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The article discusses research featured in the Expository Research Papers section including one by Laurent Demanet and Lexing Ying on the efficient representations for functions of elliptic operators and another by Jeffrey Blanchard, Coralia Cartis and Jared Tanner on restricted isometry property.

It is shown that bubbling on wine bottle labels is due to absorption of water from the glue, with subsequent hygroscopic expansion. Contrary to popular belief, most of the glue's water must be lost to the atmosphere rather than to the paper. A simple lubrication model is developed for spreading glue piles in the pressure chamber of the labeling machine. This model predicts a maximum rate for application of labels. Buckling theory shows that the current arrangement of periodic glue strips can indeed accommodate paper expansion. This project provides interesting applications of various areas of undergraduate mathematics, such as trigonometry, Maclaurin series, dimensional analysis, and fluid mechanics. It illustrates that simple mathematical modeling may provide insight into complicated real-world problem. [ABSTRACT FROM AUTHOR]

In this paper we propose and analyze a new, fast method for the numerical solution of time domain boundary integral formulations of the wave equation. We employ Lubich's convolution quadrature method for the time discretization and a Galerkin boundary element method for the spatial discretization. The coefficient matrix of the arising system of linear equations is a triangular block Toeplitz matrix. Possible choices for solving the linear system arising from the above discretization include the use of fast Fourier transform (FFT) techniques and the use of data-sparse approximations. By using FFT techniques, the computational complexity can be reduced substantially while the storage cost remains unchanged and is, typically, high. Using data-sparse approximations, the gain is reversed; i.e., the computational cost is (approximately) unchanged while the storage cost is substantially reduced. The method proposed in this paper combines the advantages of these two approaches. First, the discrete convolution (related to the block Toeplitz system) is transformed into the (discrete) Fourier image, thereby arriving at a decoupled system of discretized Helmholtz equations with complex wave numbers. A fast data-sparse (e.g., fast multipole or panel-clustering) method can then be applied to the transformed system. Additionally, significant savings can be achieved if the boundary data are smooth and time-limited. In this case the right-hand sides of many of the Helmholtz problems are almost zero, and hence can be disregarded. Finally, the proposed method is inherently parallel. We analyze the stability and convergence of these methods, thereby deriving the choice of parameters that preserves the convergence rates of the unperturbed convolution quadrature. We also present numerical results which illustrate the predicted convergence behavior. [ABSTRACT FROM AUTHOR]

In this paper, we study the relation between the error estimate of the bilinear interpolation on a general quadrilateral and the geometric characters of the quadrilateral. Some explicit bounds of the interpolation error are obtained based on some sharp estimates of the integral over 1/∣J∣p-1 for 1 ≤ p≤∞ on the reference element, where J is the Jacobian of the nonaffine mapping. This allows us to introduce weak geometric conditions (depending on p) leading to interpolation error estimates in the W1,p norm, for any p ϵ [1,∞), which can be regarded as a generalization of the regular decomposition property (RDP) condition introduced in [G. Acosta and R. G. Durán, SIAM J. Numer. Anal., 38 (2000), pp. 1073-1088] for p = 2 and new RDP conditions (NRDP) for p ≠ 2. We avoid the use of the reference family elements, which allows us to extend the results to a larger class of elements and to introduce the NRDP condition in a more unified way. As far as we know, the mesh condition presented in this paper is weaker than any other mesh conditions proposed in the literature for any p with 1 ≤ p≤∞. [ABSTRACT FROM AUTHOR]

In their 2006 paper, Chernyshenko et al. [J. Math. Phys., 48 (2007), 065204, 15 pp]. prove that a sufficiently smooth strong solution of the 3D Navier-Stokes equations is robust with respect to small enough changes in initial conditions and forcing function. They also show that if a regular enough strong solution exists, then Galerkin approximations converge to it. They then use these results to conclude that the existence of a sufficiently regular strong solution can be verified using sufficiently refined numerical computations. In this paper we study the strong solutions with less regularity than those considered in Chernyshenko et al. [J. Math. Phys., 48 (2007), 065204, 15 pp]. We prove a similar robustness result and show the validity of the results relating convergent numerical computations and the existence of the strong solutions. [ABSTRACT FROM AUTHOR]

