Algorithms for solving inverse geophysical problems on parallel computing systems

For solving inverse gravimetry problems, efficient stable parallel algorithms based on iterative gradient methods are proposed. For solving systems of linear algebraic equations with block-tridiagonal matrices arising in geoelectrics problems, a parallel matrix sweep algorithm, a square root method, and a conjugate gradient method with preconditioner are proposed. The algorithms are implemented numerically on a parallel computing system of the Institute of Mathematics and Mechanics (PCS-IMM), NVIDIA graphics processors, and an Intel multi-core CPU with some new computing technologies. The parallel algorithms are incorporated into a system of remote computations entitled “Specialized Web-Portal for Solving Geophysical Problems on Multiprocessor Computers.” Some problems with “quasi-model” and real data are solved.     

A method for approximately solving inverse problems of wave propagation in a dissipative layered medium

A method for reducing one-dimensional inverse problems of wave propagation theory to Cauchy problems for nonlinear systems of ordinary differential equations is proposed. This approach is applicable to a special class of inverse data, which is dense in the whole set of data equipped with any natural topology. Bibliography: 2 titles. Translated fromZapiski Nauchnykh Seminarov POMI, Vol. 230, 1995, pp. 36–40. Translated by A. S. Blagovestchenskii.     

A penalty function method based on bilevel programming for solving inverse optimal value problems

In this work, we reformulate the inverse optimal value problem equivalently as a corresponding nonlinear bilevel programming (BLP) problem. For the nonlinear BLP problem, the duality gap of the lower level problem is appended to the upper level objective with a penalty, and then a penalized problem is obtained. On the basis of the concept of partial calmness, we prove that the penalty function is exact. Then, an algorithm is proposed and an inverse optimal value problem is resolved to illustrate the algorithm.     

Asymptotics for spectral regularization estimators in statistical inverse problems

While optimal rates of convergence in L ₂ for spectral regularization estimators in statistical inverse problems have been much studied, the pointwise asymptotics for these estimators have received very little consideration. Here, we briefly discuss asymptotic expressions for bias and variance for some such estimators, mainly in deconvolution-type problems, and also show their asymptotic normality. The main part of the paper consists of a simulation study in which we investigate in detail the pointwise finite sample properties, both for deconvolution and the backward heat equation as well as for a regression model involving the Radon transform. In particular we explore the practical use of undersmoothing in order to achieve the nominal coverage probabilities of the confidence intervals.     

Algorithms for solving Hermite interpolation problems using the Fast Fourier Transform

We present a method for computing the Hermite interpolation polynomial based on equally spaced nodes on the unit circle with an arbitrary number of derivatives in the case of algebraic and Laurent polynomials. It is an adaptation of the method of the Fast Fourier Transform (FFT) for this type of problems with the following characteristics: easy computation, small number of operations and easy implementation.In the second part of the paper we adapt the algorithm for computing the Hermite interpolation polynomial based on the nodes of the Tchebycheff polynomials and we also study Hermite trigonometric interpolation problems.     

Legendre spectral method for solving mixed boundary value problems on rectangle

In this paper, we develop a spectral method for mixed inhomogeneous Dirichlet/Neumann/Robin boundary value problems defined on rectangle. Some results on two‐dimensional Legendre approximation in Jacobi‐weighted Sobolev space are established. As examples of applications, spectral schemes are provided for two model problems with mixed inhomogeneous boundary conditions. The spectral accuracy in space of proposed algorithms are proved. Efficient implementations are presented. Numerical results demonstrate their high accuracy and confirm the theoretical analysis well. Copyright © 2016 John Wiley & Sons, Ltd.     

Numerical algorithm based on transmutation for solving inverse wave equation

This paper develops algorithms for solving an undetermined coefficient problem for a wave equation. The algorithms are based on an integral representation for the solution to the wave equation obtained by using transmutation. The convergence of the algorithm is studied and numerical experiments are performed.     

Direct and inverse dynamic problems for SH-waves in porous media

Direct and inverse dynamic problems for the equation of SH-waves in porous media are considered. A singular solution of the direct dynamic problem is constructed. A system of nonlinear Volterra integral equations of the second kind is obtained for the dynamic inverse problems in question. Theorems of uniqueness and theorems of existence in the small for the considered inverse problems are proved. Also, theorems of continuous dependence of solutions of inverse dynamic problems on input data are proved.     

A comparison between a recursive method based on an inverse mechanical formulation and shape optimization for solving inverse form finding problems in isotropic elastoplasticity

In this paper we compare two methods, a recursive method based on an inverse mechanical formulation and a method based on a recursive shape optimization formulation, in order to solve inverse form finding problems in isotropic elastoplasticity. Both methods are succinctly presented and a numerical example is given. It was found that no difference could be found between the node coordinates on the undeformed configurations computed with both methods. However the convergence to the solution is faster with the recursive method based on an inverse mechanical formulation than with the method based on shape optimization. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

On the discrepancy principle for some Newton type methods for solving nonlinear inverse problems

We consider the computation of stable approximations to the exact solution of nonlinear ill-posed inverse problems F(x) = y with nonlinear operators F : X → Y between two Hilbert spaces X and Y by the Newton type methods

Numerical solution of inverse spectral problems for Sturm-Liouville operators with discontinuous potentials

We consider Sturm-Liouville differential operators on a finite interval with discontinuous potentials having one jump. As the main result we obtain a procedure of recovering the location of the discontinuity and the height of the jump. Using our result, we apply a generalized Rundell-Sacks algorithm of Rafler and Böckmann for a more effective reconstruction of the potential and present some numerical examples.     

