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New convergence analysis of a class of smoothing Newton-type methods for second-order cone complementarity problem

  • In this paper we propose a class of smoothing Newton-type methods for solving the second-order cone complementarity problem (SOCCP). The proposed method design is based on a special regularized Chen-Harker-Kanzow-Smale (CHKS) smoothing function. When the solution set of the SOCCP is nonempty, our method has the following convergence properties: (ⅰ) it generates a bounded iteration sequence; (ⅱ) the value of the merit function converges to zero; (ⅲ) any accumulation point of the generated iteration sequence is a solution of the SOCCP; (ⅳ) it has the local quadratic convergence rate under suitable assumptions. Some numerical results are reported.

    Citation: Li Dong, Jingyong Tang. New convergence analysis of a class of smoothing Newton-type methods for second-order cone complementarity problem[J]. AIMS Mathematics, 2022, 7(9): 17612-17627. doi: 10.3934/math.2022970

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  • In this paper we propose a class of smoothing Newton-type methods for solving the second-order cone complementarity problem (SOCCP). The proposed method design is based on a special regularized Chen-Harker-Kanzow-Smale (CHKS) smoothing function. When the solution set of the SOCCP is nonempty, our method has the following convergence properties: (ⅰ) it generates a bounded iteration sequence; (ⅱ) the value of the merit function converges to zero; (ⅲ) any accumulation point of the generated iteration sequence is a solution of the SOCCP; (ⅳ) it has the local quadratic convergence rate under suitable assumptions. Some numerical results are reported.



    In 1963, Wigner and Yanase introduced the Wigner-Yanase skew information IWY(ρ) of a density matrix ρ in a quantum mechanical system [1] with the definition

    IWY(ρ)=12Tr[[ρ,H]2],

    where ρ is the density matrix (ρ0,trρ=1) and H is a Hermitian matrix. They raised a question: For a positive definite matrix, find whether the value of

    Tr[ρsKρ1sK],

    has convex or concave properties for the matrix function that satisfies the conditions. In fact, trace operator is a useful tool in the mechanical learning; see [2,3,4].

    In 1973, Lieb proved the convexity of the function above for all 0<p<1, known as the Lieb concavity theorem [5], which successfully solved the Wigner-Yanase-Dyson conjecture by using the fact

    Ψ(eiej)=eiej=Iij,

    and the concavity of ρ1sρs [6]. In fact, a more elegant proof of the Lieb concavity theorem appeared in [2] using a tensor product designed by Ando.

    In 2009, Effros gave another proof of the Lieb concavity theorem based on the affine version of the Hansen-Pedersen-Jensen inequality and obtained some celebrated quantum inequalities [7]. After that, Aujla provided a simple proof of this well-known theorem in 2011 using some derived properties of positive semidefinite matrices [3]. Several years later, Nikoufar, Ebadian, and Gordji also gave a simple proof of the Lieb concavity theorem by showing that jointly convex and jointly concave functions hold for generalized perspectives of some elementary functions[8].

    Recently, Huang [9] obtained the function

    L(A,B)=(Tr[k(Aqs2KBspKAsq2)1s])1k,

    as jointly concave for any A,B0, which is a generalization of the Lieb concavity theorem. In our manuscript, we will obtain that the following function is jointly concave for any A,B0, and the nonnegative matrix monotone function f(x)

    G(A,B)=Tr[(f(Aqs2)Kf(Bsp)Kf(Asq2))1s],

    by using Epstein's theorem and some corollary. The rest of the paper is organized as follows. In Section 2, we introduce some definitions and conclusions about matrix tensor product, convexity of matrix, and Epstein¡¯s theorem. With these preparations, we obtain some useful results in the following Section 3 such as the generalization of Lieb concavity theorem.

    For an m×n matrix A and a p×q matrix B, the tensor product of A and B is defined by [10]

    AB:=(a11Ba1nBam1BamnB),

    where A=(aij)1im,1jn, then exterior algebra [11], denoted by "", is a binary operation for any An×n, and the definition is

    (A1A2Akk)(ξi1ξi2ξik)1i1<<ikn=(A1ξi1A2ξi2Akξik)1i1<<ikn,

    where {ξj}nj=1 is an orthonormal basis of Cn and

    ξi1ξi2ξik=1n!πσn(1)πξπ(i1)ξπ(i2)ξπ(ik),

    σn is the family of all permutations on {1,2,,n}. From above, one can obtain the Brunn-Minkowski inequality [12].

    For any A,B>0,

    {Tr[k(A+B)]}1k{Tr[kA]}1k+{Tr[kB]}1k.

    Proof. Let {ξi}ni=1 be the eigenvectors of A+B with the eigenvalue {λi}ni=1, then

    {Tr[k(A+B)]}1k=[1ξi1<<ξiknλi1λik]1k=[1ξi1<<ξikn(det|Pi1,,ik(A+B)Pi1,,ik|)]1k[1ξi1<<ξikn(det|Pi1,,ikAPi1,,ik|+det|Pi1,,ikBPi1,,ik|)]1k[1ξi1<<ξikndet|Pi1,,ikAPi1,,ik|]1k+[1ξi1<<ξikndet|Pi1,,ikBPi1,,ik|]1k={Tr[kA]}1k+{Tr[kB]}1k,

    where Pi1,,ik=(ξi1,,ξik), the first ≥" obtains det(A+B)det(A)+det(B) [13], and the second ≥" obtains by using the that fact Sk=[1ξi1<<ξiknxi1xik]1k is concave [14].

