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An earlier paper proved the convergence of a variable stepsize Bregman operator splitting algorithm (BOSVS) for minimizing ø(Bu) + H(u), where H and ø are convex functions, and ø is possibly nonsmooth. The algorithm was shown to be relatively efficient when applied to partially parallel magnetic resonance image reconstruction problems. In this paper, the convergence rate of BOSVS is analyzed. When H(u) = ‖Au - f ‖2, where A is a matrix, it is shown that for an ergodic approximation uk obtained by averaging k BOSVS iterates, the error in the objective value ø(Buk)+H(uk) is O(1/k). When the optimization problem has a unique solution u*, we obtain the estimate ‖uk-u*‖ = O(1/ √ k). The theoretical analysis is compared to observed convergence rates for partially parallel magnetic resonance image reconstruction problems where A is a large dense ill-conditioned matrix. [ABSTRACT FROM AUTHOR]

This paper discusses convergence behavior of the nonlinear inexact Uzawa algorithm for solving saddle-point problems presented in a recent paper of Bramble, Pasciak, and Vassilev (SIAM J. Numer. Anal., 34 (1997), pp. 1072­1092). It is shown that this algorithm converges under a condition weaker than that stated in their paper. Key words: saddle-point problems; nonlinear inexact Uzawa algorithm; convergence behavior [ABSTRACT FROM AUTHOR]

Let F be a compact set of a Banach space X. This paper analyzes the "generalized empirical interpolation method," which, given a function f ∊ F, builds an interpolant Jn[f] in an n dimensional subspace Xn ⊂ X with the knowledge of n outputs (σi(f))ni=1, where σi ∊ X' and X' is the dual space of X. The space Xn is built with a greedy algorithm that is adapted to F in the sense that it is generated by elements of F itself. The algorithm also selects the linear functionals (σi)ni=1 from a dictionary Σ ⊂ X'. In this paper, we study the interpolation error maxf∊F ‖f - Jn[f]‖X by comparing it with the best possible performance on an n dimensional space, i.e., the Kolmogorov n-width of F in X, dn(F,X). For polynomial or exponential decay rates of dn(F,X), we prove that the interpolation error has the same behavior modulo the norm of the interpolation operator. Sharper results are obtained in the case where X is a Hilbert space. [ABSTRACT FROM AUTHOR]

Threshold dynamics and its extensions have proven useful in computing interfacial motions in applications as diverse as materials science and machine learning. Certain desirable properties of the algorithm, such as unconditional monotonicity in two-phase ows and gradient stability more generally, hinge on positivity properties of the convolution kernel and its Fourier transform. Recent developments in the analysis of this class of algorithms indicate that sometimes, as in the case of certain anisotropic curvature ows arising in materials science, these properties of the convolution kernel cannot be expected. Other applications, such as machine learning, would benefit from as great a level of exibility in choosing the convolution kernel as possible. In this paper, we establish certain desirable properties of threshold dynamics, such as gamma convergence of its associated energy, for a substantially wider class of kernels than has been hitherto possible. We also present variants of the algorithm that extend some of these properties to even wider classes of convolution kernels. [ABSTRACT FROM AUTHOR]

This paper is concerned with the development of well-balanced high order numerical schemes for systems of balance laws with a linear flux function, whose coefficients may be variable. First, well-balanced first order numerical schemes are obtained based on the use of exact solvers of Riemann problems that include both the flux and the source terms. Godunov's methods so obtained are extended to higher order schemes by using a technique of reconstruction of states. The main contribution of this paper is to introduce a reconstruction technique that preserves the well-balanced property of Godunov's methods. Some numerical experiments are presented to verify in practice the properties of the developed numerical schemes. [ABSTRACT FROM AUTHOR]

