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Research article

Regularized homogenization on irregularly perforated domains

  • Received: 20 June 2024 Revised: 06 February 2025 Accepted: 10 February 2025 Published: 26 February 2025
  • We studied stochastic homogenization of a quasi-linear parabolic partial differential equation (PDE) with nonlinear microscopic Robin conditions on a perforated domain. The focus of our work lies in the underlying geometry that does not allow standard stochastic homogenization techniques to be applied directly. Instead, we introduced a concept of regularized homogenization: We proved homogenization on a regularized but still random geometry and demonstrated afterwards that the form of the homogenized equation was independent from the regularization, though the explicit values of the coefficients depended on the regularization. Then, we passed to the regularization limit to obtain the anticipated limit equation where the coefficients were finally independent from the intermediate regularizations. We provided evidence that the regularized homogenization and the classical stochastic homogenization coincided on geometries that indeed allowed stochastic homogenization. Furthermore, we showed that Boolean models of Poisson point processes were covered by our approach.

    Citation: Martin Heida, Benedikt Jahnel, Anh Duc Vu. Regularized homogenization on irregularly perforated domains[J]. Networks and Heterogeneous Media, 2025, 20(1): 165-212. doi: 10.3934/nhm.2025010

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  • We studied stochastic homogenization of a quasi-linear parabolic partial differential equation (PDE) with nonlinear microscopic Robin conditions on a perforated domain. The focus of our work lies in the underlying geometry that does not allow standard stochastic homogenization techniques to be applied directly. Instead, we introduced a concept of regularized homogenization: We proved homogenization on a regularized but still random geometry and demonstrated afterwards that the form of the homogenized equation was independent from the regularization, though the explicit values of the coefficients depended on the regularization. Then, we passed to the regularization limit to obtain the anticipated limit equation where the coefficients were finally independent from the intermediate regularizations. We provided evidence that the regularized homogenization and the classical stochastic homogenization coincided on geometries that indeed allowed stochastic homogenization. Furthermore, we showed that Boolean models of Poisson point processes were covered by our approach.



    The theoretical study of weakly coupled limit cycle oscillators is being actively developed in several research fields. For example, in statistical physics, various models are being developed, whereas in network science, synchronization on complex networks is attracting attention. As we state later, mathematical analysis of this field is being promoted, especially by those who are concerned with functional equations. Furthermore, this phenomenon is applied to various areas of engineering, including neural networks, bio-sciences, and network engineering[9].

    Limit cycle oscillators, which are also called nonlinear oscillators, are different from harmonic oscillators, whose limit cycle is vulnerable to the perturbation forces from outside. The synchronization phenomenon is another feature of coupled limit cycle oscillators under specific conditions.

    As is well known, such a phenomenon was first discovered by Huygens in the 17th century, who devised the pendulum clock for navigation officers. The physical formulation of this phenomenon was rigorously discussed later in the 1960's. In 1967, Winfree[37] proposed an attractive formulation, in which he successfully and rigorously defined the phase of the oscillator. He also revealed the region of synchronization in the sense of the phase space.

    Based on Winfree's contribution, Kuramoto[19] proposed a simplified but more sophisticated model, which is called the Kuramoto model. The features of his approach are phase reduction and mean field approximation. His discussion begins with the usual dynamical system:

    dXdt=F(X),

    where X is the n-dimensional vector, and F is the n-dimensional vector valued function. Based on Winfree's theory, Kuramoto defined the phase of this system as that satisfying

    dϕdt=ω,

    where ω=2π/T0 is the frequency of the oscillator with period T0. From this definition, he derived the temporal behavior of the phase as

    dϕdt=ϕF(X),

    which is the start point of phase reduction. In an N-oscillator system, he described the temporal evolution of the phase (or disturbance of phase) of each oscillator:

    dϕjdt=ωj+Nk=1Kjksin(ϕjϕk)(j=1,2,N), (1.1)

    where ϕj(j=1,2,,N) is the phase or phase disturbance of the j-th oscillator, ωj, the natural frequency (for the definition of the natural frequency, see p.67 in[19], for instance), and Kjk, the coupling strength between the jth and kth oscillators.

    Kuramoto[17][19] further sophisticated (1.1) by applying the mean field approximation and the assumption Kjk=K/N, which means that all oscillators couple with uniform strength (Kuramoto called this model as global coupling[20]):

    {dϕjdt=ωj+Krsin(ηϕj)(j=1,2,N),rexp(iη)=1NNj=1exp(iϕj), (1.2)

    where r=r(t) is the order parameter, and η is the average phase. Note that i=1 hereafter. As is well known, r[0,1] measures the coherence strength of the oscillators.

