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Research article Special Issues

Analytical findings on bilinear fractional Hardy operators in weighted central Morrey spaces with variable exponents

  • Received: 11 February 2025 Revised: 17 April 2025 Accepted: 21 April 2025 Published: 07 May 2025
  • MSC : 42B35, 26D10, 47B38, 47G10

  • This paper demonstrates the boundedness of the fractional bilinear Hardy operator and its adjoint on weighted λ-central Morrey spaces with a variable exponent. Analogous outcomes for their commutators were derived when the symbol functions are elements of the weighted λ-central bounded mean oscillation (λ-central BMO) spaces.

    Citation: Muhammad Asim, Ghada AlNemer. Analytical findings on bilinear fractional Hardy operators in weighted central Morrey spaces with variable exponents[J]. AIMS Mathematics, 2025, 10(5): 10431-10451. doi: 10.3934/math.2025475

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  • This paper demonstrates the boundedness of the fractional bilinear Hardy operator and its adjoint on weighted λ-central Morrey spaces with a variable exponent. Analogous outcomes for their commutators were derived when the symbol functions are elements of the weighted λ-central bounded mean oscillation (λ-central BMO) spaces.



    In mathematics and various sciences, the changes of output and input of nonlinear systems are out of proportion. Most of the systems involved in life are essentially nonlinear, so solving nonlinear problems has attracted various scientists. Scholars have proposed more efficient iterative methods for solving nonlinear systems. One of the most famous iterative methods for solving nonlinear systems is Newton's method [1],

    x(k+1) =x(k)[F(x(k))]1F(x(k)), (1.1)

    for k=0,1,2,..., x0 is the starting point. The Newton's method is second order convergent and effective in solving some nonlinear systems.

    With the advancement of computers and numerical algebra, scholars have developed many iterative methods based on Newton's method that are more efficient than second-order Newton's method for solving nonlinear problems [2,3,4,5,6,7]. In addition, when the Jacobian matrix cannot be calculated for nonlinear systems, some effective derivative free methods can also solve nonlinear systems well (see [8,9,10,11,12]). We propose an eighth order iterative method with high computational efficiency, which is suitable for solving large systems of equations [13]. The specific iteration format is as follows

    {y(k) =x(k)ΓkF(x(k)),w(k)=y(k)[I+(I+54M(k))M(k)]ΓkF(y(k)),x(k+1)=w(k)[I+(I+32M(k))M(k)]ΓkF(w(k)), (1.2)

    where M(k)=Γk(F(x(k))F(y(k))), and Γk=[F(x(k))]1.

    The theoretical results of local convergence and semilocal convergence of the iterative method are also important in the study. Local convergence requires the existence of the assumed solution and the initial value is close enough to the solution. Semilocal convergence does not require the existence of an assumed solution, but the selection of initial values also needs to meet certain conditions (see [14,15,16,17,18]). Therefore, for some systems that cannot be analyzed and solved, the results of semilocal convergence cannot only prove the convergence of iterative sequences, but also prove the existence of solutions of these systems, so as to obtain the existence domain and uniqueness domain of system solutions; for further study (see [19,20,21,22]). Based on this, we perform a semilocal convergence analysis on the method (1.2) .

    This paper consists of five sections. In Section 2 of the paper, the recurrence relation is explained. The semilocal convergence of the iterative method (1.2) is proved in Section 3. In Section 4, the numerical experiments of two nonlinear systems are completed. Finally, the conclusion of this paper is made.

    In this section, let X and Y be Banach spaces and let F:ΩXY be a twice differetiable nonlinear Fréchet operator in an open Ω [23]. Let us assume that the inverse of the Jacobian matrix of the system in the iteration (1.2) is Γ0L(Y,X), which is the set of linear operation from Y to X.

