Boundary concentration phenomena for an anisotropic Neumann problem in
Abstract.
Given a smooth bounded domain in , we study the following anisotropic Neumann problem
where
is a small parameter,
, is a positive smooth function
over and
denotes the outer unit normal vector to .
Under suitable assumptions on anisotropic
coefficient , we construct
solutions of this problem with arbitrarily many
mixed interior and boundary bubbles
which concentrate at totally
different
strict local
maximum or minimal boundary points of restricted to , or accumulate to
the same strict local
maximum boundary point of over
as .
Key words and phrases:
Boundary concentration phenomena; Lyapunov-Schmidt reduction method; Anisotropic Neumann problem.2010 Mathematics Subject Classification:
Primary 35B25; Secondary 35B38, 35J25.1. Introduction
This paper is concerned with the analysis of solutions to the anisotropic Neumann problem
(1.1) |
where is a smooth bounded domain in , is a small parameter, , is a positive smooth function over and denotes the outer unit normal vector to . This problem is the Euler-Lagrange equation for the energy functional
(1.2) |
which is well defined because the critical Moser-Trudinger inequality implies the validity of the Sobolev-Orlicz compact subcritical embedding
We are interested in the existence of solutions of equation (1.1) that exhibit the boundary concentration phenomenon as the parameter tends to zero. This work is strongly stimulated by some extensive research involving the isotropic case in equation (1.1):
(1.3) |
where is a smooth bounded domain in with . In the case of , this scalar equation is equivalent to an elliptic system representing the stationary Keller-Segel chemotaxis system with linear sensitivity:
(1.4) |
because the first equation in system (1.4) implies
and hence for some positive constant . Steady states of system (1.4), namely its solutions, are of basic importance for a better understanding of global dynamics to the following Keller-Segel system with :
(1.5) |
which describes chemotactic feature of cellular slime molds sensitive to the gradient of a chemical substance secreted by themselves (see [15]). The one-dimensional form of system (1.4) was first studied by Schaaf [19]. In higher dimensions Biler [2] established the existence of non-constant radially symmetric solution to (1.4) when the domain is a ball. In the general two-dimensional case, Wang-Wei [22], independently of Senba-Suzuki [20], proved that for any (where denotes the first positive eigenvalue of with Neumann boundary condition), system (1.4) has a non-constant solution such that . Meanwhile, if space dimension is , it is known that as infinite time blow-up solutions of the parabolic-elliptic system (1.5) from chemotaxis, steady states of (1.4) produce a significant concentration phenomenon in mathematical biology referred as ‘chemotactic collapse’, namely the blow-up for the quantity in (1.4) takes place as a finite sum of Dirac measure at points with masses equal to or , respectively, depending on whether the blow-up points lie inside the domain or on the boundary. By analyzing the asymptotic behavior of families of solutions to equation Senba-Suzuki [20, 21] exhibited this phenomenon for the term in with positive, uniformly bounded mass as tends to zero. More precisely, if is a family of solutions of under and , such that
then there exist non-negative integers , with for which . Moreover, once tends to zero, this family of solutions concentrate at different points inside the domain and different points on the boundary . In particular, far away from these concentration points the asymptotic profile of is uniformly described as
In addition, these concentration points or blow-up points are nothing but critical points of a functional
where for , but for , denotes the Green’s function of the problem
and its regular part defined as
Reciprocally, in the spirit of the Lyapunov-Schmidt finite-dimensional reduction method del Pino-Wei [12] constructed a family of mixed interior and boundary bubbling solutions for equation with exactly the asymptotic profile above. Successively, when and is between and , Deng [13] used a reductional argument to build solutions for equation (1.3) with bubbling profiles at points inside and on the boundary , which recovered the result in [12] when . In general, such bubbling solutions are called solutions concentrating on -dimensional sets with uniformly bounded mass.