    Since this model is sufficiently simple for rigorously analyzing and simulating on computers, numerous investigations have been conducted on it. For instance, Daido[8] derived a model that replaces the term sinθ by a more general function, and Bonilla[4] revealed stability with the aid of asymptotic expansion. Recently, Li[26] considered the Kuramoto-type model with intrinsic frustrations.

    As for the stability analysis, the work by Strogatz and Mirollo[34] is the first one, which concerns the spectrum of the incoherent state as the number of oscillators tends to infinity. Later, Crawford[6][7] applied the center manifold reduction to verify the stability of incoherence in detail.

    Due to the limitation of space, we refer the reader to the survey by Acebrón[3] of this research area.

    From the perspective of network science, it is interesting to generalize the network topology and distribution of coupling strength. Ichinomiya[14] proposed a model on random networks, and Nakao[29] numerically analyzed a model on a complex network.

    Although (1.2) is a system of ordinary differential equations, adding white noise to it makes it possible to apply partial differential equation-based analysis. We consider

    {dϕjdt=ωj+Krsin(ηϕj)+ξj(t)      V1(ϕj,t,ωj)+ξj(t)(j=1,2,N),rexp(iη)=1NNj=1exp(iϕj), (1.3)

    where {ξj(t)}Nj=1 are the independent Wiener processes satisfying

    <ξj(t)>=0,  <ξj(t)ξk(τ)>=2Dδ(tτ)δjk,

    <> stands for the mean value, D>0, the diffusion coefficient, δ(), the Dirac's delta function, and δjk, the Kronecker's delta. In virtue of the theory of stochastic processes (see Remark 1 below), the Fokker-Planck equation, which describes the temporal behavior of the probability density of particles subject to (1.3)[10][30][33], is written as

    {ϱt+θ[(ω+Krsin(ηθ))ϱ]D2ϱθ2=0,rexp(iη)=R2π0exp(iθ)ϱ(θ,t;ω)g(ω)dϕdω, (1.4)

    where ϱ(θ,t;ω) is the probability distribution function of the oscillators' phase θ at time t with natural frequency ω, and g(ω) is the probability distribution function of ω. The independent variables θ and t represent the phase of oscillators and time, respectively, and we regard ω as a parameter.

    Remark 1. Let X(t) be a Markovian process defined on t>0, and {Kj(x)}j=1 be a series of its intensity defined by

    Kj(x)=limτ0(X(τ)X(0))j/τ.

    Then, the probability distribution function w(x,t) of X(t) at time t satisfies[33]

    w(x,t)t=j=11j!(x)j{Kj(x)w(x,t)}. (1.5)

    A Markovian process satisfying

    Kj(x)=0  (j=3,4,)

    is called to be continuous. One example of this type of stochastic process is the one driven by the Brownian motion, like (1.3). In this case, (1.5) becomes

    w(x,t)t=x[K1(x)w(x,t)]+122x2[K2(x)w(x,t)],

    which is the Fokker-Planck equation. Applying this argument to (1.3), where K1=V1 and K2=2D, the corresponding Fokker-Planck equation is written as

    ϱt+θ(V1ϱ)D2ϱθ2=0,

    which corresponds to (1.4)1 (hereafter, we represent the ith equation of (a.b) as (a.b)i).

    By substituting (1.4)2 into (1.4)1, we have a single integro-differential equation with suitable boundary and initial conditions:

    {ϱt+ωϱθ+Kθ[ϱ(θ,t;ω)R2π0sin(ϕθ)ϱ(ϕ,t;ω)g(ω)dϕdω]       D2ϱθ2=0θ(0,2π),t>0,ωR,iϱθ|θ=0=iϱθ|θ=2π(i=1,2),t>0,ωR,ϱ|t=0=ϱ0θ(0,2π),ωR, (1.6)

    which is the so-called Kuramoto-Sakaguchi equation[24]. This approach enables macroscopic analysis when a system consists of numerous oscillators. As we state later, (1.6) with D=0 has also been discussed in past arguments.

    Kuramoto also presented a direction to take the spatial validity of coupling strength into account in his original model, which he called the non-local coupling model. In it, the strength of the connection between oscillators depends on the distance between them[21]. Due to the varying strength of connections, it was shown that characteristic patterns, such as a chimera pattern, emerge[21][22]. Numerical studies of the chimera state have also been conducted, mainly by Abrams and Strogatz[1][2].

    In spite of numerous contributions concerning numerical simulations, there have been few studies regarding the mathematical analysis of this model. In this paper, we discuss the existence and uniqueness of the global-in-time solution to this model. We also discuss the nonlinear stability of the trivial stationary solution and existence of the vanishing diffusion limit. We note that the vanishing diffusion limit is discussed in the function spaces of higher order derivative than that by Ha and Xiao's[11] by applying a different approach.