The Lloyd algorithm originated in the context of optimal quantization and represents a fixed point iteration for computing an optimal quantizer. Reducing average distortion at every step, it constructs a Voronoi partition of the domain and replaces each generator with the centroid of the corresponding Voronoi cell. Optimal quantization is obtained in the case of a centroidal Voronoi tessellation (CVT), which is a special Voronoi tessellation of a domain Ω ϵ ℝd having the property that the generators of the Voronoi diagram are also the centers of mass, with respect to a given density function ? ⩾ 0, of the corresponding Voronoi cells. The Lloyd iteration is currently the most popular and elegant algorithm for computing CVTs and optimal quantizers, but many questions remain about its convergence, especially in d-dimensional spaces (d > 1). In this paper, we prove that any limit point of the Lloyd iteration in any dimensional spaces is nondegenerate provided that Ω is a convex and bounded set and ? belongs to L¹(Ω) and is positive almost everywhere. This ensures that the fixed point map remains closed and hence the standard theory of descent methods guarantees weak global convergence of the Lloyd iteration to the set of nondegenerate fixed point quantizers. While previously only conjectured, the convergence properties of the Lloyd iteration are rigorously justified under such minimal regularity assumptions on the density functional. The results presented in this paper go beyond existing convergence theories for CVTs and optimal quantization related algorithms and should be of interest to both the mathematical and engineering communities. [ABSTRACT FROM AUTHOR]

For the first time, we present for the general case of fully nonlinear elliptic differential equations of second order a nonstandard C¹ finite element method (FEM). We consider, throughout the paper, two cases in parallel: For convex, bounded, polyhedral domains in Rn, or for C² bounded domains in R², we prove stability and convergence for the corresponding conforming or nonconforming C¹ FEM, respectively. The results for equations and systems of orders 2 and 2m and quadrature approximations appear elsewhere. The classical theory of discretization methods is applied to the differential operator or the combined differential and the boundary operator. The consistency error for satisfied or violated boundary conditions on polyhedral or curved domains has to be estimated. The stability has to be proved in an unusual way. This is the hard core of the paper. Essential tools are linearization, a compactness argument, the interplay between the weak and strong form of the linearized operator, and a new regularity result for solutions of finite element equations. An essential basis for our proofs are Davydov's results for C¹ FEs on polyhedral domains in Rn or of local degree 5 for C² domains in R². Better convergence and extensions to Rn for C² domains are to be expected from his forthcoming results on curved domains. Our proof for the second case in Rn, includes the first essentially as a special case. The method applies to quasi-linear elliptic problems not in divergence form as well. A discrete Newton method is shown to converge locally quadratically, essentially independently of the actual grid size by the mesh independence principle. [ABSTRACT FROM AUTHOR]

In this paper several Nyström methods for the van der Pol equation are considered. In an earlier study by Cai, Aoyagi, and Abe it was shown that the second order Nyström, or leapfrog, method fails to approximate the limit cycle of the van der Pol equation, exhibiting a periodic modulation of the amplitude and sporadic high frequency noise instead. Cai et al. did a linear analysis and concluded that the spurious behavior was due to the interaction of the main part of the solution with a high frequency computational mode. In this paper we also apply a third and fourth order Nyström method to the van der Pol equation. Numerical experiments show that in these cases the high frequency mode causes blowup after some time. The onset of the instability can be delayed by decreasing the time step. We also improve on their analysis of the second order scheme by doing a nonlinear analysis, to wit a discrete multiple scales analysis. By this means we are able to explain the spurious behavior of this system completely. [ABSTRACT FROM AUTHOR]

In the first part of this paper we study the regularity properties of solutions of initial- or boundary-value problems of linear Fredholm integro-differential equations with weakly singular or other nonsmooth kernels. We then use these results in the analysis of a piecewise polynomial collocation method for solving such problems numerically. The main purpose of the paper is the derivation of optimal global convergence estimates and the analysis of the attainable order of convergence of numerical solutions for all values of the nonuniformity parameter of the underlying grid. [ABSTRACT FROM AUTHOR]

Over the last few years a great effort has been made to develop monotone high order explicit Runge--Kutta methods by means of their Shu--Osher representations. In this context, the stepsize restriction to obtain numerical monotonicity is normally computed using the optimal representation. In this paper we extend the Shu--Osher representations for any Runge--Kutta method giving sufficient conditions for monotonicity. We show how optimal Shu--Osher representations can be constructed from the Butcher tableau of a Runge--Kutta method. The optimum stepsize restriction for monotonicity is given by the radius of absolute monotonicity of the Runge--Kutta method [L. Ferracina and M. N. Spijker, SIAM J. Numer. Anal., 42 (2004), pp. 1073--1093], and hence if this radius is zero, the method is not monotone. In the Shu--Osher representation, methods with zero radius require negative coefficients, and to deal with them, an extra associate problem is considered. In this paper we interpret these schemes as representations of perturbed Runge--Kutta methods. We extend the concept of radius of absolute monotonicity and give sufficient conditions for monotonicity. Optimal representations can be constructed from the Butcher tableau of a perturbed Runge--Kutta method. [ABSTRACT FROM AUTHOR]