Clearly, a natural question is to ask whether there exist a family of solutions of equation (1.3) concentrating on higher dimensional subsets of with or without uniformly bounded mass as the parameter tends to zero. The first result in this direction was obtained by Pistoia-Vaira [17] in the case that and the domain is a ball with dimension . Based on a fixed-point argument, they constructed a family of uniformly unbounded mass radial solutions of in the ball, which blow up on the entire boundary and hence produce the boundary concentration layer. Following closely the techniques of in [17], Bonheure-Casteras-Noris [5] constructed a family of boundary layer solutions in the annulus blowing up simultaneously along both boundaries, a family of internal layer solutions in the unit ball blowing up on an interior sphere, and a family of solutions in the unit ball with an internal layer and a boundary layer blowing up simultaneously on an interior sphere and the boundary. Very recently, when the domain is a unit disk (corresponding to a unit ball with dimension ), Bonheure-Casteras-Román [7] have successfully constructed a family of uniformly unbounded mass radial solutions of which concentrate at the origin and blow up on the entire boundary. Additionally, some bifurcation analyses of radial solutions to in a ball with dimension were also performed by Bonheure et al. in [4, 6]. As for a general smooth two-dimensional domain , it is very worth mentioning that inspired by the novel result in [17], del Pino-Pistoia-Varia [11] applied an infinite-dimensional form of Lyapunov-Schmidt reduction to establish the existence of a family of solution for equation with unbounded mass , which exhibit a sharp boundary layer and blow up along the entire as tends to zero but remains suitably away from a sequence of critical small values where certain resonance phenomenon occurs. Finally, when the domain has suitable rational symmetries in higher dimensions , Agudelo-Pistoia [1] constructed several families of layered solutions of the stationary Keller-Segel chemotaxis equation with uniformly bounded mass , which exhibit three different types of chemoattractant concentration along suitable -dimensional minimal submanifolds of the boundary.
Problem (1.1) is seemingly similar to equation (1.3). Our original motivation in equation (1.3) is based on the fact that except for , nothing is known about the existence or the boundary concentration phenomenon for solutions of equation (1.3) in higher dimensions . For this aim our idea is to consider partially axially symmetric solutions of equation (1.3) when the domain has some rotational symmetries, which implies that problem (1.1) can be viewed as a special case of equation (1.3) in higher dimensions . Indeed, take as a fixed integer. Let be a smooth bounded domain in such that
Fix with and set
Then is a smooth bounded domain in which is invariant under the action of the group on given by
Note that is the group of linear isometries of and is the unit sphere in . If we seek -invariant solutions of equation (1.3), i.e. solutions of the form
a direct calculus shows that equation (1.3) is transformed to
(1.6) |
Thus if we take anisotropic coefficient
(1.7) |
then equation (1.6) can be rewritten as problem (1.1). Hence by considering rotational symmetry of , a fruitful approach for seeking layered solutions of equation (1.3) with concentration along some -dimensional minimal submanifolds of diffeomorphic to is to reduce it to produce point-wise blow-up solutions of the anisotropic problem (1.1) in the domain of dimension . This approach, together with some Lyapunov-Schmidt finite-dimensional reduction arguments, has recently been taken to construct multi-layer positive solutions of equation (1.3) concentrating along some -dimensional minimal submanifolds of , which can be found in [1] only for the case .
In this paper, our goal is to obtain the existence of boundary separated or clustered layer positive solutions for equation (1.3) in the higher-dimensional domain with some rotational symmetries, by constructing bubbling solutions for the anisotropic planar problem (1.1) with simple or non-simple boundary concentration points when is between and . We try to use a new reductional argument to investigate the effect of anisotropic coefficient on the existence of boundary concentrating solutions to problem (1.1). As a result, with the help of some suitable assumptions on anisotropic coefficient we prove that there exist a family of positive solutions of problem (1.1) with an arbitrary number of mixed interior and boundary bubbles which concentrate at totally different strict local maximum or minimal boundary points of restricted to , or accumulate to the same strict local maximum boundary point of over as tends to zero. In particular, we recover and improve the result in [1] when .
Before precisely stating our results, let us start with some notations. Let be a positive parameter given by the relation
(1.8) |
Clearly, if and only if , and if . Let
and be the anisotropic Green’s function associated to the Neumann equation
(1.9) |
for every . The regular part of is defined depending on whether lies inside the domain or on its boundary as
(1.10) |
In this way, and for any , and the corresponding Robin’s function belongs to (see [1]). Moreover, by the maximum principle, for any , over .
Our first result concerns the existence of solutions of problem (1.1) whose mixed interior and boundary bubbles are uniformly far away from each other and interior bubbles lie in the domain with distance to the boundary uniformly approaching zero.