In this paper we consider the numerical solution of discrete boundary integral equations on polyhedral surfaces in three dimensions. When the solution contains typical edge singularities, highly stretched meshes are preferred to uniform meshes, since they reduce the number of degrees of freedom needed to obtain a fixed accuracy. The classical panel-clustering method can still be applied in the presence of such highly stretched meshes. However, we will show that the savings in computation time and storage become suboptimal because the nearfield matrix arising in the panel-clustering algorithm is no longer as sparse as it is in the case of uniform meshes. Hence, a natural question arises as to whether a new enhanced panel-clustering algorithm can be designed which performs efficiently even in the presence of highly stretched meshes. The main result of this paper is to formulate such an enhanced version of the panel-clustering algorithm. The key features of the algorithm are (i) the employment of partial analytic integration in the direction of stretching, yielding a new kernel function on a one-dimensional manifold where the influence of high aspect ratios in the stretched elements is removed, and (ii) the introduction of a generalized admissibility condition with respect to the partially integrated kernel, which ensures that certain stretched clusters which are inadmissible in the classical sense now become admissible. In the context of a model problem, we prove that our algorithm yields an accurate (up to the discretization error) matrix-vector multiplication which requires ...(NlogκN) operations, where N is the number of degrees of freedom and k is small and independent of the aspect ratio. The generalized admissibility condition can be viewed as an addition to the classical method which may be useful in general when stretched meshes are present. We also have performed a numerical experiment which shows that the sparsity of the nearfield matrix for the enhanced panel-clustering method is not negatively affected by stretched elements, and the method will perform optimally. [ABSTRACT FROM AUTHOR]

In this paper, an efficient and stable numerical algorithm for computing multiple saddle points with symmetries is developed by modifying the local minimax method established in [Y. Li and J. Zhou, SIAM J. Sci. Comput. 23 (2001), pp. 840--865; Y. Li and J. Zhou, SIAM J. Sci. Comput., 24 (2002), pp. 840--865]. First an invariant space is defined in a more general sense and a principle of invariant criticality is proved for the generalization. Then the orthogonal projection to the invariant space is used to preserve the invariance and to reduce computational error across iterations. Simple averaging formulas are used for the orthogonal projections. Numerical computations of examples with various symmetries, of which some can and others cannot be characterized by a compact group of linear isomorphisms, are carried out to confirm the theory and to illustrate applications. The mathematical features of various problems demonstrated in these examples fall into two categories: nodal solutions of saddle-point type with large Morse indices and nonradial positive solutions via symmetry breaking in radially symmetric elliptic problems. The new numerical algorithm generates these rather unstable solutions in an efficient and stable way. The existence of many unstable solutions and their behavior found in this paper remain to be investigated. [ABSTRACT FROM AUTHOR]

Local mesh-refining algorithms known from adaptive finite element methods are adopted for locally conservative and monotone finite volume discretizations of boundary value problems for steady-state convection-diffusion-reaction equations. The paper establishes residual-type explicit error estimators and averaging techniques for a posteriori finite volume error control with and without upwind in global H1- and L2-norms. Reliability and efficiency are verified theoretically and confirmed empirically with experimental support for the superiority of the suggested adaptive mesh-refining algorithms over uniform mesh refining. A discussion of adaptive computations in the simulation of contaminant concentration in a nonhomogeneous water reservoir concludes the paper. [ABSTRACT FROM AUTHOR]

The main purpose of this paper is to give numerical algorithms and the error analysis for delay quadratic problems in the calculus of variations. These methods are new, efficient, and accurate and have a global a priori error of O(h²), where h is the distance between any two successive node points. We also derive the results for the general, numerical, delay problem, but we focus on proving our results in the simpler quadratic case since the extra technical numerical details have been given previously by the second author. In addition, the authors have previously shown how to reformulate general delay constrained problems in optimal control theory/constrained calculus of variations as unconstrained delay problems. Thus our numerical results and methods will hold for these general constrained problems also. Finally, we note that our algorithm, which solves the stationary condition(s) numerically, avoids the more difficult problems of piecing the solution of second order equations together and requires less smoothness in the solution. Thus we replace difficult second order boundary value problems with the easier task of approximating definite integrals involving first order derivatives. [ABSTRACT FROM AUTHOR]

In this paper we show that the use of spectral Galerkin methods for the approximation of the Boltzmann equation in the velocity space permits one to obtain spectrally accurate numerical solutions at a reduced computational cost. We prove that the spectral algorithm preserves the total mass and approximates with infinite-order accuracy momentum and energy. Consistency of the method is also proved, and a stability result for a smoothed positive scheme is given. We demonstrate that the Fourier coefficients associated with the collision kernel of the equation have a very simple structure and in some cases can be computed explicitly. Numerical examples for homogeneous test problems in two and three dimensions confirm the advantages of the method. [ABSTRACT FROM AUTHOR]