Methods and algorithms of solving spectral problems for polynomial and rational matrices

In the present paper, methods and algorithms for numerical solution of spectral problems and some problems in algebra related to them for one- and two-parameter polynomial and rational matrices are considered. A survey of known methods of solving spectral problems for polynomial matrices that are based on the rank factorization of constant matrices, i.e., that apply the singular value decomposition (SVD) and the normalized decomposition (the QR factorization), is given. The approach to the construction of methods that makes use of rank factorization is extended to one- and two-parameter polynomial and rational matrices. Methods and algorithms for solving some parametric problems in algebra based on ideas of rank factorization are presented. Bibliography: 326titles.Dedicated to the memory of my son AlexanderTranslated fromZapiski Nauchnykh Seminarov POMI, Vol. 238, 1997, pp. 7–328.Translated by V. N. Kublanovskaya.     

New regularized algorithms based on the spectral method for solving deformable layer tomography

The deformable layer tomography (DLT) is now a popular way to characterize the unknown geometry of the velocity interface by using the traveling time observed in data, which is difficult to solve accurately, because of the strong ill-posedness. In this paper, new regularization approaches based on the spectral method are introduced, which can invert the velocity value and the geometry of the interface simultaneously. The unknown interfaces are parameterized by Legendre spectral expansion, and various regularization methods combined with traditional regularization parameters selections are utilized to solve the ill-conditioned algebraic equation system. Moreover, a regularized algorithm with prior choice of regularization parameters is proposed to solve the DLT.     

Algorithms for solving multiobjective discrete control problems and dynamic c-games on networks

In this paper we study a special class of multiobjective discrete control problems on dynamic networks. We assume that the dynamics of the system is controlled by p actors (players) and each of them intend to minimize his own integral-time cost by a certain trajectory. Applying Nash and Pareto optimality principles we study multiobjective control problems on dynamic networks where the dynamics is described by a directed graph.Polynomial-time algorithms for determining the optimal strategies of the players in the considered multiobjective control problems are proposed exploiting the special structure of the underlying graph. Properties of time-expanded networks are characterized. A constructive scheme which consists of several algorithms is presented.     

A modified pulse-spectrum technique for solving inverse problems of two-dimensional elastic wave equation

The Pulse-Spectrum Technique (PST), an iterative numerical algorithm for solving multi-parameter inverse problems of partial differential equations, is modified by using the Garlerkin method to solve the Fredholm integral equation of the first kind in each iteration. In this way, the computation of the complicated Green's matrix in the integrand can be avoided. Details are presented for simultaneous determination of bulk and shear moduli and density variation of the two-dimensional elastic wave equation. Numerical simulation is carried out for an example in the geophysical prospecting to test the feasibility and to study the intrinsic characteristics of the modified PST (MPST) without the real measurement data. It is shown that MPST does give excellent results.     

An explicit finite difference scheme based on the modified method of characteristics for solving convection-diffusion problems in one space dimension

Finite differences are combined with the modified method of characteristics to develop an explicit scheme for solving convection-dominated convection-diffusion problems in one spatial dimension. Error analysis shows that the new algorithm is stable under a mild stability criterion. Problems with known analytical solutions are used to test the algorithm and demonstrate its convergence. Numerical solutions are free of numerical dispersion, undershoot and overshoot. The algorithm is easy to implement and requires small computational times for the test problems considered.     

Discrete-analytic schemes for solving an inverse coefficient heat conduction problem in a layered medium with gradient methods

A method for constructing numerical schemes for an inverse coefficient heat conduction problem with boundary measurement data and piecewise-constant coefficients is considered. Some numerical schemes for a gradient optimization algorithm to solve the inverse problem are presented. The method is based on locally-adjoint problems in combination with approximation methods in Hilbert spaces.     

The projected newton method for solving inverse eigenvalue problems - the case of multiple eigenvaues

This paper deals with the optimal solution of ill-posed linear problems, i.e..linear problems for which the solution operator is unbounded. We consider worst-case ar,and averagecase settings. Our main result is that algorithms having finite error (for a given setting) exist if and only if the solution operator is bounded (in that setting). In the worst-case setting, this means that there is no algorithm for solving ill-posed problems having finite error. In the average-case setting, this means that algorithms having finite error exist if and only lf the solution operator is bounded on the average. If the solution operator is bounded on the average, we find average-case optimal information of cardinality n and optimal algorithms using this information, and show that the average error of these algorithms tends to zero as n→∞. These results are then used to determine the [euro]-complexity, i.e., the minimal costof finding an [euro]-accurate approximation. In the worst-case setting, the [euro]comp1exity of an illposed problem is infinite for all [euro]>0; that is, we cannot find an approximation having finite error and finite cost. In the average-case setting, the [euro]-complexity of an ill-posed problem is infinite for all [euro]>0 iff the solution operator is not bounded on the average, moreover, if the the solutionoperator is bounded on the average, then the [euro]-complexity is finite for all [euro]>0.     

Asymptotic behavior of singular solitons and the inverse scattering method for solving boundary value problems

We solve the boundary value problems for the sine-Gordon equation and the elliptic Toda lattice in the framework of the inverse scattering method. This approach allows incorporating the singular soliton solutions of the spiral vortex form. Translated from Teoreticheskaya i Matematicheskaya Fizika, Vol. 124, No. 2, pp. 279–291, August, 2000.