    Moreover, in order to obtain the semilocal convergence result for this iterative method (1.2) , Kantorovich conditions are assumed:

    (M1)Γ0β,

    (M2)Γ0F(x0)η,

    (M3)F(x)F(y)Kxy,

    where K, β, η are non-negative real numbers. For the sake of simplicity, we denote a0=Kβη and define the sequence

    ak+1=akf(ak)2g(ak), (2.1)

    where we use the following auxiliary functions

    h(x)=1256(256+256x+384x2+640x3+576x4+576x5+528x6+298x7+170x8+75x9), (2.2)
    f(x)=11xh(x), (2.3)

    and

    g(x)=x131072(196608+327680x+589824x2+819200x3+1064960x4+1351680x5+1569792x6+1689600x7+1752576x8+1693696x9+1490432x10+1226752x11+913920x12+596928x13+354724x14+180520x15+73600x16+25500x17+5625x18). (2.4)

    These functions play a key role in the analysis that will be performed next.

    Preliminary results. In order to get the difference of the first two elements in the iterative method (1.2) , we have

    w0x0=y0x0[I+(I+54Γ0(F(x0)F(y0)))Γ0(F(x0)F(y0))]Γ0F(y0). (2.5)

    The Taylor series expansion of F around x0 evaluated in y0 is

    F(y0)=F(x0)+F(x0)(y0x0)+y0x0(F(x)F(x0))dx, (2.6)

    where the term F(x0)+F(x0)(y0x0) is equal to zero, since it comes from a Newton's step. With the change x=x0+t(y0x0), we get

    F(y0)=10(F(x0+t(y0x0))F(x0))(y0x0)dt. (2.7)

    Then,

    w0x0=y0x0(I+Γ0(F(x0)F(y0))+54Γ0(F(x0)F(y0))Γ0(F(x0)F(y0)))Γ0F(y0)=y0x0(Γ0F(y0)+Γ0(F(x0)F(y0))Γ0F(y0)+54Γ0(F(x0)F(y0))Γ0(F(x0)F(y0))Γ0F(y0))=y0x0(Γ010(F(x0+t(y0x0))F(x0))(y0x0)dt+Γ0(F(x0)F(y0))Γ010(F(x0+t(y0x0))F(x0))(y0x0)dt+54Γ0(F(x0)F(y0))Γ0(F(x0)F(y0))×Γ010(F(x0+t(y0x0))F(x0))(y0x0)dt). (2.8)

    Taking norms and applying Lipschitz condition, we get

    w0x0y0x0+K2Γ0y0x02+K22Γ0y0x0Γ0y0x02+5K38Γ0y0x0Γ0y0x0Γ0y0x02η+12Kβη2+12K2β2η3+58K3β3η4=η(1+12a0+12a20+58a30), (2.9)

    so that,

    w0x0η(1+12(a0+a20+54a30)). (2.10)

    Using a method similar to (2.5), we get w0y0

    w0y0=y0y0[I+(I+54Γ0(F(x0)F(y0)))Γ0(F(x0)F(y0))]Γ0F(y0). (2.11)

    So,

    w0y0y0y0+K2Γ0y0x02+K22Γ0y0x0Γ0y0x02+5K38Γ0y0x0Γ0y0x0Γ0y0x0212Kβη2+12K2β2η3+58K3β3η4=η(12a0+12a20+58a30). (2.12)

    Next, the next step analysis

    x1x0=w0x0[I+(I+32Γ0(F(x0)F(y0)))Γ0(F(x0)F(y0))]Γ0F(w0). (2.13)

    Using Taylor's expansion of F(w0) around x0 and applying Lipschitz condition, we obtain

    x1x0w0x0+K2Γ0w0x02+K22Γ0y0x0Γ0w0x02+3K34Γ0y0x0Γ0y0x0Γ0w0x02η(1+12(a0+a20+54a30))+Kβη22(1+12(a0+a20+54a30))2+K2β2η32(1+12(a0+a20+54a30))2+3K3β3η44(1+12(a0+a20+54a30))2=η((1+12(a0+a20+54a30))+a02(1+12(a0+a20+54a30))2+a202(1+12(a0+a20+54a30))2+3a304(1+12(a0+a20+54a30))2)=η(1256(256+256a0+384a20+640a30+576a40+576a50+528a60+298a70+170a80+75a90)). (2.14)