In this paper we investigate numerical methods for solving hyperbolic conservation laws based on finite volumes and optimal recovery. These methods can, for example, be applied in certain ENO schemes. Their approximation properties depend in particular on the reconstruction from cell averages. Hence, this paper is devoted to prove convergence results for such reconstruction processes from cell averages. [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]

In our papers [Inverse Problems, 15 (1999), pp. 309--327] and [Numer. Math., 88 (2001), pp. 347--365] we proposed algorithm {\tt REGINN}, an inexact Newton iteration for the stable solution of nonlinear ill-posed problems. {\tt REGINN} consists of two components: the outer iteration, which is a Newton iteration stopped by the discrepancy principle, and an inner iteration, which computes the Newton correction by solving the linearized system. The convergence analysis presented in both papers covers virtually any linear regularization method as inner iteration, especially Landweber iteration, $\nu$-methods, and Tikhonov--Phillips regularization. In the present paper we prove convergence rates for {\tt REGINN} when the conjugate gradient method, which is nonlinear, serves as inner iteration. Thereby we add to a convergence analysis of {Hanke}, who had previously investigated {\tt REGINN} furnished with the conjugate gradient method [Numer. Funct. Anal. Optim., 18 (1997), pp. 971--993]. By numerical experiments we illustrate that the conjugate gradient method outperforms the $\nu$-method as inner iteration. [ABSTRACT FROM AUTHOR]

We consider processes in which a focused laser beam is used to induce the melting of silicium. The first goal of this paper is to propose a simple three-dimensional (3D) model of this melting process. Our model is partly based on an energy balance equation. This model leads to a nontrivial ODE describing the evolution in time of the dimension of the melt region. The second goal of this paper is to obtain approximate analytical solutions of this ODE. After using basic solution methods, we propose an original geometrical method to derive asymptotic solutions for time → ∞. These solutions turn out to be the most useful for the description of this process. [ABSTRACT FROM AUTHOR]

This paper continues the analysis started in the first part of this article (cf. [J. J. L. Velázquez, SIAM J. Appl. Math., 64 (2004), pp. 1198-1223]). It was seen there, using the method of matched asymptotics, that a regularized version of the Keller-Segel system admits, for a suitable asymptotic limit, solutions with some regions of high concentrations for the cell density. This paper considers the relation between the phenomenon of blow-up for the limit problem and the dynamics of the concentration regions described in [J. J. L. Velázquez, SIAM J. Appl. Math., 64 (2004), pp. 1198- 1223]. In particular, this paper analyzes the precise way in which the regularization introduced in the Keller-Segel system stops the aggregation process and yields the formation of concentration regions. [ABSTRACT FROM AUTHOR]

In this paper, we consider the finite-dimensional approximations of Tikhonov regularization for nonlinear ill-posed problems with approximately given right-hand sides. We propose an a posteriori parameter choice strategy, which is a modified form of Morozov's discrepancy principle, to choose the regularization parameter. Under certain assumptions on the nonlinear operator, we obtain the convergence and rates of convergence for Tikhonov regularized solutions. This paper extends the results, which were developed by Plato and Vainikko in 1990 for solving linear ill-posed equations, to nonlinear problems. [ABSTRACT FROM AUTHOR]

This paper develops a least-squares approach to the solution of the incompressible Navier­Stokes equations in primitive variables. As with our earlier work on Stokes equations, we recast the Navier­Stokes equations as a first-order system by introducing a velocity-flux variable and associated curl and trace equations. We show that a least-squares principle based on L2 norms applied to this system yields optimal discretization error estimates in the H1 norm in each variable, including the velocity flux. An analogous principle based on the use of an H-1 norm for the reduced system (with no curl or trace constraints) is shown to yield similar estimates, but now in the L2 norm for velocity-flux and pressure. Although the H-1 least-squares principle does not allow practical implementation, these results are critical to the analysis of a practical least-squares method for the reduced system based on a discrete equivalent of the negative norm. A practical method of this type is the subject of a companion paper. Finally, we establish optimal multigrid convergence estimates for the algebraic system resulting from the L2 norm approach. [ABSTRACT FROM AUTHOR]

