Multidimensional Case Research Articles

An analysis of the L1 scheme for stochastic subdiffusion problem driven by integrated space-time white noise

We consider the strong convergence of the numerical methods for solving stochastic subdiffusion problem driven by an integrated space-time white noise. The time fractional derivative is approximated by using the L1 scheme and the time fractional integral is approximated with the Lubich's first order convolution quadrature formula. We use the Euler method to approximate the noise in time and use the truncated series to approximate the noise in space. The spatial variable is discretized by using the linear finite element method. Applying the idea in Gunzburger et al. (2019) [14], we express the approximate solutions of the fully discrete scheme by the convolution of the piecewise constant function and the inverse Laplace transform of the resolvent related function. Based on such convolution expressions of the approximate solutions, we obtain the optimal convergence orders of the fully discrete scheme in spatial multi-dimensional cases by using the Laplace transform method and the corresponding resolvent estimates.

Fixed Point Theorems Applied in Uncertain Fractional Differential Equation with Jump

No previous study has involved uncertain fractional differential equation (FDE, for short) with jump. In this paper, we propose the uncertain FDEs with jump, which is driven by both an uncertain V-jump process and an uncertain canonical process. First of all, for the one-dimensional case, we give two types of uncertain FDEs with jump that are symmetric in terms of form. The next, for the multidimensional case, when the coefficients of the equations satisfy Lipschitz condition and linear growth condition, we establish an existence and uniqueness theorems of uncertain FDEs with jump of Riemann-Liouville type by Banach fixed point theorem. A symmetric proof in terms of form is suitable to the Caputo type. When the coefficients do not satisfy the Lipschitz condition and linear growth condition, we just prove an existence theorem of the Caputo type equation by Schauder fixed point theorem. In the end, we present an application about uncertain interest rate model.

The statistical properties of 3D Klein polyhedra

Let be a rank- lattice in . The convex hulls of the nonzero lattice points lying in orthants are called the Klein polyhedra of . This construction was introduced by Klein in 1895, in connection with generalizing the classical continued-fraction algorithm to the multidimensional case. Arnold stated a number of problems on the statistical and geometric properties of Klein polyhedra. In two dimensions the corresponding results follow from the theory of continued fractions. An asymptotic formula for the mean value of the -vectors (the numbers of facets, edges and vertices) of 3D Klein polyhedra is derived. This mean value is taken over the Klein polyhedra of integer 3D lattices with determinants in , where is an increasing parameter. Bibliography: 27 titles.

Directional differentiability for supremum-type functionals: Statistical applications

We show that various functionals related to the supremum of a real function defined on an arbitrary set or a measure space are Hadamard directionally differentiable. We specifically consider the supremum norm, the supremum, the infimum, and the amplitude of a function. The (usually non-linear) derivatives of these maps adopt simple expressions under suitable assumptions on the underlying space. As an application, we improve and extend to the multidimensional case the results in Raghavachari (Ann. Statist. 1 (1973) 67–73) regarding the limiting distributions of Kolmogorov–Smirnov type statistics under the alternative hypothesis. Similar results are obtained for analogous statistics associated with copulas. We additionally solve an open problem about the Berk–Jones statistic proposed by Jager and Wellner (In A Festschrift for Herman Rubin (2004) 319–331 IMS). Finally, the asymptotic distribution of maximum mean discrepancies over Donsker classes of functions is derived.

Application of discontinuous Galerkin method in supersonic and hypersonic gas flows

Most high-order methods often suffer from two- and three-dimensional unstructured grids, particularly, for supersonic and hypersonic gas flows. We applied a high-order mixed-modal discontinuous Galerkin method with a coupled slope limiter to investigate multidimensional cases of supersonic and hypersonic gas flows. Furthermore, we provide detailed implementations and validations of two- and three-dimensional problems. Examples include double Mach reflection problems and supersonic and hypersonic gas flows around a cylinder. In addition, we provide case studies of a 3D hypersonic vehicle to evaluate its computational performance on complex hypersonic gas flows. This study can be regarded as an attempt to apply the discontinuous Galerkin method to engineering problems.