    The remainder of this paper is organized as follows. In the next section, we formulate the problem of the phase reduction of non-local coupling oscillators, including both with and without diffusion. In Section 3, we introduce related work. In Sections 4 and 5, we are concerned with the local and global-in-time solvability of the problem and the stability of the stationary incoherent solution, respectively. We discuss the existence of the solution in the vanishing diffusion limit in Section 6, and provide a conclusion and discuss remaining issues in Section 7.

    In this section, we formulate the problem to be considered.We begin the discussion with the temporal evolution of the phase with additive noise under non-local coupling [15][20][31]:

    dϕdt(x,t)=ω+RG(xy)Γ(ϕ(x,t)ϕ(y,t))dy+ξ(x,t), (2.1)

    where x and y stand for the location of each oscillator; Γ(), the phase coupling function which is periodic with respect to its argument and depend only on the difference of each oscillator's phase, and G(), its strength; ω, the natural frequency of each oscillator, and ξ(x,t), the Wiener process satisfying:

    <ξ(x,t)ξ(y,τ)>=2Dδ(xy)δ(tτ)

    with D being the diffusion coefficient. Kuramoto mentioned that the non-local coupling model encompasses the original Kuramoto model as a specific case of (2.1) when G(x) is a constant (p.132 in[20], [21]).

    It is also to be noted that sin(ϕjϕk) in (1.1) is the first Fourier mode approximation of the periodic function Γ(ϕjϕk)[19]. It is possible to adopt sin() for the non-local coupling case as in[16], but in many cases, they apply Γ() for the non-local coupling model. By regarding ω and ϕ as random variables, the average of the second term in the right-hand side is written as[15][16][18]

    RG(xy)dyRg(ω)dω2π0Γ(ϕϕ)ϱ(ϕ,t;y,ω)dϕ,

    where g() is the probability distribution function of the natural frequency, and ϱ=ϱ(,t;x,ω) is the probability distribution function of the phase at time t, with location x and natural frequency ω of each oscillator. We replace the second term in the right-hand side of (2.1) with the representation above to obtain:

    dϕdt=ω+RG(xy)dyRg(ω)dω2π0Γ(ϕϕ)ϱ(ϕ,t;y,ω)dϕ+ξ(x,t)    V2(ϕ,t,x,ω)+ξ(x,t). (2.2)

    If we consider the case that G(x) is a constant K in (2.1), the average of the second term in the right-hand side is

    KRg(ω)dω2π0Γ(ϕϕ)ϱ(ϕ,t;ω)dϕ,

    and (2.2) becomes

    dϕdt=ω+KRg(ω)dω2π0Γ(ϕϕ)ϱ(ϕ,t;ω)dϕ+ξ(x,t),

    which corresponds to (1.3) as a infinite population limit of it.

    Note that (2.2) is the mean field approximation to (2.1), in the sense that we replace the second term of the right-hand side of (2.1) with its average. However, while (1.4)2 is derived by taking the infinite limit of oscillators' population, this representation of the average is theoretically exact.

    By tracing the same argument as we derived (1.4), the Fokker-Planck equation corresponding to (2.2) is written as (hereafter we denote the phase by θ)

    ϱt+θ(V2ϱ)D2ϱθ2=0.

    Together with suitable initial and boundary conditions, the problem corresponding to (2.2) is written as[15][31].

    {ϱt+θ(ωϱ)+θ(F[ϱ,ϱ])D2ϱθ2=0                                    θ(0,2π),t>0,(x,ω)R2,iϱθi|θ=0=iϱθi|θ=2π(i=0,1),t>0,(x,ω)R2,ϱ|t=0=ϱ0  θ(0,2π),(x,ω)R2, (2.3)

    where

    F[ϱ1,ϱ2]ϱ1(θ,t;x,ω)RG(xy)dyRg(ω)dω2π0Γ(θϕ)ϱ2(ϕ,t;y,ω)dϕ. (2.4)

    It is to be noted that, in[15], [21] and[31], they deal with problem (2.3) with F[ϱ1,ϱ2] replaced with

    ˜F[ϱ1,ϱ2]ϱ1(θ,t;x)RG(xy)dy2π0Γ(θϕ)ϱ2(ϕ,t;y)dϕ,

    which corresponds to the case g(ω)=δ(ωω). This means that all the oscillators have the same natural frequency, and ϱ does not depend on ω. In other words, ω is not regarded as a random variable. However, it is generally reasonable to apply (2.3)-(2.4) as Kawamura[16] did, as in the original Kuramoto model ((1.4) or (1.6)). Therefore, we employ (2.3) together with (2.4) in this paper.