A new technique to solve elliptic linear PDEs, called ultra weak variational formulation (UWVF) in this paper, is introduced in [B. Després, C. R. Acad. Sci. Paris, 318 (1994), pp. 939–944]. This paper is devoted to an evaluation of the potentialities of this technique. It is applied to a model wave problem, the two-dimensional Helmholtz problem. The new method is presented in three parts following the same style of presentation as the classical one of the finite elements method, even though they are definitely conceptually different methods. The first part is committed to the variational formulation and to the continuous problem. The second part defines the discretization process using a Galerkin procedure. The third part actually studies the efficiency of the technique from the order of convergence point of view. This is achieved using theoretical proofs and a series of numerical experiments. In particular, it is proven and shown the order of convergence is lower bounded by a linear function of the number of degrees of freedom. An application to scattering problems is presented in a fourth part. [ABSTRACT FROM AUTHOR]

Compressed sensing (CS) seeks to recover an unknown vector with N entries by making far fewer than N measurements; it posits that the number of CS measurements should be comparable to the information content of tile vector, not simply N. CS combines directly the important task of compression with the measurement task. Since its introduction in 2004 there have been hundreds of papers on CS, a large fraction of which develop algorithms to recover a signal from its compressed measurements. Because of the paradoxical nature of CS--exact reconstruction from seemingly undersampled measurements--it is crucial for acceptance of an algorithm that rigorous analyses verify the degree of undersampling the algorithm permits. The restricted isometry property (RIP) has become the dominant tool used for the analysis in such cases. We present here an asymmetric form of RIP that gives tighter bounds than the usual symmetric one. We give the best known bounds on the RIP constants for matrices from the Gaussian ensemble. Our derivations illustrate the way in which the combinatorial nature of CS is controlled. Our quantitative bounds on the RIP allow precise statements as to how aggressively a signal can be undersampled, the essential question for practitioners. We also document the extent to which RIP gives precise information about the true performance limits of CS, by comparison with approaches from high-dimensional geometry. [ABSTRACT FROM AUTHOR]

This paper is concerned with delay-independent asymptotic stability of linear neutral delay differential-algebraic equations and linear multistep methods. We first give some sufficient conditions for the delay-independent asymptotic stability of these equations. Then we study and derive a sufficient and necessary condition for the delay-independent asymptotic stability of numerical solutions obtained by linear multistep methods combined with Lagrange interpolation. Finally, one numerical example is performed to confirm our theoretical result. [ABSTRACT FROM AUTHOR]

In this paper, we propose a uniaxial perfectly matched layer (PML) method for solving the tilne-harnlonic scattering problems ill two-layered media. The exterior region of the scatterer is divided into two half spaces by all infinite plane, on two sides of which the wave number takes different vahms. We surround the conlputational donmin where the scattering field is interested by a PML with the uniaxial medium property. By imposing homogeneous boundary condition on the outer boundary of the PML, we show that the solution of the PML problem converges exponentially to the solution of the original scattering problem in the computational dolnain as either the PML absorbing coefficient or the thickness of the PML tends to infinity. [ABSTRACT FROM AUTHOR]

The affine rank minimization problem consists of finding a matrix of minimum rank that satisfies a given system of linear equality constraints. Such problems have appeared in the literature of a diverse set of fields including system identification and control, Euclidean embedding, and collaborative filtering. Although specific instances can often be solved with specialized algorithms, the general affine rank minimization problem is NP-hard because it contains vector cardinality minimization as a special case. In this paper, we show that if a certain restricted isometry property holds for the linear transformation defining the constraints, the minimum-rank solution can be recovered by solving a convex optimization problem, namely, the minimization of the nuclear norm over the given affine space. We present several random ensembles of equations where the restricted isometry property holds with overwhelming probability, provided the codimension of the subspace is sufficiently large. The techniques used in our analysis have strong parallels in the compressed sensing framework. We discuss how affine rank minimization generalizes this preexisting concept and outline a dictionary relating concepts from cardinality minimization to those of rank minimization. We also discuss several algorithmic approaches to minimizing the nuclear norm and illustrate our results with numerical examples. [ABSTRACT FROM AUTHOR]

In two earlier articles, we provided sufficient conditions on (mass action) reaction network structure for the preclusion of multiple positive steady states in the context of what chemical engineers call the continuous flow stirred tank reactor. In such reactors, all species are deemed to be present in the effluent stream, a fact which played a strong role in the proofs. When certain species are deemed to be entrapped within the reactor, the questions that must be asked are more subtle, and the mathematics becomes substantially more difficult. Here we extend results of the earlier papers to semiopen reactors and show that very similar results obtain, provided that the network of chemical reactions satisfies certain weak structural conditions; weak reversibility is sufficient but not necessary. [ABSTRACT FROM AUTHOR]