In the first part of the paper, we introduce an overlapping mortar finite element method for solving two-dimensional elliptic problems discretized on overlapping nonmatching grids. We prove an optimal error bound and estimate the condition numbers of certain overlapping Schwarz preconditioned systems for the two-subdomain case. We show that the error bound is independent of the size of the overlap and the ratio of the mesh parameters. In the second part, we introduce three additive Schwarz preconditioned conjugate gradient algorithms based on the trivial and harmonic extensions. We provide estimates for the spectral bounds on the condition numbers of the preconditioned operators. We show that although the error bound is independent of the size of the overlap, the condition number does depend on it. Numerical examples are presented to support our theory. [ABSTRACT FROM AUTHOR]

This paper reports the multiscale analysis and numerical algorithms for a class of distributed elliptic optimal control problems with constraints. Multiscale asymptotic expansions are presented, and an explicit rate of convergence is derived. A multiscale numerical method is developed. Numerical experiments are carried out to validate the predicted convergence results. [ABSTRACT FROM AUTHOR]

This paper investigates backscatter data for the inverse obstacle problem in impedance tomography, when the obstacles are small. It is shown that under this circumstance the backscatter data are close approximations of a rational function that has second or fourth order poles at the locations of the obstacles. Furthermore, a numerical method is presented to locate the obstacles via the poles of certain Laurent-Padé approximations. Numerical experiments explore the potential of this algorithm also for extended obstacles, taking into consideration that the problem is severely ill-posed. [ABSTRACT FROM AUTHOR]

In this paper, a FETI-DP formulation for three dimensional elasticity on nonmatching grids over geometrically nonconforming subdomain partitions is considered. To resolve the nonconformity of the finite elements, a mortar matching condition is imposed on the subdomain interfaces (faces). A FETI-DP algorithm is then built by enforcing the mortar matching condition in dual and primal ways. In order to make the FETI-DP algorithm scalable, a set of primal constraints, which include average and momentum constraints over interfaces, are selected from the mortar matching condition. A condition number bound, C(1 + log(H/h))², is then proved for the FETI-DP formulation for the elasticity problems with discontinuous material parameters. Only some faces need to be chosen as primal faces on which the average and momentum constraints are imposed. Numerical results are included. [ABSTRACT FROM AUTHOR]

Discontinuous Galerkin (DG) and mixed finite element (MFE) methods are two popular methods that possess local mass conservation. In this paper we investigate DG-DG and DG-MFE domain decomposition couplings using mortar finite elements to impose weak continuity of fluxes and pressures on the interface. The subdomain grids need not match, and the mortar grid may be much coarser, giving a two-scale method. Convergence results in terms of the fine subdomain scale h and the coarse mortar scale H are established for both types of couplings. In addition, a nonoverlapping parallel domain decomposition algorithm is developed, which reduces the coupled system to an interface mortar problem. The properties of the interface operator are analyzed. [ABSTRACT FROM AUTHOR]

A well-known generalization of Shannon's sampling theorem states that a bandlimited function can be reconstructed from its periodic nonuniformly spaced samples if the effective sampling rate is at least the Nyquist rate. Analogous to Shannon's sampling theorem this generalization requires that an infinite number of samples be available, which, however, is never the case in practice. Most existing reconstruction methods for periodic nonuniform sampling yield very low order (often not even first order) accuracy when only a finite number of samples is given. In this paper we propose a fast, numerically robust, root-exponential accurate reconstruction method. The efficiency and accuracy of the algorithm is obtained by fully exploiting the sampling structure and utilizing localized Fourier analysis. We discuss applications in analog-to-digital conversion where nonuniform periodic sampling arises in various situations. Finally, we demonstrate the performance of our algorithm by numerical examples. [ABSTRACT FROM AUTHOR]

We consider two-dimensional elliptic problems with discontinuous coefficients discretized by the finite element method on geometrically conforming nonmatching triangulations across the interface using the mortar technique. The resulting discrete problem is solved by a dual-primal FETI method. In this paper we introduce and analyze a preconditioner with a special scaling of coefficients and step parameters and establish convergence bounds. We show that the preconditioner is almost optimal with constants independent of the jumps of coefficients and step parameters. Extensive computational evidence is presented that illustrates an almost optimal convergence for a variety of situations (distribution of subregions, grid assignment, grid ratios, number of subregions) for both continuous and discontinuous problems. [ABSTRACT FROM AUTHOR]