    In (2.3), the unknown function is ϱ, and the independent variables are θ and t, which stand for the phase and time, respectively. We regard x and ω as parameters. We also use the notations

    F(k)[ϱ1,ϱ2]    ϱ1(θ,t;x,ω)RG(xy)dyRg(ω)dω2π0Γ(k)(θϕ)ϱ2(ϕ,t;y,ω)dϕ                                                                                         (k=1,2,).

    Note that we denote the j-th derivative of Γ(θ) by Γ(j)(j=1,2,), especially the first derivative by Γ(θ). Obviously, Γ(0)=Γ.

    As in the original Kuramoto model, the vanishing diffusion case is worth considering:

    {ϱt+θ(ωϱ)+θ(F[ϱ,ϱ])=0θ(0,2π),t>0,(x,ω)R2,iϱθi|θ=0=iϱθi|θ=2π  (i=0,1),t>0,(x,ω)R2,ϱ|t=0=ϱ0  θ(0,2π),(x,ω)R2. (2.5)

    It is obvious that ˉϱ=1/2π is the trivial stationary solution to (1.6), (2.3) and (2.5). Moreover, on the basis of appropriate assumptions on ϱ0, g and G, the following properties of ϱ will be derived (see, for instance, Lemma 2.1 in [11], Lemmas 1.1-1.2 in[24] and Lemma 4.3 of this paper):

    ϱ(θ,t;x,ω)0  θ(0,2π),t(0,T),(x,ω)R2,2π0ϱ(θ,t;x,ω)dθ=1  t(0,T),(x,ω)R2

    for arbitrary T>0, which are natural as the properties of the probability distribution function. In this paper, we discuss the solvability and some stability properties of (2.3), as well as the convergence of the solution of (2.3) to that of (2.5) as D tends to zero.

    Mathematical arguments concerning the solvability of the Kuramoto-Sakaguchi equation (1.6), which corresponds to the original Kuramoto model (1.3), was first presented by Lavrentiev et al.[24][25]. In their former work[24], they constructed the classical global-in-time solution when the support of g(ω) is compact.

    Later, they removed this restriction[25] by applying the a-priori estimates derived from the energy method. They also studied the regularity of the unknown function with respect to ω. Concenring the stability, a pioneering work was conducted by Strogatz and Mirollo[34], who were concerned with the linear stability of the trivial stationary solution ˉϱ=1/2π. Through the investigation of the spectrum of the linearized operator, they verified the existence of the critical coupling strength over which the coherent state becomes stable. Recently, Ha and Xiao[11] discussed the nonlinear stability of ˉϱ and convergence of the solution as D tends to zero. However, their estimate remained in the space L with respect to θ, as we discuss in detail in Section 6. They also verified the instability of ˉϱ when the support of g(ω) is sufficiently narrow[12].

    For the case of vanishing diffusion D=0 in (1.6), Chiba[5] argued the nonlinear stability of the trivial stationary solution under the assumption of unbounded support of g(ω).

    Concerning the non-local coupling model, however, there are no mathematical arguments as far as we know.

    In this section, we discuss the global-in-time solvability of (2.3). We first prepare the definitions of function spaces.

    In this subsection, we define the function spaces used throughout this paper. Let T>0, and G be an open set in R. Hereafter, L2(G) stands for a set of square-integrable functions defined on G, equipped with the norm

    The inner product is defined by

    where denotes the complex conjugate of .

    For simplicity, we denote the -norm of a function with respect to merely by or

    Hereafter, let us use the notation for simplicity.

    By and , we mean the spaces of real continuous and -times continuously differentiable functions on , respectively. The notation denotes a set of functions with a compact support in .

    For a Banach space with the norm , we denote the space of -valued measurable functions on the interval by , whose norm is defined by

    Likewise, we denote by (and by ) the space of continuous functions (resp. -times continuously differentiable functions) from into .

    Subject to the definition by Temam[35], we say, for a fixed parameter , a -periodic function

    which is expanded in the Fourier series, belongs to the Sobolev space when it satisfies

    Due to the definition of the Fourier series, the Fourier coefficients of a function are defined by

    Note that in case , the norm above is equal to the usual Sobolev norm

    We also introduce the notation to denote a set of functions defined on , which are infinitely smoothly differentiable with respect to both and . Let us introduce the following notations:

    where is an arbitrary number. In addition, we use notations and for brevity. Hereafter, 's represent constants in the estimate of some quantities. When we denote with suffixes, it depends on . For simplicity, we hereafter use notations for a function in general.