Hat problems have become a popular topic in recreational mathematics. In a typical hat problem, each of n players tries to guess the color of the hat, he or she is wearing by looking at the colors of the hats worn by some of the other players. In this paper we consider several variants of the problem, united by the common theme that the guessing strategies are required to be deterministic and the objective is to maximize the number of correct answers in the worst case. We also summarize what is currently known about the worst-case analysis of deterministic hat guessing problems with a finite number of players. [ABSTRACT FROM AUTHOR]

Most probability and statistics textbooks are loaded with dice, coins, and balls in urns. These are perfect metaphors for actual phenomena where uncertainty plays a role. However, students will greatly appreciate a real-life example. In this paper we examine the mathematics of an implementation of an iris recognition system, We show that the determination of a crucial spread parameter is made on implicit assumptions that are not fulfilled. Some elementary probability theory calculations show that this leads in general to an optimistic assessment of the reliability of the identification system. Then we use a famous inequality to quantify this optimism. [ABSTRACT FROM AUTHOR]

The problem of estimating underlying trends in time series data arises in a variety of discipline. In this paper we propose a variation on Hodrick-Prescott (H-P) filtering, a widely used method for trend estimation. The proposed ℓ1 trend filtering method substitutes a sum of absolute values (i.e., ℓ1 norm) for the sum of squares used in H-P filtering to penalize variations in the estimated trend. The ℓ1 trend filtering method produces trend estimates that are piecewise linear, and therefore it is well suited to analyzing time series with an underlying piecewise linear trend. The kinks, knots, or changes in slope of the estimated trend can be interpreted as abrupt changes or events in the underlying dynamics of the time aeries. Liming specialized interior-point methods, ℓ1> tread filtering can be carried out with not much more effort than H-P filtering; in particular, the number of arithmetic operations required grows linearly with the number of data points. We describe the method and some of its basic properties and give some illustrative examples. We show how the method is related to ℓ1 regularization-based methods in sparse signal recovery and feature selection, and we list some extensions of the basic method. [ABSTRACT FROM AUTHOR]

This paper surveys some results on acute and nonobtuse simplices and associated spatial partitions. These partitions are relevant in numerical mathematics, including piecewise polynomial approximation theory and the finite element method. Special attention is paid to a basic type of nonobtuse simplices called path-simplices, the generalization of right triangles to higher dimensions. In addition to applications in numerical mathematics, we give examples of the appearance of acute sad nonobtuse simplices in other areas of mathematics. [ABSTRACT FROM AUTHOR]

Emerging applications for networked and cooperative robots motivate the study of motion coordination for groups of agents. For example, it is envisioned that groups of agents will perform a variety of useful tasks including surveillance, exploration, and environmental monitoring. This paper deals with basic interactions among mobile agents such as "move away from the closest other agent" or "move toward the furthest vertex of your own Voronoi polygon." These simple interactions amount to distributed dynamical systems because their implementation requires only minimal information about neighboring agents. We characterize the close relationship between these distributed dynamical systems and the disk-covering and sphere-packing cost functions from geometric optimization. Our main results are as follows: (i) we characterize the smoothness properties of these geometric cost functions, (ii) we show that the interaction laws are variations of the nonsmooth gradient of the cost functions, and (iii) we establish various asymptotic convergence properties of the laws. The technical approach relies on concepts from computational geometry, nonsmooth analysis, and nonsmooth stability theory. [ABSTRACT FROM AUTHOR]

This paper deals with superconvergence phenomena in general grids when projectionbased approximations are used for solving Fredholm integral equations of the second kind with weakly singular kernels. Four variants of the Galerkin method are considered. They are the classical Galerkin method, the iterated Galerkin method, the Kantorovich method, and the iterated Kantorovich method. It is proved that the iterated Kantorovich approximation exhibits the best superconvergence rate if the right-hand side of the integral equation is nonsmooth. All error estimates are derived for an arbitrary grid without any uniformity or quasi-uniformity condition on it, and are formulated in terms of the data without any additional assumption on the solution. Numerical examples concern the equation governing transfer of photons in stellar atmospheres. The numerical results illustrate the fact that the error estimates proposed in the different theorems are quite sharp, and confirm the superiority of the iterated Kantorovich scheme. [ABSTRACT FROM AUTHOR]