Theorem 1.1. Let , be any non-negative integers with , and assume that there exist different points such that each is either a strict local maximum or a strict local minimum point of restricted to and satisfies for all , . Then for any sufficiently small , there exist a family of positive solutions for problem (1.1) with different boundary bubbles and different interior bubbles located at distance from such that
where is defined in (1.8), for , but for . More precisely,
where , as , on each compact subset of , the parameter satisfies
for some , and satisfies
In particular, for some , as ,
Our next result concerns the existence of solutions of problem (1.1) with mixed interior and boundary bubbles which accumulate to the same boundary point.
Theorem 1.2. Let , be any non-negative integers with , and assume that is a strict local maximum point of over and satisfies . Then for any sufficiently small , there exist a family of positive solutions for problem (1.1) with different boundary bubbles and different interior bubbles which accumulate to as , such that
where is defined in (1.8). More precisely,
where , as , on each compact subset of , for , but for , the parameter satisfies
for some , and satisfies
In particular, for some , as ,
Now we find that if and the domain
has some rational symmetries in higher dimensions
such that the corresponding anisotropic coefficient
given by (1.7) satisfies the assumptions in Theorem 1.2, then
equation (1.3) has a family of positive solutions with
arbitrarily many mixed interior and boundary layers which
collapse to the same -dimensional minimal submanifold
of as tends to zero. Meanwhile,
we observe that the assumptions in
Theorem contain the following two cases:
(C1)
is a strict
local maximum point of restricted to ;
(C2)
is a strict local maximum
point of restricted in
and satisfies .
Arguing as in the proof of Theorem , we readily prove that if
(C1) holds, then problem (1.1) has positive solutions with
arbitrarily many
boundary bubbles which accumulate to along ; while
if (C2) holds, then problem (1.1) has positive solutions with
arbitrarily many
interior bubbles which accumulate to along the neighborhood near the
inner normal direction of . As for the latter case, our result seems to close some gap which
was left open in the literature [1] regarding
such type of chemoattractant concentration
from the stationary Keller-Segel system with linear
chemotactical
sensitivity function, namely involving the existence of
solutions of equation with
an arbitrary number of interior layers
which simultaneously
accumulate along a suitable -dimensional minimal submanifold
of as tends to zero.
Finally, it is necessary to point out that
radial solutions of equation with concentration on an arbitrary number
of internal spheres were built by Bonheure-Casteras-Noris [6] when the domain
is a ball with dimension , but
a remarkable fact is that, in opposition to our result
or an analogous one given by Malchiodi-Ni-Wei [16] for
a singularly perturbed elliptic Neumann problem on a ball, the layers of those solutions do not accumulate
to the boundary of as tends to zero.
The proof of our results relies on a very well known Lyapunov-Schmidt finite-dimensional reduction procedure. In Section we provide a good approximation for the solution of problem (1.1) and estimate the scaling error created by this approximation. Then we rewrite problem (1.1) in terms of a linear operator for which a solvability theory is performed through solving a linearized problem in Section . In Section we solve an auxiliary nonlinear problem. In Section we reduce the problem of finding bubbling solutions of (1.1) to that of finding a critical point of a finite-dimensional function. In section we give an asymptotic expansion of the energy functional associated to the approximate solution. In Section we provide the detailed proof of Theorems -. Finally, we give some technical explanations in Appendix .
Notation: In this paper the letters and will always denote a universal positive constant independent of , which could be changed from one line to another. The symbol (respectively ) will denote a quantity for which tends to zero (respectively, stays bounded ) as parameter goes to zero. Moreover, we will use the notation (respectively ) to stand for a quantity which tends to zero (respectively, which remains uniformly bounded) as tends to zero.
2. An approximation for the solution
The original cells for the construction of an approximate solution of problem (1.1) are based on the four-parameter family of functions
(2.1) |
which exactly solve
Set
(2.2) |
The configuration space for concentration points we try to look for is the following
(2.3) |
where , is sufficiently small and uniquely defined by in (1.8), and is given by
(2.4) |
Let and be fixed. For numbers , , yet to be determined, but we always assume
(2.5) |
for some , independent of . Define
(2.6) |
and for each ,
(2.7) |
Here, , , are radial solutions of
(2.8) |
with
(2.9) |
and
(2.10) |
and
(2.11) |
and
(2.12) |
According to [8], it readily follows that for any ,
(2.13) |
where
(2.14) |
Obviously, for every , the coefficient has at most polynomial growth with respect to . Moreover,
(2.15) |
Now we construct the approximate solution of problem (1.1) by
(2.16) |
where is a correction term defined as the solution of
(2.17) |
To state the asymptotic behavior of each correction term in terms of , and , we first use the convention
(2.18) |
Lemma 2.1. For any and , then we have
(2.19) |
uniformly in , where is the regular part of the anisotropic Green’s function defined in (1.10).