    First, we state the existence and uniqueness of the local-in-time solution to problem (2.3).

    Theorem 4.1. Let us assume , and the following issues:

    (ⅰ) is -periodic, and satisfies ;

    (ⅱ) ;

    (ⅲ);

    (ⅳ) ;

    () satisfies , ;

    () .

    Then, there exists a certain and a solution to (2.3) on such that

    where

    Before proceeding to the proof of Theorem 4.1, we prepare the following lemmas.

    Lemma 4.2. Let be a function satisfying in general. Then, the following estimates hold:

    (ⅰ) If and for each , then

    (ⅱ)

    (ⅲ)

    Proof. Here we only show the proof of (ⅱ). By virtue of the Schwarz inequality, we have

    The estimate (ⅲ) is obtained in a similar manner, and statement (ⅰ) is obtained easily.

    Hereafter, for arbitrary , we use the notation

    Lemma 4.3. For an arbitrary , if there exists a solution to (2.3) that belongs to , then the following issues hold:

    (ⅰ)

    (ⅱ)

    Remark 2. If in Theorem 4.1 is large enough (), then the first statement in Theorem 4.1 holds in the pointwise sense due to the Sobolev's embedding theorem and maximum principle (see[11]).

    Proof. We verify the statement by using the Stampacchia's truncation method. Let us define

    It is obvious that and stand for the positive and negative parts of , respectively, satisfying . Then, by multiplying (2.3) by and integrating over , we obtain

    Here we used the estimate:

    which is derived by integration by parts and Lemma 4.2. Taking into account we arrive at on by virtue of the Gronwall's inequality. This implies the first statement. The second one is proved by direct calculation (see, [24]), and we omit the proof.

    We carry out the proof of Theorem 4.1 in three steps below.

    (ⅰ) Existence of a solution that belongs to on a certain time interval ;

    (ⅱ) proof of , and consequently ;

    (ⅲ) uniqueness of the solution in .

    We apply the semi-discrete approximation used by Sjöberg[32] and Tsutsumi[36] for the study of the KdV equation. Let us take , , and denote as and the difference operators defined by

    Now, instead of problem (2.3), we consider the following differential-difference equation:

    (4.1)

    where

    Note that this function is defined on the continuous interval with respect to

    By virtue of the estimate (4.9) we will verify later, it is clear that problem (4.1) above has a unique solution for every . Then we derive some bounds for and its differences, which are uniform with respect to . To do that, in the space of grid-functions we define the scalar product and the norm by

    respectively. As Sjöberg[32] and Tsutsumi[36] did, we assume with , and then

    forms an orthonormal basis with respect to the scalar products and .

    The following lemmas are due to the work by Sjöberg[32] and Tsutsumi[36]; thus, we omit the proof here.

    Lemma 4.4. If is a real -periodic grid-function, i.e., if , and if is another real -periodic grid-function, then the following equalities hold:

    (4.2)
    (4.3)

    Lemma 4.5.  Let and be non-negative integers with , and , a function of the form

    Then,

    holds with some constants

    For the proof of Lemma 4.5, see Lemma 2.2 in the work by Sjöberg[32]. In addition, the following lemma is useful.

    Lemma 4.6. Let , and be the discrete Fourier series of , that is,

    with Then, the discrete version of the Parseval type equality

    holds for non-negative integers and .

    Proof. We first verify the statement when In fact, since

    noting that

    (4.4)

    where is the Kronecker's delta, we have

    On the other hand, since

    we have

    Accordingly, by noting (4.4) again, we have

    Finally, the statement holds in case , since is the Fourier series of . We verify this for for simplicity. In fact, by definition,

    (4.5)

    On the other hand,

    However, it is easy to see that this equals the rightmost-hand side of (4.5); therefore, is the discrete Fourier series of For other pairs of , we are able to show the desired statement in the similar manners.

    On the basis of Lemma 4.6, we derive some estimates of and its differences.

    Lemma 4.7. The following estimates hold:

    where and are positive constants independent on , and .

    Proof. Let us multiply (4.1) by . Then, by virtue of Lemma 4.2, we have

    (4.6)

    Making use of

    for two real -periodic grid-functions and in general, where , we have

    where is a certain positive constant, and , a constant dependent on (hereafter we use these notations in the same meaning). Here we have used the estimates

    and by means of the mean value theorem and Schwarz's inequality,

    (4.7)

    where . In addition, we have used the Young's inequality

    where we take Thus, taking the supremum with respect to in (4.6), we arrive at

    By virtue of the comparison theorem, is estimated from above by the solution of the ordinary differential equation

    which has a solution on with some , and satisfies the estimate of the form

    (4.8)

    with a constant independent on . Next, we multiply (4.1) by . With the aid of (4.2)-(4.3), we show some of the elementary calculations below:

    Combining these, we have

    By taking sufficiently small, and due to estimate (4.8) we have already obtained, we derive

    which yields

    for due to the preceding discussion.