Multigrid algorithms for Co interior penalty methods for fourth order elliptic boundary value problems on polygonal domains are studied in this paper. It is shown that V -cycle, F-cycle and W-cycle algorithms are contractions if the number of smoothing steps is sufficiently large. The contraction numbers of these algorithms are bounded by Cm-α, where m is the number of presmoothing (and postsmoothing) steps, α is the index of elliptic regularity, and the positive constant C is mesh-independent. These estimates are established for a smoothing scheme that uses a Poisson solve as a preconditioner, which can be easily implemented because the Co finite element spaces are standard spaces for second order problems. Furthermore the variable V -cycle algorithm is also shown to be an optimal preconditioner. [ABSTRACT FROM AUTHOR]

Centroidal Voronoi tessellations (CVTs) are Voronoi tessellations of a bounded geometric domain such that the generating points of the tessellations are also the centroids (mass centers) of the corresponding Voronoi regions with respect to a given density function. Centroidal Voronoi tessellations may also be defined in more abstract and more general settings. Due to the natural optimization properties enjoyed by CVTs, they have many applications in diverse fields. The Lloyd algorithm is one of the most popular iterative schemes for computing the CVTs but its theoretical analysis is far from complete. In this paper, some new analytical results on the local and global convergence of the Lloyd algorithm are presented. These results are derived through careful utilization of the optimization properties shared by CVTs. Numerical experiments are also provided to substantiate the theoretical analysis. [ABSTRACT FROM AUTHOR]

In this paper we study the stability for all positive time of the fully implicit Euler scheme for the two-dimensional Navier—Stokes equations. More precisely, we consider the time discretization scheme and with the aid of the discrete Gronwall lemma and the discrete uniform Gronwall lemma we prove that the numerical scheme is stable. [ABSTRACT FROM AUTHOR]

We present and study a nonconforming domain decomposition method for the discretization of the three-dimensional Stokes problem in the velocity-pressure formulation. The approximation is based on some local mixed finite elements for nonmatching tetrahedral grids. The aim pursued is a systematic construction of the mortared discrete velocity space, the pressure being not subjected to any matching constraints across the interfaces. Using the bubble stabilization techniques, applied in Brezzi and Marini's paper to the three fields method [Math. Cornp., 70 (2001), pp. 911-934], allows us to define an algorithm which is easy to implement. The numerical analysis relies on the pressure-splitting argument of Boland and Nicolaides and allows us to establish an inf-sup condition with a constant that does not depend on the mesh size or on the total number of the subdomains. Then, by the Berger-Scott-Strang lemma written down for our saddle point system we derive optimal accuracy results. [ABSTRACT FROM AUTHOR]

Accurate numerical modeling of complex physical, chemical, and biological systems requires numerical simulation capability over a large range of length scales, with the ability to capture rapidly varying phenomena localized in space and/or time. Adaptive mesh refinement (AMR) is a numerical process for dynamically introducing local fine resolution on computational grids during the solution process, in response to unresolved error in a computation. Fast adaptive composite-grid (FAC) methods are a class of algorithms that exploit the multilevel structure of AMR grids to solve elliptic problems efficiently. This paper develops a theoretical foundation for AFACx, an asynchronous FAC method. A new multilevel condition number estimate establishes that the convergence rate of the AFACx algorithm does not degrade as the number of refinement levels in the AMR hierarchy increases. [ABSTRACT FROM AUTHOR]

Finding approximate solutions to systems of it nonlinear equations in it real variables is a much studied problem in numerical analysis. Somewhat more recently, researchers have developed numerical methods to provide mathematically rigorous error bounds on such solutions. (We say that we "verify" existence of the solution within those bounds on the variables.) However, when the Jacobi matrix is singular at the solution, no computational techniques to verify existence can handle the general case. Nonetheless, computational verification that one or more solutions exists within a region in complex space containing the real bounds is possible by computing the topological degree. In a previous paper, we presented theory and algorithms for the simplest case, when the rank-defect of the Jacobian matrix at the solution is 1 and the topological index is 2. Here, we generalize that result to arbitrary topological index d ≥ 2: We present theory, algorithms, and experimental results. We also present a heuristic for determining the degree, obtaining a value that we can subsequently verify with our algorithms. Although execution times are slow compared to corresponding bound verification processes for nonsingular systems, the order with respect to system size is still cubic. [ABSTRACT FROM AUTHOR]

