and suppose that .
Therefore, we have the following system of two linear integral equations with respect to two unknown functions
(11) |
where we have used the following notations
Unique solvability conditions for the system (11) will be equivalent to unique solvability for the discrete Dirichlet problem (5),(9).
Thus, we obtain the following result.
4.3. Non-local discrete boundary condition
We consider here the for the equation (5) with different boundary conditions, namely
(12) |
These additional conditions will help us to determine uniquely the unknown functions in the solution (8).
Indeed, using the discrete Fourier transform we rewrite the conditions (12) as follows
(13) |
Now we substitute the formulas (13) into (8). The first two equality are
It implies the following relations according to the third condition
Then we have at least formally
(14) |
It is left to formulate and to prove exactly the obtained result.
Theorem 3. Let . Then the discrete problem (5),(12) has unique solution which is given by the formula (14).
The a priori estimate
holds with a const non-depending on
Proof. We need to prove the a priori estimate only. Let us consider the first summand
The second summand has the same estimate.
5. A comparison between discrete and continuous solutions
The continuous analogue of the discrete boundary value problem is the following [19].
Let be a pseudo-differential operator with the symbol satisfying the condition
and admitting the wave factorization with respect to the quadrant with index .
We consider the equation
(15) |
with the following additional conditions
(16) |
A solution of the problem (15),(16) is sought in the space [18] and boundary functions are taken from the space . Such problem was considered in [19] and it has the solution
(17) |
under condition that the symbol admits the wave factorization with respect to the quadrant
with index such that .
To construct a discrete boundary value problem which is good approximation to (15),(16) we need to choose and in a special way. First, we introduce the operator which acts as follows. For a function defined in we take its Fourier transform then we take its restriction on and periodically extend it to . Finally, we take its inverse discrete Fourier transform and obtain the function of discrete variable . Thus, we put
Second, the symbol of digital operator we construct in the same way. If we have the wave factorization for the symbol then we take restrictions of factors on and the periodic symbol is a product of these restrictions. For such and the symbol we obtain the following result.
Theorem 4. Let . Then we have the following estimate for solutions and of the continuous problem (15),(16) and the discrete one (5),(12)
where the const depends on functions , can be an arbitrary number.
Proof. We need to compare two functions (14) and (17), more exactly their inverse discrete Fourier transform and inverse Fourier transform at points . We have
since according to our choice for the functions and coincide in points .
We will estimate one summand.
since . It implies the required estimate.
Conclusion
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