Depth Induced Regression Medians and Uniqueness

The notion of median in one dimension is a foundational element in nonparametric statistics. It has been extended to multi-dimensional cases both in location and in regression via notions of data depth. Regression depth (RD) and projection regression depth (PRD) represent the two most promising notions in regression. Carrizosa depth D C is another depth notion in regression. Depth-induced regression medians (maximum depth estimators) serve as robust alternatives to the classical least squares estimator. The uniqueness of regression medians is indispensable in the discussion of their properties and the asymptotics (consistency and limiting distribution) of sample regression medians. Are the regression medians induced from RD, PRD, and D C unique? Answering this question is the main goal of this article. It is found that only the regression median induced from PRD possesses the desired uniqueness property. The conventional remedy measure for non-uniqueness, taking average of all medians, might yield an estimator that no longer possesses the maximum depth in both RD and D C cases. These and other findings indicate that the PRD and its induced median are highly favorable among their leading competitors.

Approximation of the Multidimensional Optimal Control Problem for the Heat Equation (Applicable to Computational Fluid Dynamics (CFD))

This work is devoted to finding an estimate of the convergence rate of an algorithm for numerically solving the optimal control problem for the three-dimensional heat equation. An important aspect of the work is not only the establishment of convergence of solutions of a sequence of discrete problems to the solution of the original differential problem, but the determination of the order of convergence, which plays a very important role in applications. The paper uses the discretization method of the differential problem and the method of integral estimates. The reduction of a differential multidimensional mixed problem to a difference one is based on the approximation of the desired solution and its derivatives by difference expressions, for which the error of such an approximation is known. The idea of using integral estimates is typical for such problems, but in the multidimensional case significant technical difficulties arise. To estimate errors, we used multidimensional analogues of the integration formula by parts, Friedrichs and Poincare inequalities. The technique used in this work can be applied under some additional assumptions, and for nonlinear multidimensional mixed problems of parabolic type. To find a numerical solution, the variable direction method is used for the difference problem of a parabolic type equation. The resulting algorithm is implemented using program code written in the Python 3.7 programming language.

Mornitoring, Forecasting and Optimization Technique When Multi-Variables Shift With Time

In this paper, the quality control technique and the optimization of adjustment interval of one dimensional quality characteristic are extended to multi-dimensional case in which the vector of the quality characteristics or important financial indices of firms shifts with time. A special multivariate triangle control chart is proposed to control such kind of process. An application is illustrated to monitor and predict the soundness of insurers of U.S. Finally, 7 important issues for further study in future are presented.

Orthogonal Splines in Approximation of Functions

The problem of approximating of a surface given by the values of a function of two arguments in a finite number of points of a certain region in the classical formulation is reduced to solving a system of algebraic equations with tightly filled matrixes or with band matrixes. In the case of complex surfaces, such a problem requires a significant number of arithmetic operations and significant computer time spent on such calculations. The curvilinear boundary of the domain of general type does not allow using classical orthogonal polynomials or trigonometric functions to solve this problem. This paper is devoted to an application of orthogonal splines for creation of approximations of functions in form of finite Fourier series. The orthogonal functions with compact supports give possibilities for creation of such approximations of functions in regions with arbitrary geometry of a boundary in multidimensional cases. A comparison of the fields of application of classical orthogonal polynomials, trigonometric functions and orthogonal splines in approximation problems is carried out. The advantages of orthogonal splines in multidimensional problems are shown. The formulation of function approximation problem in variational form is given, a system of equations for coefficients of linear approximation with a diagonal matrix is formed, expressions for Fourier coefficients and approximations in the form of a finite Fourier series are written. Examples of approximations are considered. The efficiency of orthogonal splines is shown. The development of this direction associated with the use of other orthogonal splines is discussed.

Ogawa Integrability and a Condition for Convergence in the Multidimensional Case

Ogawa Integrability and a Condition for Convergence in the Multidimensional Case

Goal-Based Error Estimation for the Multi-Dimensional Diamond Difference and Box Discrete Ordinate (SN) Methods

Goal-based error estimation due to spatial discretization and adaptive mesh refinement (AMR) has previously been investigated for the one dimensional, diamond difference, discrete ordinate (1-D DD-SN) method for discretizing the Neutron Transport Equation (NTE). This paper investigates the challenges of extending goal-based error estimation to multi-dimensions with supporting evidence provided on 2-D fixed (extraneous) source and Keff eigenvalue (criticality) verification test cases. It was found that extending Hennart’s weighted residual view of the lowest order 1-D DD equations to multi-dimensions gave what has previously been called the box method. This paper shows how the box method can be extended to higher orders. The paper also shows an equivalence between the higher order box methods and the higher order DD methods derived by Hébert et al. Though, less information is retained in the final solution in the latter case. These extensions allow for the definition of dual weighted residual (DWR) error estimators in multi-dimensions for the DD and box methods. However, they are not applied to drive AMR in the multi-dimensional case due to the various challenges explained in this paper.