In this paper, we propose a nonoverlapping domain decomposition method for solving the three-dimensional Maxwell equations, based on the edge element discretization. For the Schur complement system on the interface, we construct an efficient preconditioner by introducing two special coarse subspaces defined on the nonoverlapping sub domains. It is shown that the condition number of the preconditioned system grows only polylogarithmically with the ratio between the subdomain diameter and the finite element mesh size but possibly depends on the jumps of the coefficients. [ABSTRACT FROM AUTHOR]

The mortar methods are based on domain decomposition and they allow for the coupling of different variational approximations in different subdomains. The resulting methods are nonconforming but still yield optimal approximations. In this paper, we will discuss iterative substructuring algorithms for the algebraic systems arising from the discretization of symmetric, second-order, elliptic equations in two dimensions. Both spectral and finite element methods, for geometrically conforming as well as nonconforming domain decompositions, are studied. In each case, we obtain a polylogarithmic bound on the condition number of the preconditioned matrix. [ABSTRACT FROM AUTHOR]

In this paper, we study the additive Schwarz method for the h-p version of the finite element method in three dimensions. The main idea is to treat separately the h-version (linear) components and the p-version (high-order) components by a vertex-based method. It can also be viewed as a three-level method with the level being the linear finite element approximation on the coarse mesh, the linear finite element approximation on the fine mesh, and the high-order finite element approximation on the fine mesh, respectively. The resulting algorithm can be implemented in parallel on the subdomain level for the h-version components and on the element level for the p-version components. The condition number is of order [This symbol cannot be presented in ASCII format](1 + ln Hipi/hi)⇔2, where Hi stands for the diameter of the subdomain Ωi, hi is the diameter of the elements in Ωi, and pi is the maximum of the polynomial degrees used in Ωi. [ABSTRACT FROM AUTHOR]

In this paper the problem of computing bifurcation diagrams for large-scale nonlinear parameter-dependent steady state systems which arise following the spatial discretization of semilinear PDEs is investigated. A continuation algorithm which employs a preconditioned version of the recursive projection method (RPM) is presented. The RPM is often expensive when it is used in conjunction with the numerical method of lines. Preconditioning the Jacobian of the underlying fixed point operator results in an algorithm (the preconditioned recursive projection method (PRPM)) which is capable of efficiently computing equilibrium solution diagrams of large stiff systems. For many PDE problems the PRPM is a fast and effective means of detecting both steady state and Hopf bifurcation along a branch of solutions. A description of the performance of the PRPM when applied to two numerical examples is given. [ABSTRACT FROM AUTHOR]

A cell-centered finite volume method is proposed to approximate numerically the solution to the steady convection-diffusion equation on unstructured meshes of $d$-simplexes, where $d\geq 2$ is the spatial dimension. The method is formally second-order accurate by means of a piecewise linear reconstruction within each cell and at mesh vertices. An algorithm is provided to calculate nonnegative and bounded weights. Face gradients, required to discretize the diffusive fluxes, are defined by a nonlinear strategy that allows us to demonstrate the existence of a maximum principle. Finally, a set of numerical results documents the performance of the method in treating problems with internal layers and solutions with strong gradients. [ABSTRACT FROM AUTHOR]

The hp-adaptive approximation is formulated as an approximation problem on a full binary tree T, where for each of the leaves Δ an order p(Δ ) ≥ 1 is assigned in such a way that the sum of all orders p(Δ ) does not exceed N, which is called the complexity of the approximation. The leaves Δ correspond to the cells of the partition, while p(Δ ) is the dimension of the polynomial space used for the local approximation on Δ . Devising an incremental algorithm for near-best adaptive approximation for the problem of finding the best possible tree T and assignments p(Δ ) leads to building a construction that attaches a ghost tree with p(Δ ) leaves to each leaf Δ of T with p(Δ ) > 1. The resulting full binary tree τ has at most N leaves and can be used as a proxy of T for assembling hp-adaptive procedures. Under the standard assumptions about the local errors, we prove that the error of our approximation of complexity N is bounded by 2N-1 N-n+1σ n, where σ n, n ≤ N, is the error of the best possible approximation of complexity n. [ABSTRACT FROM AUTHOR]

We develop an a posteriori analysis of C0 interior penalty methods for the displacement obstacle problem of clamped Kirchhoff plates. We show t hat a residual based error estimator originally designed for C0 interior penalty methods for the bound ary value problem of clamped Kirchhoff plates can also be used for the obstacle problem. We obtain reliability and efficiency estimates for the error estimator and introduce an adaptive algorithm based on this error estimator. Numerical results indicate that the performance of the adaptive algorithm is optimal for both quadratic and cubic C0 interior penalty methods. [ABSTRACT FROM AUTHOR]