    By applying Banach's lemma, one has

    IΓ0F(x1)=Γ0F(x0)Γ0F(x1)=Γ0F(x0)Γ0F(x1)Kβx1x0Kβη(1256(256+256a0+384a20+640a30+576a40+576a50+528a60+298a70+170a80+75a90))=a0(h(a0))<1, (2.15)

    where

    h(x)=1256(256+256x+384x2+640x3+576x4+576x5+528x6+298x7+170x8+75x9).

    Then, as far as a0(h(a0))<1 (by taking a0<0.45807), Banach's lemma guarantees that

    (Γ0F(x1))1=Γ1Γ10

    exists and

    Γ111a0(h(a0))Γ0=f(a0)Γ0, (2.16)

    so

    f(x)=111256(256+256x+384x2+640x3+576x4+576x5+528x6+298x7+170x8+75x9).

    Based on the above analysis, we can obtain the following theorem.

    Theorem 1. For k1, the following conditions are valid:

    (O1k)Γkf(ak1)Γk1,

    (O2k)ykxk=ΓkF(xk)f(ak1)g(ak1)yk1xk1,

    (O3k)KΓkykxkak,

    (O4k)xkxk1h(ak1)yk1xk1.

    Proof. The above theorem is proven through induction. Starting with k=1, (2.16) proved the (O11).

    (O21): The Taylor's expansion of F(x1) around y0, we can get

    F(x1)=F(y0)+F(y0)(x1y0)+x1y0(F(x)F(y0))dx=F(y0)+(F(y0)F(x0))(x1y0)+F(x0)(x1y0)+10(F(y0+t(x1y0))F(y0))(x1y0)dt. (2.17)

    So, we must to have x1y0

    x1y0=w0y0[I+(I+32Γ0(F(x0)F(y0)))Γ0(F(x0)F(y0))]Γ0F(w0). (2.18)

    And bounding its norm, the following inequality is obtained

    x1y0w0y0+K2Γ0w0x02+K22Γ0y0x0Γ0w0x02+3K34Γ0y0x0Γ0y0x0Γ0w0x02η(12a0+12a20+58a30)+Kβη22(1+12(a0+a20+54a30))2+K2β2η32(1+12(a0+a20+54a30))2+3K3β3η44(1+12(a0+a20+54a30))2η(1256(256+384a0+640a20+576a30+576a40+528a50+298a60+170a70+75a80)). (2.19)

    Then, using (2.17)–(2.19), the F(x1) is bounded

    F(x1)12Kη2+Kη2(1256(256+384a0+640a20+576a30+576a40+528a50+298a60+170a70+75a80))+1βη(1256(256+384a0+640a20+576a30+576a40+528a50+298a60+170a70+75a80))+12Kη2(1256(256+384a0+640a20+576a30+576a40+528a50+298a60+170a70+75a80))2. (2.20)

    Therefore, by applying (O11), we get

    y1x1=Γ1F(x1)=f(a0)Γ0F(x1)f(a0)[1131072a0(196608+327680a0+589824a20+819200a30+1064960a40+1351680a50+1569792a60+1689600a70+1752576a80+1693696a90+1490432a100+1226752a110+913920a120+596928a130+354724a140+180520a150+73600a160+25500a170+5625a180)]η. (2.21)

    That is,

    y1x1=f(a0)g(a0)ηf(a0)g(a0)y0x0,

    where,

    g(x)=x131072(196608+327680x+589824x2+819200x3+1064960x4+1351680x5+1569792x6+1689600x7+1752576x8+1693696x9+1490432x10+1226752x11+913920x12+596928x13+354724x14+180520x15+73600x16+25500x17+5625x18).

    (O31): Using (O11) and (O21),

    KΓ1y1x1Kf(a0)Γ0f(a0)g(a0)y0x0=a0f(a0)2g(a0)=a1.