A recent study [D. N. Arnold, D. Boffi, and R. S. Falk, SIAM J. Numer. Anal., 42 (2005), pp. 2429-2451] reveals that convergence of finite element methods using H(div , O)-compatible finite element spaces deteriorates on nonaffine quadrilateral grids. This phenomena is particularly troublesome for the lowest-order Raviart-Thomas elements, because it implies loss of convergence in some norms for finite element solutions of mixed and least-squares methods. In this paper we propose reformulation of finite element methods, based on the natural mimetic divergence operator [M. Shashkov, Conservative Finite Difference Methods on General Grids, CRC Press, Boca Raton, FL, 1996], which restores the order of convergence. Reformulations of mixed Galerkin and leastsquares methods for the Darcy equation illustrate our approach. We prove that reformulated methods converge optimally with respect to a norm involving the mimetic divergence operator. Furthermore, we prove that standard and reformulated versions of the mixed Galerkin method lead to identical linear systems, but the two versions of the least-squares method are veritably different. The surprising conclusion is that the degradation of convergence in the mixed method on nonaffine quadrilateral grids is superficial, and that the lowest-order Raviart-Thomas elements are safe to use in this method. However, the breakdown in the least-squares method is real, and there one should use our proposed reformulation. [ABSTRACT FROM AUTHOR]

We develop a family of new interior penalty discontinuous Galerkin methods for the Keller-Segel chemotaxis model. This model is described by a system of two nonlinear PDEs: a convection-diffusion equation for the cell density coupled with a reaction-diffusion equation for the chemoattractant concentration. It has been recently shown that the convective part of this system is of a mixed hyperbolic-elliptic-type, which may cause severe instabilities when the studied system is solved by straightforward numerical methods. Therefore, the first step in the derivation of our new methods is made by introducing the new variable for the gradient of the chemoattractant concentration and by reformulating the original Keller-Segel model in the form of a convection-diffusionreaction system with a hyperbolic convective part. We then design interior penalty discontinuous Galerkin methods for the rewritten Keller-Segel system. Our methods employ the central-upwind numerical fluxes, originally developed in the context of finite-volume methods for hyperbolic systems of conservation laws. In this paper, we consider Cartesian grids and prove error estimates for the proposed high-order discontinuous Galerkin methods. Our proof is valid for pre-blow-up times since we assume boundedness of the exact solution. We also show that the blow-up time of the exact solution is bounded from above by the blow-up time of our numerical solution. In the numerical tests presented below, we demonstrate that the obtained numerical solutions have no negative values and are oscillation-free, even though no slope-limiting technique has been implemented. [ABSTRACT FROM AUTHOR]

The fast marching method (FMM) has proved to be a very efficient algorithm for solving the isotropic Eikonal equation. Because it is a minor modification of Dijkstra's algorithm for finding the shortest path through a discrete graph, FMM is also easy to implement. In this paper we describe a new class of Hamilton-Jacobi (HJ) PDEs with axis-aligned anisotropy which satisfy a causality condition for standard finite-difference schemes on orthogonal grids and can hence be solved using the FMM; the only modification required to the algorithm is in the local update equation for a node. This class of HJ PDEs has applications in anelliptic wave propagation and robotic path planning, and brief examples are included. Since our class of HJ PDEs and grids permit asymmetries, we also examine some methods of improving the efficiency of the local update that do not require symmetric grids and PDEs. Finally, we include explicit update formulas for variations of the Eikonal equation that use the Manhattan, Euclidean, and infinity norms on orthogonal grids of arbitrary dimension and with variable node spacing. [ABSTRACT FROM AUTHOR]

In this paper, the frequency domain-based numerical methods for simulation of fractional order systems are studied in the sense of stability preservation. First, the stability boundary curve is exactly determined for these methods. Then, this boundary is analyzed and compared with an accurate (ideal) boundary in different frequency ranges. Also, the critical regions in which the stability does not preserve are determined. Finally, the analytical achievements are confirmed via some numerical illustrations. [ABSTRACT FROM AUTHOR]

In this paper, we consider the singularly perturbed reaction-diffusion problem in one and two dimensions. The boundary value problem is decomposed into a first-order system to which a suitable weighted least-squares formulation is proposed. A robust, stable, and efficient approach is developed based on local discontinuous Galerkin (LDG) discretization for the weak form. Uniform error estimates are derived. Numerical examples are presented to illustrate the method and the theoretical results. Comparison studies are made between the proposed method and other methods. [ABSTRACT FROM AUTHOR]

Judy and Motta developed a customizable electrodeposition process for fabrication of very small metal structures on a substrate. In this process, layers of metal of various shapes are placed on the substrate, then the substrate is inserted in an electroplating solution. Some of the metal layers have power applied to them, while the rest of the metal layers are not connected to the power initially. Metal ions in the plating solution start depositing on the powered layers and a surface grows from the powered layers. As the surface grows, it will touch metal layers that were initially unpowered, causing them to become powered and to start growing with the rest of the surface. The metal layers on the substrate are known as seed layer patterns, and different seed layer patterns can produce different shapes. This paper presents a mathematical model, a forward simulation method, and an inverse problem solution for the growth of a surface from a seed layer pattern. The model describes the surface evolution as uniform growth in the direction normal to the surface. This growth is simulated in two and three dimensions using the level set method. The inverse problem is to design a seed layer pattern that produces a desired surface shape. Some surface shapes are not attainable by any seed layer pattern. For smooth attainable shapes, we present a computational method that solves this inverse problem. [ABSTRACT FROM AUTHOR]