Proof.
Inserting (2.1), (2.7) and (2.13) into (2.17), we have that for any ,
Using (1.9)-(1.10) we get that the regular part of Green’s function, , satisfies
Set
Then
Direct computations show that there exists a constant such that for any ,
and
and for any ,
and
Hence for any and any ,
On the other hand, if , from the fact that for any (see [1]) we can compute that for any ,
then
While if , by the definition of in (2.3) we easily find
then
As a consequence, from elliptic regularity theory we have that for any and any ,
By Morrey’s embedding theorem,
where , which implies that expansion (2.19) holds with . ∎
From Lemma 2.1 we can easily prove that away from each point , namely for any ,
(2.20) |
While if with some , from the fact that for any and any we find
and for any ,
Thus if ,
(2.21) |
will be a good approximation for the solution of problem (1.1) provided that for each , the concentration parameter satisfies the nonlinear system
(2.22) |
It is necessary to point out that from (2.6), (2.14), (2.15) and the Implicit Function Theorem we readily have that for any sufficiently small and any points , there is a unique solution for system (2) under assumption (2.5). Moreover, for any ,
and
(2.23) |
Let us perform the change of variables
By the definitions of and in (1.8) and (2.6), respectively, we can rewrite equation (1.1) in the following form
(2.24) |
where
(2.25) |
We write , and define the initial approximate solution of (2.24) as
(2.26) |
with and defined in (2.16). What remains of this paper is to look for solutions of problem (2.24) in the form , where will represent a higher-order correction. In terms of , problem (2.24) becomes
(2.27) |
where
and
(2.28) |
For any and , let us introduce a weighted -norm defined as
(2.29) |
where is small but fixed, independent of . With respect to the -norm, the error term defined in (2.28) can be estimated as follows.
Proposition 2.2. There exists a constant such that for any and for any small enough,
(2.30) |
Proof.
By (2.16), (2.17) and (2.26) we obtain
(2.31) |
By (2.2), (2.5) and (2.13) we have that if for any ,
(2.32) |
On the other hand, in the same region, by (2.20) and (2.26) we obtain
(2.33) |
and hence,
which, together with (2.5) and (2.32), easily yields
(2.34) |
Let us fix an index and the region with any but close enough to . From (2.21), (2.26) and Taylor expansion we have that in the ball with large but fixed,
and
where is large but fixed, independent of . Then
(2.35) |
Furthermore, by (2.25),
(2.36) |
By (2.31), (2) and the definitions of , in (2.9)-(2) we can derive that in the region ,
(2.37) |
As in the remaining region with any but close enough to , by (2.9)-(2.13) and (2.31) we find that there exists a constant , independent of every , such that
(2.38) |
On the other hand, in the same region, by (2.5), (2.13), (2.21) and (2.26) we have that
then
(2.39) |
Furthermore, by the Taylor expansion we find that there exists a constant , independent of every , such that
(2.40) |
and
(2.41) |
Hence in the region with any but close enough to , by (2.38), (2.40) and (2.41),
which, together with (2.34) and (2.37), implies the validity of estimate (2.30). ∎
3. Analysis of the linearized operator
In this section we perform the solvability theory for the linear operator under the weighted -norm introduced in (2.29), uniformly on . Notice that , where . As in Proposition 2.2, we have the following asymptotical expansions with respect to and , respectively.
Proposition 3.1. There exists a constant such that for any and for any small enough,
(3.1) |
uniformly in the region with any but close enough to . While if with large but fixed, then
(3.2) |
In addition,
(3.3) |
Proof.