    (O41): For k=1 it has been proven in (2.16).

    The proof of (O1k+1), (O2k+1), (O3k+1) and (O4k+1) is based on the same method of proving that the inductive assumption with (O1k), (O2k), (O3k) and (O4k) as k1 holds true.

    According to the convergence property of xk sequence in Banach space, we need to prove that this sequence is a Cauchy sequence. Based on the auxiliary function, we can obtain the following results.

    Lemma 1. According h(x),f(x) and g(x), we have:

    i. f(x) is inceasing and f(x)>1 for x(0,0.45807),

    ii. h(x) and g(x) are increasing for x(0,0.45807).

    The above lemma can be calculated from the Section 2, and the process is omitted.

    Lemma 2. The f(x) and g(x) defined by (2.3) and (2.4). Then

    i. f(a0)g(a0)<1 for a0<0.252232,

    ii. f(a0)2g(a0)<1 for a0<0.21715,

    iii. the sequence ak is decreasing and ak<0.21715 for k>0.

    Proof. It is straightforword that i, ii are satisfied. As f(a0)2g(a0)<1, then by construction of ak, it is a dereasing sequence. So ak<a00.21715, for all k1.

    Theorem 2. Let X, Y be Banach spaces and F:ΩXY be a nonlinear twice differentiable Fréchet operator in an open set domain Ω. Assume that Γ0=[F(x0)]1 exists in x0Ω and meet the conditions of (M1)(M3). Let be a0=Kβη, and assume that a0<0.21. The sequence {xk} defined in (2.1) and starting in x0 converges to the solution x of F(x)=0, if Be(x0,Rη)=xX:xx0<RηΩ where R=h(a0)1f(a0)g(a0). In the case, the iterates {xk} and {yk} are contained in Be(x0,Rη) and xBe(x0,Rη). In addition, the x is the only solution of equation F(x)=0 in Bn(x0,2KβRη)Ω.

    Proof. By recursively applying (O4k), we can write

    xk+1xkh(ak)ykxkh(ak)f(ak1)g(ak1)yk1xk1h(ak)[k1i=0f(ai)g(ai)]y0x0. (3.1)

    Then,

    xk+mxkxk+mxk+m1+xk+m1xk+m2++xk+1xkh(ak+m1)ηk+m2i=0f(ai)g(ai)+h(ak+m2)ηk+m3i=0f(ai)g(ai)++h(ak)ηk1i=0f(ai)g(ai). (3.2)

    As h(x) is increasing and ak dreasing, it can be stated that

    xk+mxkh(ak)ηm1l=0[k+l1i=0f(ai)g(ai)]h(ak)ηm1l=0(f(a0)g(a0))l+k. (3.3)

    Moreover, according Lemmas 1 and 2, by using the expression for the partial sum of a geometrical series,

    xk+mxkh(ak)1(f(a0)g(a0))m1f(a0)g(a0)(f(a0)g(a0))kη. (3.4)

    So, the Cauchy sequence if and only if f(a0)g(a0)<1 (Lemma 2).

    For k=0,

    xmx0xmxm1+xm1xm2++x1x0h(a0)y0x0m1r=0(f(a0)g(a0))r.=h(a0)1(f(a0)g(a0))m1f(a0)g(a0)η<Rη, (3.5)

    when m, we get the radius od convergence Rη=h(a0)1f(a0)g(a0)η.

    Let's prove that x is the solution of F(x)=0 starting from the boundary of F(xn),

    F(xk)F(x0)+F(xk)F(x0)F(x0)+Kxkx0F(x0)+KRη. (3.6)

    Then, acorrding M2 and (3.1)

    F(xk)F(xk)ykxkF(xk)h(ak)[n1i=0f(ai)g(ai)]η, (3.7)

    as h(x), f(x) and g(x) are increasing and ak is the decreasing sequence,

    F(xk)F(xk)h(ak)(f(a0)g(a0))kη. (3.8)

    Taking into account that F(xk) is bounded and (f(a0)g(a0))k tends to zero when k, we conclude that F(xk)0. As F is continuous in Ω, then F(x)=0.