The Laplace Transform is frequently encountered in mathematics, physics, engineering, and other fields. However, the spectral properties of the Laplace Transform tend to complicate its numerical treatment; therefore, the closely related "Truncated" Laplace Transforms are often used in applications. We have constructed efficient algorithms for the evaluation of the left singular functions and singular values of the Truncated Laplace Transform. Together with the previously introduced algorithms for the evaluation of the right singular functions, these algorithms provide the singular value decomposition of the Truncated Laplace Transform. The resulting algorithms are applicable to all environments likely to be encountered in applications, including the evaluation of singular functions corresponding to extremely small singular values (e.g., 10-1000). [ABSTRACT FROM AUTHOR]

Hidden-variable resultant methods are a class of algorithms for solving multidimensional polynomial rootfinding problems. In two dimensions, when significant care is taken, they are competitive practical rootfinders. However, in higher dimensions they are known to miss zeros, calculate roots to low precision, and introduce spurious solutions. We show that the hidden variable resultant method based on the Cayley (Dixon or Bézout) matrix is inherently and spectacularly numerically unstable by a factor that grows exponentially with the dimension. We also show that the Sylvester matrix for solving bivariate polynomial systems can square the condition number of the problem. In other words, two popular hidden variable resultant methods are numerically unstable, and this mathematically explains the difficulties that are frequently reported by practitioners. Regardless of how the constructed polynomial eigenvalue problem is solved, severe numerical difficulties will be present. Along the way, we prove that the Cayley resultant is a generalization of Cramer's rule for solving linear systems and generalize Clenshaw's algorithm to an evaluation scheme for polynomials expressed in a degree-graded polynomial basis. [ABSTRACT FROM AUTHOR]

We introduce a new iterative algorithm to find sparse solutions of underdetermined linear systems. The algorithm, a simple combination of the Iterative Hard Thresholding algorithm and the Compressive Sampling Matching Pursuit algorithm, is called Hard Thresholding Pursuit. We study its general convergence and notice in particular that only a finite number of iterations are required. We then show that, under a certain condition on the restricted isometry constant of the matrix of the linear system, the Hard Thresholding Pursuit algorithm indeed finds all s-sparse solutions. This condition, which reads δ3s < 1/√3, is heuristically better than the sufficient conditions currently available for other compressive sensing algorithms. It applies to fast versions of the algorithm, too, including the Iterative Hard Thresholding algorithm. Stability with respect to sparsity defect and robustness with respect to measurement error are also guaranteed under the condition δ3s < 1/√3. We conclude with some numerical experiments to demonstrate the good empirical performance and the low complexity of the Hard Thresholding Pursuit algorithm. [ABSTRACT FROM AUTHOR]

We propose a fast algorithm for the solution of the nonlinear boundary integral equation resulting from a reformulation of a boundary value problem of the Laplace equation with nonlinear boundary conditions. The fast algorithm is developed by using the multilevel augmentation method (introduced recently by Chen, Wu, and Xu for general nonlinear integral equations), in conjunction with a matrix truncation strategy, and an error control technique of numerical integrations for integrals appeared in the process of solving the equation. We prove that the proposed algorithm has an optimal convergence order (up to a logarithmic factor) and a nearly linear computational complexity order (measured in the number of multiplications and functional evaluations). Numerical experiments are presented to demonstrate its approximation accuracy and computational efficiency, verifying the theoretical estimates, and to compare performance of the proposed algorithm with that of the Atkinson and Chandler algorithm. [ABSTRACT FROM AUTHOR]