    Similarly, multiplying (4.1) by leads to

    We expand the last term in the left-hand side as

    Each term is estimated as follows.

    Here we applied a similar estimate as (4.7). Thus, by using (4.8) we have the estimate of the form

    which yields the boundedness of on . In a similar manner, we obtain the estimates of higher difference terms with respect to .

    When , by virtue of Lemma 4.5, we easily obtain

    (4.9)

    under the assumptions of Theorem 4.1. Then, as Sjöberg[32] and Tsutsumi[36] did, we consider the discrete Fourier series of , which is denoted as :

    Estimate (4.9) and Lemmas 4.5-4.7 yield that the sequence of functions is uniformly bounded and equicontinuous on , . With the aid of the Arzera-Ascoli theorem, we see that contains a subsequence which converges to a certain function as . In addition, it is clear that

    in for each . Therefore, this is the desired solution to (4.1).

    Finally, we discuss the regularity of with respect to . Let us define

    which clearly satisfy

    Thus, under the assumptions of Theorem 4.1, we can show that

    with respect to for each and in the same line with the arguments by Lavrentiev[24]. The same argument holds concerning the regularity with respect to , and we finally arrive at the desired regularity of .

    Before proceeding to the uniqueness part, we mention that the solution that was guaranteed to exist in the previous process also belongs to thanks to Lemma 4.3, and consequently, to This is directly obtained from Lemma 4.3.

    Finally, we discuss the uniqueness part of the statement. Assume that there exist two solutions to (2.3) on with the same initial data, and let us define

    Then, it satisfies:

    (4.10)

    We multiply (4.10) by . Then, integration by parts yields

    These yield

    By virtue of the Gronwall's inequality and the initial condition (4.10), we have

    which indicates the uniqueness of the solution in the desired function space.

    Now we discuss the global-in-time solvability of (2.3). Let be provided, which satisfies the assumption (ⅵ) in Theorem 4.1. In accordance with Theorem 4.1, we first construct the local-in-time solution on , where is the time provided in that theorem. Then, we have the a-priori estimate.

    Lemma 4.8. Let be an arbitrary number. If there exists a solution to 2.3 on , estimates of the form

    (4.11)

    hold with certain constants independent of .

    Proof. For the sake of simplicity, we introduce the notation and derive the estimate of its norm which leads to the desired estimates. From (2.3), it is obvious that satisfies

    (4.12)

    Multiply (4.12) by , and making use of Lemma 4.2 and the periodicity of with respect to yields

    On the other hand, in the same line as the arguments by Lavrentiev[24], we have

    where we have applied the Young's inequality in the last inequality.

    Thus, after taking the supremum with respect to , we have the estimate of the form

    (4.13)

    Therefore, if we take so small that holds, then by virtue of the classical Gronwall's inequality, we have the estimate of the form (see, for instance, p.85 of[35])

    (4.14)

    Next, we show the estimate of , which satisfies

    Then, due to the estimates

    and the Young's inequality, and taking the supremum with respect to and , we have the estimate of the form

    (4.15)

    with constants . Now we divide the second term in the left-hand side of (4.13) into two terms by using a small constant , and apply the Poincaré's inequality

    to the first term:

    Then, we obtain

    Summing up this and (4.15) multiplied by a positive constant , which will be specified later, we have

    Therefore, we take , and in the following manner:

    (ⅰ) Take and so that holds;

    (ⅱ) Then, take so small that

    hold.

    Then, in the same line with the deduction of (4.14), we have

    (4.16)

    Similarly, for we have the estimate of the form:

    (4.17)

    For estimates of , we introduce the Friedrichs mollifier with respect to [28], and define

    with a constant We also define

    for functions in general. Note that when they are defined on , we extend them onto preserving the regularity[23].

    Now, by operating to (4.12), we have

    (4.18)

    where

    Operating to (4.18) yields

    (4.19)

    Hereafter we use the notation to denote the binomial coefficient of l choose i.

    Then, we multiply (4.19) by , and with the similar process as above, obtain the estimate

    (4.20)

    with constants By noting , we obtain the following estimate from (4.20) by letting tend to zero:

    (4.21)

    We now multiply each estimate for in (4.15), (4.17) and (4.21) by a positive constant , which will be specified later, and sum up them. We also introduce for simplicity. These yield

    It should be noted that a straightforward estimate, like that by Ha and Xiao[11] will require to be monotonically and increasingly dependent on . Instead, we partially apply the Poincaré's inequality as before:

    (4.22)

    We take , and as follows.