    Finally, the uniqueness of x in B(x0,2KβRη)Ω.

    0=F(y)F(x)=(F(x)+10F(x+t(yx))(yx)dt)(F(x)=(yx)10F(x+t(yx))dt). (3.9)

    In order to guarantee that yx=0 it is necesssary to prove that operator 10F(x+t(yx))dt is invertible. Applying hypothesis (M3),

    Γ010F(x+t(yx))F(x0)dtKβ10x+t(yx)x0dtKβ10((1t)xx0+tyx0)dt<Kβ2(Rη+2KβRη)=1. (3.10)

    By the Banach lemma, the intergal operator is invertible and hence y=x.

    In this section, we provide some numerical examples to illustrate the theoretical results introduced earlier.

    Example 1. Hammerstein equation is a kind of important nonlinear integral equation [24], which is given as follows:

    x(s)=1+(1/5)10N(s,t)x(t)3dt, (4.1)

    where xC[0,1],s,t[0,1], with the kernel N is

    N(s,t)={(1s)tts,s(1t)st.

    To solve (4.1) we transform it into a syste of nonlinear equations through a discretization process. We approximate the integral appearing in Eq (4.1) by using Gauss-Legendre quadrature,

    10s(t)dt7i=1wjs(tj),

    being tj and wj the nodes and the weights of the Gauss-Legendre polynomial. Denoting the approximation of x(tj) as xi,i=1,...,7, then we estimate (4.1) with the nonlinear system of equations

    xi1157j=1aijx3j=0,i=1,...,7 (4.2)

    where

    aij={wjtj(1ti)ji,wjti(1tj)i<j.

    So, the system can be rewritten as

    F(x)=x115Avx,vx=(x31,x32,...,x37)T,
    F(x)=I35AD(x),D(x)=diag(x21,x22,...,x27),

    where F if a nonlinear operator in the Banach space RL, and F is its Fréchet derivative in L(RL,RL).

    According the method (1.2), we will use it to solve the nonlinear systems.

    Taking x0=(1.8,1.8,...,1.8)T,L=7 and the infinity norm, we get

    Γ0β,β1.2559,Γ0F(x0)η,η2.2062,F(x)F(y)kxy,k0.0671,a0=kβη,0.1860. (4.3)

    The above results satisfy the semilocal convergence condition, so this method can be applied to the system. Thus, we guarantee the existence of the solution in Be(x0,0.5646), and the uniqueness in Bn(x0,22.4874). Table 1 shows the the radius of the existence domain and the radius of the unique domain under different initial values. For x0i>1.87,i=1,2,...,7, convergence conditions are not satisfied and, therefore, the convergence is not guaranteed.

    Table 1.  Different initial values related parameters.
    x0i β η k a0 Re Rn
    0.2 1.0025 2.1204 0.0287 0.0610 0.0754 69.3528
    0.4 1.0102 1.6005 0.0337 0.0545 0.0657 58.6428
    0.6 1.0232 1.0827 0.0390 0.0433 0.0500 50.0651
    0.8 1.0420 0.5637 0.0451 0.0265 0.0288 42.5422
    1.0 1.0671 0.0461 0.0682 0.0034 0.0034 27.4813
    1.2 1.0996 0.4949 0.0505 0.0275 0.0300 36.0019
    1.4 1.1406 1.0420 0.0569 0.0676 0.0859 30.7271
    1.6 1.1919 1.6098 0.0622 0.1193 0.1970 26.6603
    1.7 1.2222 1.9038 0.0647 0.1505 0.3107 24.7005

     | Show Table
    DownLoad: CSV

    Using the iterative method (1.2) to solve (4.2), the exact solution is

    x=(1.003,1.012,1.023,1.028,1.023,1.012,1.003)T.