Propagation of One- and Two-Dimensional Discrete Waves Under Finite Difference Approximation

We analyze the propagation properties of the numerical versions of one- and two-dimensional wave equations, semi-discretized in space by finite difference schemes. We focus on high-frequency solutions whose propagation can be described, both at the continuous and at the semi-discrete levels, by micro-local tools. We consider uniform and non-uniform numerical grids as well as constant and variable coefficients. The energy of continuous and semi-discrete high-frequency solutions propagates along bi-characteristic rays, but their dynamics are different in the continuous and the semi-discrete setting, because of the nature of the corresponding Hamiltonians. One of the main objectives of this paper is to illustrate through accurate numerical simulations that, in agreement with micro-local theory, numerical high-frequency solutions can bend in an unexpected manner, as a result of the accumulation of the local effects introduced by the heterogeneity of the numerical grid. These effects are enhanced in the multi-dimensional case where the interaction and combination of such behaviors in the various space directions may produce, for instance, the rodeo effect, i.e., waves that are trapped by the numerical grid in closed loops, without ever getting to the exterior boundary. Our analysis allows to explain all such pathological behaviors. Moreover, the discussion in this paper also contributes to the existing theory about the necessity of filtering high-frequency numerical components when dealing with control and inversion problems for waves, which is based very much on the theory of rays and, in particular, on the fact that they can be observed when reaching the exterior boundary of the domain, a key property that can be lost through numerical discretization.

A Probabilistic Representation of the Cauchy Problem Solution for the Multidimensional Schrödinger Equation

We construct a probabilistic representation of the Cauchy problem solution for the Schrodinger equation 2i∂tu = − Δu. The result is an extension to the multidimensional case of the previous results by I. Ibragimov, N. Smorodina, and M. Faddeev.

Alternating and variable controls for the wave equation

The present article discusses the exact observability of the wave equation when the observation subset of the boundary is variable in time. In the one-dimensional case, we prove an equivalent condition for the exact observability, which takes into account only the location in time of the observation. To this end we use Fourier series. Then we investigate the two specific cases of single exchange of the control position, and of exchange at a constant rate. In the multi-dimensional case, we analyse sufficient conditions for the exact observability relying on the multiplier method. In the last section, the multi-dimensional results are applied to specific settings and some connections between the one and multi-dimensional case are discussed; furthermore some open problems are presented.

Block generalized locally Toeplitz sequences: theory and applications in the multidimensional case

In computational mathematics, when dealing with a large linear discrete problem (e.g., a linear system) arising from thenumerical discretization of a partial differential equation (PDE), knowledge of the spectral distribution of the associated matrix has proved to beuseful information for designing/analyzing appropriate solvers–-especially, preconditioned Krylov and multigrid solvers–-for the considered problem.Actually, this spectral information is of interest also in itself as long as the eigenvalues of the aforementioned matrix represent physical quantities of interest,which is the case for several problems from engineering and applied sciences (e.g., the study of natural vibration frequencies in an elastic material).The theory of multilevel generalized locally Toeplitz (GLT) sequences is a powerful apparatus for computing the asymptotic spectral distribution of matrices $A_n$arising from virtually any kind of numerical discretization of PDEs. Indeed, when the mesh-fineness parameter $n$ tends to infinity, these matrices $A_n$ give rise to asequence $\\{A_n\\}_n$, which often turns out to be a multilevel GLT sequence or one of its “relatives”, i.e., a multilevel block GLT sequence or a (multilevel) reduced GLTsequence. In particular, multilevel block GLT sequences are encountered in the discretization of systems of PDEs as well as in the higher-order finite element or discontinuousGalerkin approximation of scalar/vectorial PDEs.In this work, we systematically develop the theory of multilevel block GLT sequences as an extension of the theories of (unilevel) GLT sequences[Garoni and Serra-Capizzano, Generalized Locally Toeplitz Sequences: Theory and Applications. Vol. I., Springer, Cham, 2017],multilevel GLT sequences[Garoni and Serra-Capizzano, Generalized Locally Toeplitz Sequences: Theory and Applications. Vol. II., Springer, Cham, 2018],and block GLT sequences[Barbarino, Garoni, and Serra-Capizzano, Electron. Trans. Numer. Anal., 53 (2020), pp. 28–112].We also present several emblematic applications of this theory in the context of PDE discretizations.