The aim of this paper is to analyze a numerical method for solving the magnetostatic problem in a three-dimensional bounded domain containing prescribed currents and magnetic materials. The method discretizes a well-known formulation of this problem based on two scalar potentials: the total potential, defined in magnetic materials, and the reduced potential, defined in dielectric media and in nonmagnetic conductors carrying currents. The topology of the domain of each material is not assumed to be trivial. The resulting variational problem is proved to be well posed and is discretized by means of standard piecewise linear finite elements. Transmission conditions are imposed by means of a piecewise linear Lagrange multiplier on the surface separating the domains of both potentials. Error estimates for the numerical method are proved and the results of some numerical tests are reported to assess the performance of the method. [ABSTRACT FROM AUTHOR]

This paper presents analysis of a weighted-norm least squares finite element method for elliptic problems with boundary singularities. We use H(div) conforming Raviart-Thomas elements and continuous piecewise polynomial elements. With only a rough estimate of the power of the singularity, we employ a simple, locally weighted L² norm to eliminate the pollution effect and recover better rates of convergence. Theoretical results are carried out in weighted Sobolev spaces and include ellipticity bounds of the homogeneous least-squares functional, new weighted Raviart-Thomas interpolation results, and error estimates in both weighted and nonweighted norms. Numerical tests are given to confirm the theoretical estimates and to illustrate the practicality of the method. [ABSTRACT FROM AUTHOR]

In order to ensure convergence to the viscosity solution, the standard method for discretizing Hamilton-Jacobi-Bellman partial differential equations uses forward/backward differencing for the drift term. In this paper, we devise a monotone method which uses central weighting as much as possible. In order to solve the discretized algebraic equations, we have to maximize a possibly discontinuous objective function at each node. Nevertheless, convergence of the overall iteration can be guaranteed. Numerical experiments on two examples from the finance literature show higher rates of convergence for this approach compared to the use of forward/backward differencing only. [ABSTRACT FROM AUTHOR]

A popular vector quantization scheme can be constructed by centroidal Voronoi tessellations (CVTs) which also have many other applications in diverse areas of science and engineering. The development of efficient algorithms for their construction is a key to the successful applications of CVTs in practice. This paper studies the details of a new optimization-based multilevel algorithm for the numerical computation of CVTs. The rigorous proof of its uniform convergence in one space dimension and the results of computational simulations are provided. They substantiate recent claims on the significant speedup demonstrated by the new scheme in comparison with traditional methods. [ABSTRACT FROM AUTHOR]

Mixed trigonometric polynomial systems arise in many fields of science and engineering. Commonly, this class of systems is transformed into polynomial systems by variable substituting and adding some quadratic equations, and then solved by some polynomial system solving method. In this paper, by exploiting the special structure of the additional quadratic equations, an efficient hybrid method for solving polynomial systems coming from mixed trigonometric polynomial systems is presented. It combines the homotopy method, in which the homotopy is a combination of coefficient parameter homotopy and the random product homotopy, with decomposition, variable substitution, and reduction techniques. Numerical tests are given to show its effectiveness, and it is applied to solve a practical problem. [ABSTRACT FROM AUTHOR]

After a brief survey of basic results about finite-dimensional approximation settings (such as mathematical frameworks of various projection methods, including the least-squares method, the dual least-squares method, and the Galerkin method) for infinite-dimensional Moore-Penrose inverses, this paper proceeds to a detailed study from the following aspects: For projection methods, we investigate convergence and weak convergence of their approximation setting to develop a unified theory on projection methods for infinite-dimensional Moore-Penrose inverses; this investigation yields a fundamental convergence theorem (Theorem 2.2), from which the criterion for convergence, the criterion for weak convergence, and the generalized dual least-squares method are derived. We also derive general results on the least-squares method, by which two flaws in Groestch's results are corrected. For nonprojection methods (whose approximation setting is a more general framework), we investigate weak perfect convergence of their approximation setting and provide a necessary and sufficient condition of such convergence holding (Theorem 3.2). Several examples are proposed as counterexamples to illustrate the differences between some important concepts or as concrete algorithms to show how the present work can help to analyze their behavior. [ABSTRACT FROM AUTHOR]