    Associated with the function f(x) (x(0,+)), the matrix function f(A) is defined as [15]

    f(A)=Pf(ΛA)P=i=1f(λi)Pi,

    where f(ΛA):=diag{f(λ1),...,f(λn)} and P2i=Pi. For any A,B are two nonnegative Hermitian matrices, we denote AB if xAxxBx for any xRn, then the matrix monotone function f(x) is defined [4] as

    f(A)f(B)for allAB>0.

    Since the matrix-monotone function is a special kind of operator monotone function, we present the following general conclusions about the operator-monotone function, which can be found in [16].

    The following statements for a real valued continuous function f on (0,+) are equivalent:

    (i)f is operator-monotone;

    (ii)f admits an analytic continuation to the whole domain Imz0 in such a way that ImzImf(z)>0.

    Using Lemma 2.1, one can obtain that f(xp)1p is a matrix monotone function and matrix-concave function for any nonnegative matrix monotone function f(x) and 0<p1 [2].

    The jointly matrix-concave function, is defined as follows [17]:

    f(tA1+(1t)A2,tB1+(1t)B2)tf(A1,B1)+(1t)f(A2,B2), (2.1)

    for all A1,A2,B1,B2H+n, and all t[0,1]. From (2.1) and associated with spectral theory, H. Epstein [18] obtained the following three lammes:

    If ImC=CC2i>0 and 0<α<1, then

    ImeiαπCα<0<ImCα. (2.2)

    This lemma can be obtained from the integral representation [19] of

    Cα=+0(1t1C+t)dμ(t).

    Setting A1,B1Hn, and A2,B2H+n, and A=A1+iA2,B=B1+iB2, if

    ImAα>0,ImBβ>0,ImeiαπAα<0,ImeiβπBβ<0,

    where 0<α,β, straightforward calculations show.

    Let A and B be defined as above, then

    SP(AB){z=ρeiθ:0<ρ,0<θ<α+β}. (2.3)

    Using Lemmas (2.3) and (2.4), set

    D=π2θπ20<εR{AMn:ReeiθAε},

    where G(z)=f(A1+zA2) and F(z)=f(A2+zA1). If sgnIm(A)=sgnIm(f(A)) and f(sA)=spf(A)(0<p1) hold for any A and s>0, then we know G(z) is a Herglotz function and we can obtain the following theorem.

    Let f(z) be a complex valued holomorphic function on D, and let sgnImf(A)=sgnIm(A) and f(sA)=spf(A)(0<p1) hold for any A and s>0, then f(A) is concave for any A>0.

    Based on the preparation, in this section, we will obtain some useful theorems. To begin, let f(x) be a matrix monotone function, then we can obtain the following theorem by using Lemma 2.5.

    For any p,q,s>0 and s,p+q1, the function

    G(A)=Tr[(f(Aqs2)Kf(Asp)Kf(Asq2))1s], (3.1)

    is concave for any A0 and nonnegative matrix monotone function f(x).

    Proof. To prove this theorem, first, we can obtain that

    ˉG(A)=Tr[(Aqs2KAspKAsq2)1s],

    satisfies Lemma 2.5.

    From an expression of ˉG(A), we know it is a holomorphic function and

    ˉG(ρA)=Tr[((ρqs2Aqs2)K(ρA)spK(ρqs2Asq2))1s]=ρp+qG(A).

    Finally, setting A=A1+iB1 where B1>0, we know that

    sgnIm(A)=sgnIm(Aps)=sgnIm(KAqsK).

    By using Lemmas 2.3 and 2.4, one can obtain

    SP(KAspKAsq){z=ρeiθ:0<ρ,0<θ<s(p+q)π}.

    This implies

    sgnIm(G(A))=sgnImTr[(Aqs2KAspKAsq2)1s]=sgnImTr[(KAspKAsq))1s]=sgnImTr[(T1ΛT)1s],Λ=(λ1000λn)=sgnImTr[Λ1s]=sgnImTr[+0Λ[1s]Λ+tdμ(t)]=sgnImni=1λ1si,

    where λi=ρieθi and 0<θi<s(p+q)π.

    Hence, we know sgnIm(ˉG(A))>0 if sgnIm(A)>0. So, from Lemma 2.5, we obtain that ˉG(A) is concave for any A0. Specifically, setting A=(Z00B) and K=(00H0), we know

    Tr[(Zqs2KBspKZsq2)1s], (3.2)

    is jointly concave for any Z,B0.

    Next, since f(xp)1p is a matrix concave function for any nonnegative matrix monotone function f(x) (0<p1), we have

    G(A+B2)=Tr[(f((A+B2)qs2)Kf((A+B2)sp)Kf((A+B2)sq2))1s]Tr[(f2qs(Aqs2)+f2qs(Bqs2)2)qsK(f1ps(Aps)+f1ps(Bps)2)psK)1s](concavity of f(xp)1p)G(A)+G(B)2.