The solution set V of a polynomial system, i.e., the set of common zeroes of a set of multivariate polynomials with complex coefficients, may contain several components, e.g., points, curves, surfaces, etc. Each component has attached to it a number of quantities, one of which is its dimension. Given a numerical approximation to a point p on the set V, this article presents an efficient algorithm to compute the maximum dimension of the irreducible components of V which pass through p, i.e., a local dimension test. Such a test is a crucial element in the homotopy-based numerical irreducible decomposition algorithms of Sommese, Verschelde, and Wampler. This article presents computational evidence to illustrate that the use of this new algorithm greatly reduces the cost of so-called "junk-point filtering," previously a significant bottleneck in the computation of a numerical irreducible decomposition. For moderate size examples, this results in well over an order of magnitude improvement in the computation of a numerical irreducible decomposition. As the computation of a numerical irreducible decomposition is a fundamental backbone operation, gains in efficiency in the irreducible decomposition algorithm carry over to the many computations which require this decomposition as an initial step. Another feature of a local dimension test is that one can now compute the irreducible components in a prescribed dimension without first computing the numerical irreducible decomposition of all higher dimensions. For example, one may compute the isolated solutions of a polynomial system without having to carry out the full numerical irreducible decomposition. [ABSTRACT FROM AUTHOR]

We study numerical methods for a coupled Navier-Stokes/Darcy model which describes a fluid flow filtrating through porous media. A decoupled and linearized two-grid algorithm is proposed. Numerical analysis and experiments are presented to show the efficiency and effectiveness of the decoupled and linearized algorithm. [ABSTRACT FROM AUTHOR]

The author proposes stochastic approximation methods of finding the optimal measure change by the exponential tilting for Lévy processes in Monte Carlo importance sampling variance reduction. In accordance with the structure of the underlying Lévy measure, either a constrained or unconstrained algorithm of the stochastic approximation is chosen. For both cases, the almost sure convergence to a unique stationary point is proved. Numerical examples are presented to illustrate the effectiveness of our method. [ABSTRACT FROM AUTHOR]

A BDDC (balancing domain decomposition by constraints) method is developed for elliptic equations, with discontinuous coefficients, discretized by mortar finite element methods for geometrically nonconforming partitions in both two and three space dimensions. The coarse component of the preconditioner is defined in terms of one mortar constraint for each edge/face, which is the intersection of the boundaries of a pair of subdomains. A condition number bound of the form C maxi{(1 + log(Hi/hi))2} is established under certain assumptions on the geometrically nonconforming subdomain partition in the three-dimensional case. Here Hi and hi are the subdomain diameters and the mesh sizes, respectively. In the geometrically conforming case and the geometrically nonconforming cases in two dimensions, no assumptions on the subdomain partition are required. This BDDC preconditioner is also shown to be closely related to the Neumann-Dirichlet version of the FETI-DP algorithm. The results are illustrated by numerical experiments which confirm the theoretical results. [ABSTRACT FROM AUTHOR]

We present a new fast-marching algorithm for an eikonal equation with a velocitychanging sign. This first order equation models a front propagation in the normal direction. The algorithm is an extension of the fast-marching method in two respects. The first is that the new scheme can deal with a time-dependent velocity, and the second is that there is no restriction on its change in sign. We analyze the properties of the algorithm, and we prove its convergence in the class of discontinuous viscosity solutions. Finally, we present some numerical simulations of fronts propagating in ℝ². [ABSTRACT FROM AUTHOR]

In the theory for domain decomposition algorithms of the iterative substructuring family, each subdomain is typically assumed to be the union of a few coarse triangles or tetrahedra. This is an unrealistic assumption, in particular if the subdomains result from the use of a mesh partitioner, in which case they might not even have uniformly Lipschitz continuous boundaries. The purpose of this study is to derive bounds for the condition number of these preconditioned conjugate gradient methods which depend only on a parameter in an isoperimetric inequality, two geometric parameters characterizing John and uniform domains, and the maximum number of edges of any subdomain. A related purpose is to explore to what extent well-known technical tools previously developed for quite regular subdomains can be extended to much more irregular subdomains. Some of these results are valid for any John domain, while an extension theorem, which is needed in this study, requires that the subdomains have complements which are uniform. The results, so far, are complete only for problems in two dimensions. Details are worked out for a FETI-DP algorithm and numerical results support the findings. Some of the numerical experiments illustrate that care must be taken when selecting the scaling of the preconditioners in the case of irregular subdomains. [ABSTRACT FROM AUTHOR]

This work develops adaptive time stepping algorithms for the approximation of a functional of a diffusion with jumps based on a jump augmented Monte Carlo Euler-Maruyama method, which achieve a prescribed precision. The main result is the derivation of new expansions for the time discretization error, with computable leading order term in a posteriori form, which are based on stochastic flows and discrete dual backward functions. Combined with proper estimation of the statistical error, they lead to efficient and accurate computation of global error estimates, extending the results by A. Szepessy, R. Tempone, and G. E. Zouraris [Comm. Pure Appl. Math., 54 (2001), pp. 1169-1214]. Adaptive algorithms for either deterministic or trajectory-dependent time stepping are proposed. Numerical examples show the performance of the proposed error approximations and the adaptive schemes. [ABSTRACT FROM AUTHOR]

