Volume 23, Issue 4

We consider the scattering of spherically-symmetric acoustic waves by an anisotropic medium and a cavity. While there is a large number of recent works devoted to the scattering problems with cavities, existence of an infinite set of transmission eigenvalues is an open problem in general. In this paper we prove existence of an infinite set of transmission eigenvalues for anisotropic Helmholtz and Schrödinger equations in a spherically-symmetric domain with a cavity. Further in this paper we consider the corresponding inverse problem. Under some assumptions we prove the uniqueness in the inverse problem.

Ill-posedness and/or ill-conditioning are features users have to deal with appropriately in the controllability of diffusion problems for secure and reliable outputs. We investigate those issues in the case of a boundary Dirichlet control, in an attempt to underline the origin of the troubles arising in the numerical computations and to shed some light on the difficulties to obtain good quality simulations. The exact-controllability is severely ill-posed while, in spite of its well-posedness, the null-controllability turns out to be very badly ill-conditioned. Theoretical and numerical results are stated on the heat equation in one dimension to illustrate the specific instabilities of each problem. The main tools used here are first a characterization of the subspace where the HUM (Hilbert Uniqueness Method) control lies and the study of the spectrum of some structured matrices, of Pick and Löwner type, obtained from the Fourier calculations on the state and adjoint equations.

This paper deals with the problem of identifying parameters in the mathematical model of immune competition developed in [Modelling Complex Biological Systems: A Kinetic Theory Approach, Birkhäuser, Boston, 2006]. More precisely, we use the approach called inverse problem to identify the parameters of the model, and we investigate the identifiability as well as the stability of the inverse problem. In numerical analysis, the inverse problem is reformulated as an optimization problem where the variables are the estimated parameters in the model. In our study, the regularized least-squares cost function and the adjoint technique to compute the gradient of the cost function are used. Finally, some numerical tests for parameters identification using synthetic data are presented.

In the present paper we consider an inverse source problem for a time-fractional mixed parabolic-hyperbolic equation with Caputo derivatives. In the case when the hyperbolic part of the considered mixed-type equation is the wave equation, the uniqueness of the source and the solution are strongly influenced by the initial time and the problem is generally ill-posed. However, when the hyperbolic part is time-fractional, the problem is well-posed if the end time is large. Our method relies on the orthonormal system of eigenfunctions of the operator with respect to the space variables. Finally, we prove uniqueness and stability of certain weak solutions for the problems under consideration.

Many systems can be represented as linear time-invariant (LTI) systems in state space with ordinary differential equations (ODE). Forced responses are often used for model parameter estimation; however, some models are not uniquely identifiable from the data of forced responses, or experiments with pure forced response may not be the optimal design. It is thus meaningful to look for other types of data for model parameter estimation through redesigning experiments. In this work, we compare the influence of forced and initial condition responses on the deterministic identifiability of LTI systems in state space with ODEs as model structure. It is clearly demonstrated that one initial condition vector is equivalent to one column vector of the control matrix for constraining system eigenvectors. The combination of forced and initial condition responses can improve the identifiability of models that are not identifiable only from forced responses. Explicit formulations and an algorithm are derived to identify model parameters from the combined data of forced and initial condition responses.

In this paper, we discuss an inverse problem for the Vlasov–Poisson system. We prove local uniqueness and stability theorems by using the method in Anikonov and Amirov [Dokl. Akad. Nauk SSSR 272 (1983), 1292–1293] under the specular reflection boundary condition and with a prescribed outward electrical field at the boundary.

A version of the nonstationary iterated Tikhonov method was recently introduced to regularize linear inverse problems in Banach spaces [Inverse Problems 28 (2012), Article ID 104011]. In the present work we employ this method as inner iteration of the inexact Newton regularization method REGINN [Inverse Problems 15 (1999), 309–327] which stably solves nonlinear ill-posed problems. Further, we propose and analyze a Kaczmarz version of the new scheme which allows fast solution of problems which can be split into smaller subproblems. As special cases we prove strong convergence of Kaczmarz variants of the Levenberg–Marquardt and the iterated Tikhonov methods in Banach spaces.

This paper is concerned with the development of numerical schemes for the minimization of functionals involving sparsity constraints and nonconvex fidelity terms. These functionals appear in a natural way in the context of Tikhonov regularization of nonlinear inverse problems with ℓ 1 penalty terms. Our method of minimization is based on a generalized conditional gradient scheme. It is well known that these algorithms might converge quite slowly in practice. Therefore, we propose an acceleration which is based on a decreasing thresholding strategy. Its efficiency relies on certain spectral properties of the problem at hand. We show that under certain boundedness and contraction conditions the resulting algorithm is linearly convergent to a global minimizer and that the iteration is monotone with respect to the Tikhonov functional. We study important classes of operator equations to which our analysis can be applied. Moreover, we introduce a certain multilevel preconditioning strategy which in practice promotes the aforementioned spectral properties for problems where the nonlinearity is a perturbation of a linear operator.

A long standing problem is completely solved here for the first time. This problem was posed by K. Chadan and P. C. Sabatier in their classical book “Inverse Problems in Quantum Scattering Theory”, Springer, New York, 1977. The inverse scattering problem of the reconstruction of the unknown potential with a compact support in the three-dimensional Schrödinger equation is considered. Only the modulus of the scattering complex-valued wave field is known, whereas the phase is unknown. It is shown that the unknown potential can be reconstructed via the inverse Radon transform. This solution has potential applications in imaging of nanostructures.