    Finishing this theorem, one can obtain the Lieb concavity theorem as the following corollary.

    Let 0<p+q1, then

    L(Z,B)=Tr[ZqHBpH], (3.3)

    is jointly concave for any Z,BH+n.

    Proof. Set A=(Z00B) and K=(00H0). When s=1 and f(x)=x we know the function

    G(A)=Tr[(Aq2KApKAq2)]=Tr[(KBpKZq)],

    is jointly concave for any Z,BH+n, which is the Lieb concavity theorem.

    In fact, we can obtain the expansion of the Lieb concavity theorem by Huang [20], which is the following corollary.

    Let 0p,q,s1 and p+q1, then

    H(A,B)=(Tr[k(Aqs2KBspKAsq2)1s])1k, (3.4)

    is jointly concave for any A,B0.

    Proof. Set Z=(A00B), ¯K=(00K0) and f(x)=x. Hence, H(A,B) is jointly concave for any A,B0 equivalent to (Tr[k(Zqs2¯KZsp¯KZsq2)1s])1k, which is concave for any Z0.

    So, we obtain

    H(A1+A22,B1+B22)=(Tr[k((Z1+Z22)qs2¯K(Z1+Z22)sp¯K(Z1+Z22)sq2)1s])1k=(Tr[k((Z1+Z22)qs¯K(Z1+Z22)sp¯K)1s])1k=(Tr[(Z1k1I+Z2k1I2)qs˜K(Z1k1I+Z2k1I2)sp˜K]1s)1k(Tr[[(Z1k1I)qs˜K(Z1k1I)sp˜K]1s+[(Z2k1I)qs˜K(Z2k1I)sp˜K]1s2])1k=(Tr[([Zqs1¯KZsp1¯K]1s+[Zqs2¯KZsp2¯K]1s2)k1((Z1+Z22)qs¯K(Z1+Z22)sp¯K)1s])1k=(Tr[([Λ(z1+z22)sqΛk2])ˉk2([Λ(z1+z22)spΛk2])]1sˉk2)1k(Tr[k([Zqs1¯KZsp1¯K]1s+[Zqs2¯KZsp2¯K]1s2)])1k12(Tr[k[Zqs1¯KZsp1¯K]1s])1k+12(Tr[k[Zqs2¯KZsp2¯K]1s])1k(Thm 2.1 )=H(A1,B1)+H(A2,B2)2, (3.5)

    where ˜K=¯Kk1((Z1+Z22)qs¯K(Z1+Z22)sp¯K)1s, ˉk2=([z1sqˉkz1spk]1s+[z2sqˉkz2spˉk]1s2)12Λk1ˉk, and the first is obtained by using Theorem 3.1 and the second is obtained by using Theorem 3.1 recycling.

    Generally, the following result can be obtained.

    Let 0p,q,s1, and p+q1, then

    H(A,B)=(Tr[k(f(Aqs2)Kf(Bsp)Kf(Asq2))1s])1k, (3.6)

    is jointly concave for any A,B0, where f is a nonnegative matrix monotone function.

    The proof is similar to Corollary 3.3, where it is omitted.

    Setting Z=(A00B), K=(00esA20) and using the Lie-Trotter formula, when p=1,q=0, we obtain that

    limt0Tr[((Z)qs2K(Z)spK(Z)sq2)1s]=Tr[eA+lnB],

    is concave for any B0. So, we can obtain a useful result [9] from Corollary 3.3.

    Let Z,BH+n, then

    H(B)=(Tr[keA+lnB])1k, (3.7)

    is concave for any B0.

    This paper shows that (Tr[k(f(Aqs2)Kf(Bsp)Kf(Asq2))1s])1k is jointly concave for any nonnegative matrix monotone function f (x) and a generalization of the Lieb concavity theorem is given by using the properties of external algebras. In fact, we guess that the following function

    F(A)={Tr[Λn(f(Asq2)Kf(Asp)Kf(Asq2))]}1n{Tr[Λn1(f(Asq2)Kf(Asp)Kf(Asq2))]}1n1,

    should also be concave.

    For the time being, this theory has not been applied to mechanics, and the follow-up research is to apply the anti-information matrix to mechanics.

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

    This paper was written by He Qiujin. He Qiujin and Yang Rongling completed the design of the theorem and the proof of the theorem. He Qiujin led the writing of the paper. Yang Rongling proofread all the drafts. Bu Chunxia made the first instruction to the paper and reviewed the article objectively. All the authors contributed to the further revision of this article. Considering the constructiveness of theorem proof, He Qiujin, Yang Rongling, and Bu Chunxia all participated in the design of the theorem. In the course of proving the theorem, they separately conducted data collection and consulted relevant data and further derivation.

    Finally, all three authors contributed to the writing and revision of the paper, and offered some constructive comments and suggestions for improvement to ensure that the paper can accurately explain the rationality of theorem construction and proof.

    The authors declare no conflict of interest.



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