A new approximate mortar condition is proposed for the lowest order Crouzeix-Raviart finite element on nonmatching grids, which uses only the nodal values on the interface for the calculation of the mortar projection. This approach allows for improved and more flexible algorithms compared to those for the standard mortar condition where nodal values in the interior of a subdomain, those closest to a mortar side of the subdomain, are also required in the calculation. [ABSTRACT FROM AUTHOR]

The original fast sweeping method, which is an efficient iterative method for stationary Hamilton--Jacobi equations, relies on natural ordering provided by a rectangular mesh. We propose novel ordering strategies so that the fast sweeping method can be extended efficiently and easily to any unstructured mesh. To that end we introduce multiple reference points and order all the nodes according to their lp-metrics to those reference points. We show that these orderings satisfy the two most important properties underlying the fast sweeping method: (1) these orderings can cover all directions of information propagating efficiently; (2) any characteristic can be decomposed into a finite number of pieces and each piece can be covered by one of the orderings. We prove the convergence of the new algorithm. The computational complexity of the algorithm is nearly optimal in the sense that the total computational cost consists of O(M) flops for iteration steps and O(MlogM) flops for sorting at the predetermined initialization step which can be efficiently optimized by adopting a linear time sorting method, where M is the total number of mesh points. Extensive numerical examples demonstrate that the new algorithm converges in a finite number of iterations independent of mesh size. [ABSTRACT FROM AUTHOR]

Attenuated Radon projections with respect to the weight function Wµ(x, y) = (1 - x² - y²)µ-½ are shown to be closely related to the orthogonal expansion in two variables with respect to Wµ. This leads to an algorithm for reconstructing two-dimensional functions (images) from attenuated Radon projections. Similar results are established for reconstructing functions on the sphere from projections described by integrals over circles on the sphere, and for reconstructing functions on the three-dimensional ball and cylinder domains. [ABSTRACT FROM AUTHOR]

A primal-based penalty preconditioner is presented for a linear set of equations arising from elliptic saddle point problems. We show that the eigenvalues of the preconditioned matrix are positive real and demonstrate that a variant of the preconditioner can be combined with the conjugate gradient algorithm. Our approach is motivated by two basic observations. First, the solution of a problem with constraints is often similar to the solution of a problem where the constraints are penalized. Second, certain methods of solution not available for a constrained problem are possible for its penalized counterpart so motivating a primal-based Schur complement approach. Numerical examples for elliptic two- and three-dimensional problems are presented that confirm theoretical results and demonstrate the effectiveness of the preconditioner. [ABSTRACT FROM AUTHOR]

A new monotone finite difference scheme is introduced that approximates viscosity solutions of first-order nonlinear Hamilton-Jacobi equations. The main feature of the scheme is that it allows for locally varying time and space grids, making it ideal for use with adaptive algorithms. Explicit a priori error estimates are given to establish convergence. Numerical examples, including adaptive mesh refinement examples, demonstrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

We consider the behavior of certain adaptive timestepping methods, based upon embedded explicit Runge--Kutta pairs, when applied to dissipative ODEs. It has been observed numerically that the standard local error controls can impart desirable stability properties, but this has been rigorously verified only for very special, low-order, Runge--Kutta pairs. The rooted-tree expansion of a certain quadratic form, central to the stability theory of Runge--Kutta methods, is derived. This, together with key assumptions on the sequence of accepted time-steps and the local error estimate, provides a general explanation for the observed stability of such algorithms on dissipative problems. Under these assumptions, which are expected to hold for "typical" numerical trajectories, two different results are proved. First, for a large class of embedded Runge--Kutta pairs of order $(1,2)$, controlled on an error-per-unit-step basis, all such numerical trajectories will eventually enter a particular bounded set. This occurs for sufficiently small tolerances independent of the initial conditions. Second, for pairs of arbitrary orders $(p-1,p)$, operating under either error-per-step or error-per-unit-step control, similar results are obtained when an additional structural assumption (that should be valid for many cases of interest) is imposed on the dissipative vector field. Numerical results support both the analysis and the assumptions made. [ABSTRACT FROM AUTHOR]