For the sake of simplicity, we consider the estimates for the potential only. By (2.25) we can compute
If with any and large but fixed, by using (2) and Taylor expansion we obtain
and
and hence
(3.4) |
While if with any but close enough to , by (2.39) we find
and by (2.40),
(3.5) |
Additionally, if for all , by (2.33) we deduce
and so
(3.6) |
Jointing together (3.4)-(3.6) and the definition of in (2.29), we obtain the first estimate in (3.3). ∎
Given and points , we consider the following linear problem of finding a function and scalars , , , such that
(3.7) |
where if while if , and , , are defined as follows: let be a large but fixed number and be a smooth, non-increasing cut-off function such that if , and if . Set
(3.8) |
For each , we have and define
(3.9) |
For each , we have and define a rotation map such that . Let be the defining function for the boundary in a small neighborhood of the origin, that is, there exist , small and a smooth function satisfying , and such that . Then we consider the flattening change of variables defined by
Then for each , we set
and define
(3.10) |
Note that , , preserves the homogeneous Neumann boundary condition. Moreover,
(3.11) |
Proposition 3.2. Let be a positive integer. Then there exist constants and such that for any , any points and any , there is a unique solution and , , to problem (3.7). Moreover,
The proof of this result will be split into a series of lemmas which we state and prove as follows.
Lemma 3.3. There exist constants and , independent of , such that for any sufficiently small , any points and any , there is a function
smooth and positive so that
Moreover, is uniformly bounded, i.e.
Proof.
Let us take
where is the uniformly bounded solution of
Choosing the positive constant larger if necessary, it is directly checked that meets all the conditions of the lemma for large but small enough. ∎
Given and , let us consider the linear equation
(3.12) |
Lemma 3.4. There exist and such that for any and any solution of (3.12) with the orthogonality conditions
(3.13) |
one has
where is independent of .
Proof.
Set , being the constant in Lemma 3.3. By (2.5) it follows that for small enough, and by (2.3), all are disjointed for any points . Let be bounded and a solution to (3.12) satisfying (3.13). We define the inner norm of by
and claim that there is a constant independent of such that
(3.14) |
Indeed, set
where is the positive, uniformly bounded barrier constructed by Lemma 3.3 and the constant is chosen larger if necessary, independent of . Then for ,
for ,
and for ,
From the maximum principle (see [18]), it follows that on , which gives estimate (3.14).
We prove the lemma by contradiction. Assume that there exist a sequence , points , functions , and associated solutions of equation (3.12) with orthogonality conditions (3.13) such that
(3.15) |
For each , we have and we consider , where and . Note that
where
By the expansion of in (3.2) and elliptic regularity, converges uniformly over compact sets to a bounded solution of equation
which satisfies
(3.16) |
However, by the result of [3, 9], must be a linear combination of , . Notice that for and . Hence (3.16) implies .
As for each , we have and we consider , where is a rotation map such that . Similarly to the above argument, we have that converges uniformly over compact sets to a bounded solution of equation
which satisfies
(3.17) |
Then is a linear combination of , . Notice that for and . Hence (3.17) implies and then . But by (3.14)-(3.15), , which is a contradiction. ∎
Lemma 3.5. For small enough, if solves (3.12) and satisfies
(3.18) |
then
(3.19) |
where is independent of .
Proof.
According to the results in Lemma 3.4 of [12] and Lemma 4.5 of [13], for simplicity we consider the validity of estimate (3.19) only when the concentration points satisfy the relation for any , and for any sufficiently small, fixed and independent of . Let be a large but fixed number. For any , we define
(3.20) |
where
(3.21) |
From estimate (2.5) and definitions (3.9) and (3.10) we have
(3.22) |
and
(3.23) |
Let and be radial smooth cut-off functions in such that
Denote that for any ,
(3.24) |
and for any ,
(3.25) |
Now define
(3.26) |
Given satisfying (3.12) and (3.18), let
(3.27) |
We can adjust and such that satisfies the orthogonality conditions
(3.28) |
Indeed, testing (3.27) by , , and using (3.18), (3.28) and the fact that if , we find
(3.29) |
(3.30) |
Note that for any and ,
where denotes the Kronecker’s symbol, but for any and ,
From (3.23) and (3.26) it follows that for any and ,
Hence by (3.30) we can get that for any and ,
and then
(3.31) |
We need just to consider . From (3.29) it follows that for any ,
(3.32) |
and for any ,
(3.33) |
where satisfies (3.31). We denote the coefficient matrix of equations (3.32)-(3.33) with respect to . By the above estimates, is diagonally dominant, so invertible, where . Hence is invertible and is well defined.
