Stabilizing the Metzler matrices with applications to dynamical systems Abstract Real matrices with non-negative off-diagonal entries play a crucial role for modelling the positive linear dynamical systems. In the literature, these matrices are referred to as Metzler matrices or negated Z-matrices. Finding the closest stable Metzler matrix to an unstable one (and vice versa) is an important issue with many applications. The stability considered here is in the sense of Hurwitz, and the distance between matrices is measured in \(l_\infty ,\,l_1\), and in the max norm. We provide either explicit solutions or efficient algorithms for obtaining the closest (un)stable matrix. The procedure for finding the closest stable Metzler matrix is based on the recently introduced selective greedy spectral method for optimizing the Perron eigenvalue. Originally intended for non-negative matrices, here is generalized to Metzler matrices. The efficiency of the new algorithms is demonstrated in examples and numerical experiments for the dimension of up to 2000. Applications to dynamical systems, linear switching systems, and sign-matrices are considered.

Symmetric collocation ERKN methods for general second-order oscillators Abstract For the numerical solution of the general second-order oscillatory system \(y''+ M y = f(y,y')\), You et al. (Numer Algorithm 66:147–176, 2014) proposed the extended Runge–Kutta–Nyström (ERKN) methods. This paper is devoted to symmetric collocation ERKN methods of Gauss and Lobatto IIIA types by Lagrange interpolation. Linear stability of the new ERKN methods is analyzed. Numerical experiments show the high effectiveness of the new ERKN methods compared to their RKN counterparts.

Solution formulas for differential Sylvester and Lyapunov equations Abstract The differential Sylvester equation and its symmetric version, the differential Lyapunov equation, appear in different fields of applied mathematics like control theory, system theory, and model order reduction. The few available straight-forward numerical approaches when applied to large-scale systems come with prohibitively large storage requirements. This shortage motivates us to summarize and explore existing solution formulas for these equations. We develop a unifying approach based on the spectral theorem for normal operators like the Sylvester operator \({\mathcal {S}}(X)=AX+XB\) and derive a formula for its norm using an induced operator norm based on the spectrum of A and B. In view of numerical approximations, we propose an algorithm that identifies a suitable Krylov subspace using Taylor series and use a projection to approximate the solution. Numerical results for large-scale differential Lyapunov equations are presented in the last sections.

A new recursive formulation of the Tau method for solving linear Abel–Volterra integral equations and its application to fractional differential equations Abstract In this paper, the recursive approach of the Tau method is developed for numerical solution of Abel–Volterra type integral equations. Due to the singular behavior of solutions of these equations, the existing spectral approaches suffer from low accuracy. To overcome this drawback we use Müntz–Legendre polynomials as basis functions which have remarkable approximation to functions with singular behavior at origin and express Tau approximation of the exact solution based on a sequence of basis canonical polynomials that is generated by a simple recursive formula. We also provide a convergence analysis for the proposed method and obtain an exponential rate of convergence regardless of singularity behavior of the exact solution. Some examples are given to demonstrate the effectiveness of the proposed method. The results are compared with those obtained by existing numerical methods, thereby confirming the superiority of our scheme. The paper is closed by providing application of this method to approximate solution of a linear fractional integro-differential equation.

Mixed finite element discretizations of acoustic Helmholtz problems with high wavenumbers Abstract We study the acoustic Helmholtz equation with impedance boundary conditions formulated in terms of velocity, and analyze the stability and convergence properties of lowest-order Raviart-Thomas finite element discretizations. We focus on the high-wavenumber regime, where such discretizations suffer from the so-called “pollution effect”, and lack stability unless the mesh is sufficiently refined. We provide wavenumber-explicit mesh refinement conditions to ensure the well-posedness and stability of discrete scheme, as well as wavenumber-explicit error estimates. Our key result is that the condition “ \(k^2 h\) is sufficiently small”, where k and h respectively denote the wavenumber and the mesh size, is sufficient to ensure the stability of the scheme. We also present numerical experiments that illustrate the theory and show that the derived stability condition is actually necessary.

A virtual element method for the coupled Stokes–Darcy problem with the Beaver–Joseph–Saffman interface condition Abstract In this work, we propose a virtual element method for discretizing the equations that couple the incompressible steady Stokes flow with the Darcy flow by means of the Beaver–Joseph–Saffman condition on their interface. In addition to avoiding explicit expressions of basis functions, this method can not only improve the computational efficiency of any polynomial degree, but also can treat any polygonal elements, including non-convex and non-matching elements. Moreover, combining with the discrete inf-sup condition of a virtual element approximation for the velocity and pressure pair \(P_{k}/P_{k-1}\) , we can obtain optimal error estimates. Furthermore, numerical experiments are presented to show the efficiency and validity of the coupled method.

Least squares solutions to the rank-constrained matrix approximation problem in the Frobenius norm Abstract In this paper, we discuss the following rank-constrained matrix approximation problem in the Frobenius norm: \(\Vert C-AX\Vert =\min \) subject to \( \text{ rk }\left( {C_1 - A_1 X} \right) = b \) , where b is an appropriate chosen nonnegative integer. We solve the problem by applying the classical rank-constrained matrix approximation, the singular value decomposition, the quotient singular value decomposition and generalized inverses, and get two general forms of the least squares solutions.

Strong convergence analysis of iterative solvers for random operator equations Abstract For the numerical solution of linear systems that arise from discretized linear partial differential equations, multigrid and domain decomposition methods are well established. Multigrid methods are known to have optimal complexity and domain decomposition methods are in particular useful for parallelization of the implemented algorithm. For linear random operator equations, the classical theory is not directly applicable, since condition numbers of system matrices may be close to degenerate due to non-uniform random input. It is shown that iterative methods converge in the strong, i.e. \(L^p\) , sense if the random input satisfies certain integrability conditions. As a main result, standard multigrid and domain decomposition methods are applicable in the case of linear elliptic partial differential equations with lognormal diffusion coefficients and converge strongly with deterministic bounds on the computational work which are essentially optimal. This enables the application of multilevel Monte Carlo methods with rigorous, deterministic bounds on the computational work.

A remarkable Wronskian with application to critical lengths of cycloidal spaces Abstract Recently, Carnicer et al. (Calcolo 54(4):1521–1531, 2017) proved the very elegant and surprising fact that half of the critical length of a cycloidal space coincides with the first positive zero of a spherical Bessel function. Their finding relied in identifying the first positive zero of certain Wronskians. In this paper, we show that these Wronskians admit explicit expressions in terms of spherical Bessel functions. As an application, we recover the above mentioned result.

A hybrid extragradient method for a general split equality problem involving resolvents and pseudomonotone bifunctions in Banach spaces Abstract In this paper, using a hybrid extragradient method, we introduce a new iterative process for finding a common element of the solution set of the Split Equality Common Equilibrium Problem for a finite family of pseudomonotone bifunctions and the solution set of the Split Equality Common Null Point Problem for a finite family of monotone operators in certain Banach spaces. We establish strong convergence of the proposed algorithm. This paper concludes with certain applications where we utilize our results to study the determination of a solution of the Split Equality Common Variational Inequality Problem and a solution of the Split Equality Common Null Point Problem. A numerical example to support our main theorem will be exhibited. The theorems proved improve and complement a host of important recent results.