The classical error analysis for the Raviart-Thomas interpolation on triangular elements requires the so-called regularity of the elements, or equivalently, the minimum angle condition. However, in the lowest order case, optimal order error estimates have been obtained in [G. Acosta and R. G. Durán, SIAM J. Numer. Anal., 37 (2000), pp. 18-36] replacing the regularity hypothesis by the maximum angle condition, which was known to be sufficient to prove estimates for the standard Lagrange interpolation. In this paper we prove error estimates on triangular elements for the Raviart-Thomas interpolation of any order under the maximum angle condition. Also, we show how our arguments can be extended to the three-dimensional case to obtain error estimates for tetrahedral elements under the regular vertex property introduced in [G. Acosta and R. G. Durán, SIAM J. Numer. Anal., 37 (2000), pp. 18-36]. [ABSTRACT FROM AUTHOR]

An interior penalty method for certain two-dimensional curl-curl problems is investigated in this paper. This method computes the divergence-free part of the solution using locally divergence-free discontinuous P1 vector fields on graded meshes. It has optimal order convergence (up to an arbitrarily small ϵ) for the source problem and the eigenproblem. Results of numerical experiments that corroborate the theoretical results are also presented. [ABSTRACT FROM AUTHOR]

The effective resistance between two nodes of a weighted graph is the electrical resistance seen between the nodes of a resistor network with branch conductances given by the edge weights. The effective resistance comes up in many applications and fields in addition to electrical network analysis, including, for example, Markov chains and continuous-time averaging networks. In this paper we study the problem of allocating edge weights on a given graph in order to minimize the total effective resistance, i.e., the sum of the resistances between all pairs of nodes. We show that this is a convex optimization problem and can be solved efficiently either numerically or, in some cases, analytically. We show that optimal allocation of the edge weights can reduce the total effective resistance of the graph (compared to uniform weights) by a factor that grows unboundedly with the size of the graph. We show that among all graphs with n nodes, the path has the largest value of optimal total effective resistance and the complete graph has the least. [ABSTRACT FROM AUTHOR]

Ion channels control many biological processes in cells, and, consequently, a large amount of research is devoted to this topic. Great progress in the understanding of channel function has been made recently using advanced mathematical modeling and simulation. This paper investigates another interesting mathematical topic, namely inverse problems, in connection with ion channels. We concentrate on problems that arise when we try to determine (‘identify’) one of the structural features of a channel—its permanent charge—from measurements of its function, namely current-voltage curves in many solutions. We also try to design channels with desirable properties— for example with particular selectivity properties—using the methods of inverse problems. The use of mathematical methods of identification will help in the design of efficient experiments to determine the properties of ion channels. Closely related mathematical methods will allow the rational design of ion channels useful in many applications, technological and medical. We also discuss certain mathematical issues arising in these inverse problems, such as their ill-posedness and the choice of regularization techniques, as well as challenges in their numerical solution. The L-type Ca channel is studied with the methods of inverse problems to see how mathematics can aid in the analysis of existing ion channels and the design of new ones. [ABSTRACT FROM AUTHOR]

In this paper, we derive an equation for the growth of a flame ball for a free boundary combustion model with radiative transfer. The equation for the radiative field is given by the linearized Eddington equation. We then study the mathematical properties of this equation of growth and carry out numerical computations in order to discuss the stability or instability of steady flame balls. [ABSTRACT FROM AUTHOR]

This paper is devoted to the resolution of the time-harmonic linearized Galbrun equation, which models, via a mixed Lagrangian-Eulerian representation, the propagation of acoustic and hydrodynamic perturbations in a given flow of a compressible fluid. We consider here the case of a uniform subsonic flow in an infinite, two-dimensional duct. Using a limiting absorption process, we characterize the outgoing solution radiated by a compactly supported source. Then we propose a Fredholm formulation with perfectly matched absorbing layers for approximating this outgoing solution. The convergence of the approximated solution to the exact one is proved, and error estimates with respect to the parameters of the absorbing layers are derived. Several significant numerical examples are included. [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 the integration of one-dimensional highly oscillatory functions. Based on analytic continuation, rapidly converging quadrature rules are derived for a general class of oscillatory integrals with an analytic integrand. The accuracy of the quadrature increases both for the case of a fixed number of points and increasing frequency, and for the case of an increasing number of points and fixed frequency. These results are then used to obtain quadrature rules for more general oscillatory integrals, i.e., for functions that exhibit some smoothness but that are not analytic. The approach described in this paper is related to the steepest descent method, but it does not employ asymptotic expansions. It can be used for small or moderate frequencies as well as for very high frequencies. The approach is compared with the oscillatory integration techniques recently developed by Iserles and Nørsett. [ABSTRACT FROM AUTHOR]