Estimate (3.19) is a direct consequence of the following two claims.
Claim 1. Let , then for any and ,
(3.34) |
Claim 2. For any and ,
In fact, by the definition of in (3.27) we obtain
(3.35) |
Since (3.28) holds, the previous lemma allows us to conclude
(3.36) |
Using the definition of again and the fact that
(3.37) |
estimate (3.19) then follows from estimate (3.36) and Claim 2.
Proof of Claim 1. Let us first denote that for any , but for any . For any , due to and , we find
(3.38) |
and
(3.39) |
Then for any and , by (3.2), (3.9) and (3.10) we have that in the region ,
Hence
which, together with the definition of in (2.29), implies for all and .
Let us prove the second inequality in (3.34). Consider four regions
Notice first that
(3.40) |
and for any ,
(3.41) |
and for any , by (3.2) and (8.7),
(3.42) |
In ,
(3.43) |
In ,
Using (3.22) and (3.41) we conclude that for any ,
(3.44) |
Moreover, and . From (3.11), (3.40) and (3.42) we can derive that
(3.45) |
In , by (3.11), (3.40) and (3.41),
For the estimation of the first two terms, we split into some subregions:
In , by (2.13) and (3.2) we find
which implies
(3.46) |
In , by (3.1),
(3.47) |
As in with , by (3.2), (3.11), (3.23) and (3.40),
(3.48) |
Finally, in ,
Note that in . Moreover, , ,
(3.49) |
(3.50) |
Combining (3.43), (3.45), (3.46), (3.47), (3) and (3.50), we arrive at
Proof of Claim 2. Testing equation (3.35) against and using estimates (3.36)-(3.37), we find
where we have used that
From estimates (3.31) and (3.34) it follows that for any ,
(3.51) |
Observe that
where
and
Let us first estimate the expression . Integrating by parts the first term and the last term of respectively, we find
From (3.8), (3.9), (3.10), (3.39) and (3.44) we have that and in . Then
By (3.49),
Since in , by (2.5), (3.8), (3.9), (3.10), (3.20), (3.21), (3.38) and (3.39) we can derive that
(3.52) |
Next, we analyze the expression . From (2.5), (3.1), (3.2), (3.8), (3.9), (3.10), (3.11), (3.40) and (3.41) we can estimate
and
and
and
But by (3.23), (3.47) and (3),
So
Owing to the relation in the Appendix
(3.53) |
(3.54) |
Combining estimates (3) and (3.54), we arrive at
(3.55) |
According to (3.51), we still need to calculate with . From the previous estimates of and , we can easily compute
and
It remains to consider the integral over . Using (3.26) and an integration by parts, we have
As above, we get
and
Then
From the above estimates we find
(3.56) |
Furthermore, substituting (3.55)-(3.56) into (3.51), we obtain
Using linear algebra arguments, we can conclude Claim 2 for and complete the proof by (3.31). ∎
Proof of Proposition 3.2. Let us first prove that for any , solutions of problem (3.7), the a priori estimate
(3.57) |
holds. In fact, Lemma 3.5 gives
As in Lemma 3.4, arguing by contradiction to (3.57), we assume further that
(3.58) |
We omit the dependence on . It suffices to prove that . To this end, we multiply (3.7) by , with the cut-off function defined in (3.24)-(3.25), and integrate by parts to find that for any and ,
(3.59) |
From (3.2), (3.8), (3.9), (3.10), (3.38) and (3.39) we can compute
For the estimation of the first term, we decompose into several pieces:
where for , but for . From (2.3), (2.5) and (3.38) we obtain
(3.60) |
uniformly in , . In , by (3.2), (3.8) (3.9) and (3.10) we have that for any and ,
and for any and ,
In , , by (3.60),
In , by (3.1),
Hence
(3.61) |
where for any and , and
but for any and , and
On the other hand, if ,
(3.62) |
and if ,
(3.63) |
and if , by (3.60),
(3.64) |
In addition, due to , we obtain
(3.65) |
As a consequence, replacing estimates (3.61)-(3.65) to (3.59), we have that for any and ,
Then
(3.66) |
From the first two assumptions in (3.58) we get . As in contradiction arguments of Lemma 3.4, we can derive that for any ,
but for any ,
with some constant . In view of the odd function with , by (8.7) and Lebesgue’s theorem we have that
Hence by replacing estimates (3.61)-(3.65) to (3.59) again we have a better estimate
which is impossible because of the last assumption in (3.58). So estimate (3.57) is established and then by (3.66), we find
Let us consider the Hilbert space
with the norm . Equation (3.7) is equivalent to find such that
By Fredholm’s alternative this is equivalent to the uniqueness of solutions to this problem, which in turn follows from estimate (3.57). The proof is complete.