    (ⅰ) Take and so that hold;

    (ⅱ) Take so small that

    hold;

    (ⅲ) Take so small that

    hold;

    (ⅳ) As for , take them so small inductively that:

    hold;

    (ⅴ) Finally, take so small that

    hold.

    Thus, (4.22) becomes

    where the coefficients of each term in the left-hand side are all positive. Thus, as we have obtained (4.14) and (4.16), the Gronwall's inequality again yields

    Now, by virtue of Lemma 4.8, satisfies the assumption (ⅵ) in Theorem 4.1 imposed on . Thereby, we are able to extend over the time interval as a solution to (2.3). This solution, which is now defined over , again satisfies the estimate (4.11), and we then extend it over the region . Iterating this procedure sufficiently many times, we are able to obtain the solution over the time interval for arbitrary We summarize these arguments as follows.

    Theorem 4.9. Let be an arbitrary positive number. Then, under the same assumptions as in Theorem 4.1, there exists a solution to 2.3 on .

    Remark 3. From these considerations, it is obvious that Theorem 4.9 holds when is compactly supported. we can also extend these arguments when is the Dirac's delta function, i.e. , since Lemma 4.2 holds in that case.

    Corollary 4.10. Under the assumptions in Theorem 4.1 with (ⅳ) replaced by , the same statement as in Theorem 4.9 holds.

    In this section, we discuss the nonlinear stability of the trivial stationary solution . As in the proof of Lemma 4.8, we introduce the notation and derive the estimate of its norm with respect to time.

    The asymptotic stability of reads

    Theorem 5.1. In addition to the assumptions in Theorem 4.1, we assume

    Then, is asymptotically stable in and satisfies the inequality

    with certain positive constants .

    Proof. The line of the argument is similar to that of Lemma 4.8, but this time we have to confirm the non-positiveness of the left-hand side of the energy type inequalities. First, let us multiply (4.12) by . By making use of Lemma 4.2, we have the estimate:

    Thus, we have the energy estimate

    (5.1)

    For the estimate of only, if holds, with the aid of the Poincaré's inequality, we have

    which leads to the estimate of the form

    (5.2)

    by virtue of the Gronwall's inequality. Estimate (5.2) implies the asymptotic stability of in

    Next, we show the estimate up to the first-order spatial derivative. First, by applying the Poincaré's inequality to the second term of the left-hand side in (5.1) partially, as in the previous section, we have

    (5.3)

    Then, let us sum up (5.3) and (4.15), and we have

    (5.4)

    As in the previous section, we take and in the following manner:

    (ⅰ) Take so small that holds;

    (ⅱ) Then, take so small that

    hold.

    By applying the Gronwall's inequality to (5.4), these lead to the estimate of the form

    that is, the asymptotic stability of holds in

    Similarly, we make use of (4.17) and (4.21) to deduce

    (5.5)
    (5.6)

    Summing up (5.3), (5.5) and (5.6) multiplied by constants with , we arrive at

    Now, we determine and as follows.

    (ⅰ) Take so small that ;

    (ⅱ) Take so small that

    hold;

    (ⅲ) Take so small that

    hold;

    (ⅵ) As for , take them so small inductively that:

    hold;

    (ⅴ) Finally, take so small that

    hold.

    These yield the estimate of the form

    which directly leads to the desired statement.

    Remark 4. For the original Kuramoto-Sakaguchi equation (1.6), Ha[11] deduced a similar result concerning the asymptotic stability of . On the basis of some regularity and decay of with respect to , they estimated the norm with weight with respect to . Their arguments are based on the energy method, which is similar to the one presented here. The advantage of our method is to make the estimate sharper by dividing the terms of a higher derivative into two terms before applying the Poincaré's inequality. Indeed, as we have mentioned before, we need monotonically increasing with respect to with the procedure used by Ha and Xiao[11]. As we mentioned in Section 2, the original Kuramoto model (1.3) (or (1.6)) can be regarded as a specific case of the non-local coupling model (2.2) (resp. (2.3))[20]. Therefore, the stability of the incoherent state in (1.6) is verified through similar arguments and assumptions in Theorem 4.1 (see also[13]).