    Example 2. Let X=Y=R2 be equipped with the max-norm. Choose: x0=(0.9,0.9)T, s[0,12). Let s=0.49, define function F by

    F(x)=(x31s,x32s)T,x=(x1,x2)T. (4.4)

    The fréchet-derivative of operator F is given by

    F(x)=[3x21003x2].

    Taking x0=(0.9,0.9)T and the infinity norm, we get

    Γ0β,β0.4115,Γ0F(x0)η,η0.1391,F(x)F(y)kxy,k3.6113,a0=kβη,0.2067. (4.5)

    The convergence conditions are met and consequently the method can be applied to the system. The existence domain of the solution is Be(x0,0.9101), and the uniqueness domain is Bn(x0,1.2192).

    Taking x0=(0.73,0.73)T and the infinity norm, then

    Γ0β,β0.6255,Γ0F(x0)η,η0.0893,F(x)F(y)kxy,k3.2329,a0=kβη,0.1806. (4.6)

    The existence domain of the solution is Be(x0,0.5095), and the uniqueness domain is Bn(x0,0.943534).

    When the initial value satisfies the Kantorovich condition and the range of a0 obtained, the initial value within that range is taken to solve the system. Iterative method (1.2) for solving nonlinear (4.4) with roots of x=(0.7884,0.7884)T.

    Similar results can be obtained in Tables 2 and 3, that is, under the Kantorovich condition, by selecting different initial values, we can converge to a unique solution. When the initial value is closer to the root, the error estimate is lower. This semilocal convergence that can prove the existence and uniqueness of solutions under certain assumptions is very valuable.

    Table 2.  Numberical results of method (1.2) for nonliner equation.
    x0i iter xkxk1 F(xk)
    0.2 4 7.469e-336 2.149e-2021
    0.4 4 2.538e-352 4.629e-2120
    0.6 4 1.755e-383 8.222e-2307
    0.8 4 5.848e-445 2.318e-2675
    1.0 4 2.629e-701 3.000e-4096
    1.2 4 2.221e-467 5.991e-2809
    1.4 4 1.935e-353 8.489e-2126
    1.6 4 8.010e-286 2.379e-1720
    1.7 4 7.450e-259 1.285e-1558

     | Show Table
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    Table 3.  Numberical results of method (1.2) for nonliner equation.
    x0i iter xkxk1 F(xk) ρ
    0.72 4 4.048e-331 1.878e-2640 8
    0.74 4 2.665e-419 6.432e-3346 8
    0.76 4 1.046e-548 3.726e-4381 8
    0.78 4 2.052e-830 1.000e-6000 8
    0.8 4 2.246e-767 1.000e-6000 8
    0.82 4 2.005e-554 6.803e-4427 8
    0.84 4 1.127e-454 6.768e-3629 8
    0.86 4 9.380e-391 1.559e-3117 8
    0.88 4 1.414e-344 4.163e-2748 8
    0.9 4 5.796e-309 3.313e-2463 8

     | Show Table
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    In this paper, the semilocal convergence of the eighth order iterative method (1.2) is studied. By analyzing the behavior of the iterative method under the Kantorovich condition, the Lipschitz condition is applied to the first derivative, and the theory of semilocal convergence of the iterative method is obtained by using the recurrence relation. The existence and uniqueness domain of the solution of the nonlinear system is obtained. In the experimental part, a classical Hammerstein nonlinear integral equation and a matrix function are solved. The experimental results are consistent with expectations, and the high-precision approximation of the system solution also proves the effectiveness of the method numerically.

    The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.

    This research was supported by the National Natural Science Foundation of China (No. 61976027), the Natural Science Foundation of Liaoning Province (Nos. 2022-MS-371, 2023-MS-296), Educational Commission Foundation of Liaoning Province of China (Nos. LJKMZ20221492, LJKMZ20221498) and the Key Project of Bohai University (No. 0522xn078).

    The authors declare no conflicts of interest.



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