Remark 3.6. Given with , let be the solution of equation (3.7) given by Proposition 3.2. Multiplying (3.7) by and integrating by parts, we get
By Proposition 3.1 we find
Remark 3.7. The result of Proposition 3.2 implies that the unique solution of equation (3.7) defines a continuous linear map from the Banach space of all functions in for which , into . It is necessary to point out that the operator is differentiable with respect to the variables in . More precisely, if we fix and set , then by formally computing the derivative of with respect to and using the delicate estimate we can obtain the a priori estimate
4. The nonlinear problem
Consider the nonlinear problem: for any points , we find a function and scalars , , such that
(4.1) |
where satisfies (3.1)-(3.3), and , are defined in (2.28). We have the following result.
Proposition 4.1. Let be a positive integer. Then there exist constants and such that for any and any points , problem (4.1) admits a unique solution for some coefficients , , , such that
(4.2) |
Furthermore, the map is a -function in and , precisely for any and ,
(4.3) |
where .
Proof.
Proposition and Remarks 3.6-3.7 allow us to apply the Contraction Mapping Theorem and the Implicit Function Theorem to find a unique solution for problem (4.1) satisfying (4.2)-(4.3). Since it is a standard procedure, we omit the details, see Lemmas 4.1-4.2 in [10] for a similar proof. We just mention that and . ∎
5. Variational reduction
Since problem (4.1) has been solved, we find a solution of problem (2.27) and hence to the original equation (1.1) if we match with the coefficient in (4.1) so that
(5.1) |
We consider the energy functional defined in (1.2) and take its finite-dimensional restriction
where
with defined in (2.26) and the unique solution to problem (4.1) given by Proposition 4.1. Define
Then by (1.8),
(5.2) |
Proposition 5.1. The function is of class . Moreover, for all sufficiently small, if , then satisfies (5.1), that is, is a solution of equation (1.1).
Proof.
Since the map is a -function in and , we can check that is a -function of in . Assume that solves problem (4.1) and . Then by (5.2), we have that for any and ,
(5.3) |
Recall that . From (2.1), (2.2), (2.7) and (2.16) we know that
From the fact that for any , we have that
and for each ,
As in the proof of Lemma 2.1, by the elliptic regularity of the equation we can prove that
Then
So
(5.4) |
On the other hand, by (3.8), (3.9), (3.10) and (3.38) we can compute
Then
(5.5) |
Hence by (5.4)-(5.5), equations (5) can be written as, for each and ,
which is a strictly diagonal dominant system. This implies that for each and . ∎
In order to solve for critical points of the function , a delicate ingredient is the expected uniformly -closeness between the functions and , which will be applied in the proof of our main theorems.
Proposition 5.2. For any points and for any small enough, the following expansion uniformly holds
where
Proof.
Using , a Taylor expansion and an integration by parts give
so we get
taking into account , and and (3.3). Let us differentiate with respect to ,
From estimates , , and we find
The continuity in of all these expressions is inherited from that of and its derivatives in in the norm. ∎
6. Expansion of the energy
In this section we will give an asymptotic estimate of where is the approximate solution defined in (2.16) and is the energy functional (1.2) associated to problem (1.1).
We have
Proposition 6.1. Let be a positive integer. With the choice (2) for the parameters , there exists such that for any and any points , the following expansion uniformly holds
(6.1) |
where is large but fixed, independent of , and is given by
(6.2) |
Proof.