REGULAR SOLUTION OF THE INVERSE PROBLEM WITH INTEGRAL CONDITION FOR A TIME-FRACTIONAL EQUATION

Direct and inverse problems for equations with fractional derivatives are arising in various fields of science and technology. The conditions for classical solvability of the Cauchy and boundary-value prob\-lems for diffusion-wave equations with fractional derivatives are known. Estimates of components of the Green's vector-function of the Cauchy problem for such equations are known. We study the inverse problem of determining the space-dependent component of the right-hand side of the equation with a time fractional derivative and known functions from Schwartz-type space of smooth rapidly decreasing functions or with values in them. We also consider such a problem in the case of data from some wider space of smooth, decreasing to zero at infinity functions or with values in them. We find sufficient conditions for unique solvability of the inverse problem under the time-integral additional condition \[\frac{1}{T}\int_{0}^{T}u(x,t)\eta_1(t)dt=\Phi_1(x), \;\;\;x\in \Bbb R^n\] where $u$ is the unknown solution of the Cauchy problem, $\eta_1$ and $\Phi_1$ are the given functions. Using the method of the Green's vector function, we reduce the problem to solvability of an integrodifferential equation in a certain class of smooth, decreasing to zero at infinity functions. We prove its unique solvability. There are various methods for the approximate solution of direct and inverse problems for equations with fractional derivatives, mainly for the one-dimensional spatial case. It follows from our results the method of constructing an approximate solution of the inverse problem in the multidimensional spatial case. It is based on the use of known methods of constructing the numerical solutions of integrodifferential equations. The application of the Fourier transform by spatial variables is effective for constructing a numerical solution of the obtained integrodifferential equation, since the Fourier transform of the components of the Green's vector function can be explicitly written.

Robust Restoration of Sparse Multidimensional Single-Photon LiDAR Images

The challenges of real world applications of the laser detection and ranging (Lidar) three-dimensional (3-D) imaging require specialized algorithms. In this paper, a new reconstruction algorithm for single-photon 3-D Lidar images is presented that can deal with multiple tasks. For example, when the return signal contains multiple peaks due to imaging semitransparent surfaces, or when imaging through obscurants such as scattering media. A generalization to the multidimensional case, including multispectral and multitemporal 3-D images, is also provided. The approach is based on the minimization of a cost function accounting for Poissonian observations of the single-photon data, the nonlocal spatial correlations between pixels and the small number of depth layers inside the observed range window. An alternating direction method of multipliers that offers good convergence properties is used to solve this minimization problem. The resulting algorithm is validated on synthetic and real data and in challenging realistic scenarios including sparse photon regimes for fast imaging, the presence of high background due to obscurants, and the joint processing of multispectral and/or multitemporal data.

A Growth Behavior of Szegö Type Operators

We define new integral operators on the Haydy space similar to Szego projection. We show that these operators map from Hp to H2 for some 1 ≤ p 2, where the range of p is depending on a growth condition. To prove that, we generalize the Hausdorff-Young Theorem to multi-dimensional case.

A MULTIDIMENSIONAL SUBDIFFUSION MODEL WITH CHEMOTAXIS

The mathematical model for subdiffusion process with chemotaxis proposed by Langlands and Henry [1] for the one-dimensional case is extended to the multi-dimensional case. The model is derived from random walks process using a probability measure on a n-multidimensional unit ball $S^{n-1}$.

On the unique solvability for initial - boundary problems of vibrations of a beam, one end of which is fixed and the other is free, in the Sobolev classes in the multidimensional case

On the unique solvability for initial - boundary problems of vibrations of a beam, one end of which is fixed and the other is free, in the Sobolev classes in the multidimensional case