    Finally, we discuss the vanishing limit of the diffusion coefficient. In order to show the dependency of the solution on the diffusion coefficient clearly, we denote the solution of (2.3) as , whereas that of (2.5) is denoted as As we have stated, Ha and Xiao[11] held a similar discussion for the original Kuramoto-Sakaguchi equation (1.6). However, they estimated the norm of by using the polynomial of , which resulted in the convergence in with respect to . In the discussion below, we apply the compactness argument for deriving higher order convergence than their result. This method is also applicable to the original Kuramoto-Sakaguchi equation[13]. We first prepare some lemmas below.

    Lemma 6.1. Let be an arbitrary number. Then, the sequence is uniformly bounded with respect to in .

    Proof. What we have to verify are

    (6.1)
    (6.2)

    with some constants and dependent on . For , we have already verified (6.1) in the previous section.

    Now we provide the estimates of the temporal derivative of inductively. Let us assume that the boundedness of has been proven for Then, by noting

    and Lemma 4.2, we have the estimate of the form

    (6.3)

    where are the positive constants. By virtue of the assumption of the induction and the Gronwall's inequality, we then have the estimate of the form

    (6.4)

    As for , we use the mollifier again. Recalling the notation defined in Section 4, we consider

    (6.5)

    where and

    We operate the temporal derivative to (6.5) and obtain

    (6.6)

    Then, after the energy type estimate, we make tend to zero. By making use of the fact

    we obtain (6.4) with with the aid of the assumptions of the induction.

    Next, we estimate the term including both temporal and spatial derivatives. We only show the case , when the mollifier is necessary again. By applying the -th order spatial derivative to (6.6) with replaced with , we have

    (6.7)

    Now we show some examples of the energy type estimates. In case , we have

    For , we have

    Otherwise, we have

    By combining these and (6.7), and applying the Young's and Schwarz's inequalities, we derive the energy estimate of the form

    (6.8)

    After making and applying the Gronwall's inequality, we have the estimate of the form

    Thus, we have shown the first part of the statement. Estimate (6.2) is derived from (6.3), (6.8), and the estimates we have already obtained. These complete the proof.

    By virtue of Lemma 6.1, we see that the sequence includes a sub-sequence, denoted as again, which is convergent in the weak-star sense as tends to zero:

    (6.9)
    (6.10)

    Then, in the relationship

    if we make tend to zero, we have

    which means .

    The next lemma clarifies the space to which this sequence converges.

    Lemma 6.2. Let be an arbitrary number. Then, the sequence forms the Cauchy sequence in .

    Proof. Let us define for arbitrary , , which satisfies

    Then, with the aid of the estimates

    we have

    Thus, by virtue of the Gronwall's inequality and the fact that , we have the estimate of the form

    This implies that the sequence is the Cauchy sequence in The estimates of higher derivative terms are obtained in a similar manner. To show this, we subtract (6.7) with replaced with a certain from itself and obtain

    where , and

    We show inductively that hold as and tend to zero based on the assumption that form the Cauchy sequences with and . Let us show some examples of the estimates. In case , we have

    In case , we have

    Otherwise, we have

    After applying the Schwarz's inequality, we make tend to zero. Then, on the basis of the assumption of the induction, we have the estimate of the form:

    where as and tend to zero.

    From these considerations, the sequence forms the Cauchy sequence in . This completes the proof of Lemma 6.2.

    By Lemma 6.2, we see that belongs to . Now, we show that certainly satisfies (2.5). To do this, we take an arbitrary function satisfying , , and consider

    (6.11)

    In virtue of (6.9)-(6.10), if we make tend to zero,

    On the other hand, thanks to the Rellich's theorem[27], we have

    strongly as ; therefore,

    holds. Thus, we arrive at

    (6.12)

    which means that certainly satisfies (2.5). Next, integrate (6.11) and (6.12) by part with respect to , and the assumptions on yield

    (6.13)
    (6.14)

    respectively. Comparing (6.13) and (6.14) with the aid of (6.9)-(6.10) implies , and so the initial condition (2.5) is satisfied. The periodicity (2.5) obviously holds due to the function space to which belongs. Thus, . We summarize these arguments as follows.

    Theorem 6.3. Let be an arbitrary number, and impose the same assumptions as in Theorem 4.1. Then, the solution of (2.3) converges to that of (2.5) in , which is denoted as , as tends to zero.

    In this paper, we discussed the mathematical analysis of the nonlinear Fokker-Planck equation of Kuramoto's non-local coupling model of oscillators. We first showed the local and global-in-time solvability, and then the nonlinear asymptotic stability of the incoherent state. Finally, we verified the existence of the vanishing diffusion limit solution as the diffusion coefficient tends to zero.

    Our future work will be concerned with the mathematical stability analysis of the chimera state of this model and the coupled oscillator model on the complex graph. We will also tackle the bifurcation problem.



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