Observe that
(6.3) |
Let us analyze the behavior of . From the definition of in (2.16) we get
From (2.20)-(2.21) we can compute
Using the relation and the change of variables , we obtain
where . But
and
Then
(6.4) |
Similarly, by (2.9), (8.3) and (8.7) we get
Note that
Then
(6.5) |
Hence by (6.2), (6.4) and (6),
(6.6) |
Regarding the expression , by (2.26) we have
By (2.5), (2) and (8.3)-(8.6),
Then
(6.7) |
Submitting (6.6)-(6.7) into (6.3), we obtain
7. Proofs of theorems
Proof of Theorem 1.1. We will look for a solution of problem (1.1) in the form , where the concentration points are determined by the parametrization
where and belong to the configuration space
for any small and independent of . Notice that if is a critical point of the reduced energy in , then the function is a solution of problem (1.1) with the qualitative properties described by Theorem 1.1. Hence with the aid of (5.2), Propositions 5.2 and 6.1 we are led to find a critical point of the reduced energy , or equivalently, a critical point of
(7.1) |
We claim that can be written as
(7.2) |
where the smooth functions depends on and but only depends on , and , , and uniformly converge to zero as . In fact, using asymptotical properties of the regular part of the anisotropic Green’s function in [1], we have that for any and ,
(7.3) |
where , the vector function for any and , the mapping with . Then
(7.4) |
Moreover, if with ,
(7.5) |
while if and ,
(7.6) |
On the other hand, using the smooth property of over , we perform a Taylor expansion around each boundary point along the inner normal vector to give
(7.7) |
Inserting (7.4)-(7.7) into (7) and using (2.18) and the fact that for all with , we conclude that expansion (7.2) holds.
We seek a critical point of by degree theory. Let be the tangential derivative which is defined on . Set
Then
Due to with , we can choose small enough so that for any , there exists a unique positive such that and . Set , . Since are different strict local maximum or strict local minimum points of on , we have that that for any sufficiently small , and any , the Brouwer degrees
and
Then by (7.2),
Hence if is small enough, there exists such that . In particular, as , which completes the proof.
Proof of Theorem 1.2. We need just to find a critical point of such that points accumulate to . For this aim, we consider the configuration space
where is a sufficiently small but fixed number, independent of . Using (5.2), Propositions 5.2 and 6.1 together with the fact that for all with , we obtain that reduces to
(7.8) |
-uniformly in . Let us claim that for any , and for any small enough, the maximization problem
has a solution in the interior of . Once this claim is proven, we can easily conclude the qualitative properties of solutions of (1.1) described by Theorem 1.2.
Let be the maximizer of . We are led to prove that belongs to the interior of . First, we obtain a lower bound for over . Around the point , we consider a smooth change of variables
where is a diffeomorphism and is an open neighborhood of the origin such that and . Let
where and satisfy , for all sufficiently small, fixed and independent of . By using the expansion we find
Then it is clear to see because of . Since is a strict local maximum point of over and satisfies , there exists a constant independent of such that
From (7.3) it follows that for any and with ,
Moreover, for any with ,
Hence by (7),
(7.9) |
Next, we suppose .
There are four possibilities:
C1. There exists an such that
, in which case,
for some
independent of ;
C2. There exists an such that
, in which case,
for
some independent of ;
C3. There exists an such that
;
C4. There exist indices , , such that
.
From (1.9), (7.3) and the maximum principle we have that
for all and with ,
Thus in the first and second cases,
which contradicts to (7.9).
This shows that . By the condition of over ,
we deduce for all .
In the third case,
(7.10) |
In the last case, if and ,
(7.11) |
while if and ,
(7.12) |
Comparing (7)-(7) with (7.9), we obtain
(7.13) |
which is impossible by the choice of in (2.4).
8. Appendix
According to [8], for a radial function there exists a radial solution
(8.1) |
for the equation
where
Moreover, if is the smooth function with at most logarithmic growth at infinity, then a direct computation shows that
(8.2) |
where
Proof of (3.53). Using the change of variables , we denote that
(8.3) |
Let , and be some radial solutions of
where
Obviously,
Using formulas (8.1)-(8.2) and replacing with , we can compute
(8.4) |
and
(8.5) |
By (2.9) we obtain
and hence
(8.6) |
This combined with (8.3)-(8.5) readily implies
(8.7) |
Furthermore,
In a straightforward but tedious way, by the explicit expression of we can compute
(also see [14] on Page ). Moreover,
Therefore,
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