Numerical quadrature

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Efficient and accurate numerical quadrature for immersed boundary methods

Efficient and accurate numerical quadrature for immersed boundary methods

One question in the context of immersed boundary or fictitious domain methods is how to compute discontinuous integrands in cut elements accurately. A frequently used method is to apply a composed Gaussian quadrature based on a spacetree subdivision. Although this approach works robustly on any geometry, the resulting integration mesh yields a low order representation of the boundary. If high order shape functions are employed to approximate the solution, this lack of geometric approxima- tion power prevents exponential convergence in the asymptotic range. In this paper we present an algorithmic subdivision approach that aims to be as robust as the spa- cetree decomposition even for close-to-degenerate cases—but remains geometrically accurate at the same time. Based on 2D numerical examples, we will show that optimal convergence rates can be obtained with a nearly optimal number of integration points. Keywords: Immersed boundary methods, Finite Cell Method, Numerical quadrature

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Numerical quadrature for the approximation of singular oscillating integrals appearing in boundary integral equations

Numerical quadrature for the approximation of singular oscillating integrals appearing in boundary integral equations

We present a method for the numerical quadrature of an integral with a logarithmic singularity and a cosine oscillator: a modified Filon-Lobatto quadrature for the oscillating parts and an integral transformation based on the error function for the singularity. Since this integral can be solved analytically, we are in a position to verify the results of our investigations, with a focus on precision and computation time.

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A Survey Of Numerical Quadrature Methods For Highly Oscillatory Integrals

A Survey Of Numerical Quadrature Methods For Highly Oscillatory Integrals

In this thesis, we examine the main types of numerical quadrature methods for a special subclass of one-dimensional highly oscillatory integrals. Along with a presentation of the methods themselves and the error bounds, the thesis contains implementations of the methods in Maple and Python. The implementations take advantage of the symbolic computational abilities of Maple and allow for a larger class of problems to be solved with greater ease to the user. We also present a new variation on Levin integration which uses di ff erentiation matrices in various interpolation bases.

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Length Scales in Bayesian Automatic Adaptive Quadrature

Length Scales in Bayesian Automatic Adaptive Quadrature

Abstract. Two conceptual developments in the Bayesian automatic adaptive quadrature approach to the numerical solution of one-dimensional Riemann integrals [Gh. Adam, S. Adam, Springer LNCS 7125, 1–16 (2012)] are reported. First, it is shown that the numerical quadrature which avoids the overcomputing and minimizes the hidden floating point loss of precision asks for the consideration of three classes of integration domain lengths endowed with specific quadrature sums: microscopic (trapezoidal rule), meso- scopic (Simpson rule), and macroscopic (quadrature sums of high algebraic degrees of precision). Second, sensitive diagnostic tools for the Bayesian inference on macroscopic ranges, coming from the use of Clenshaw-Curtis quadrature, are derived.

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Multistage Numerical Picard Iteration Methods for Nonlinear Volterra Integral Equations of the Second Kind

Multistage Numerical Picard Iteration Methods for Nonlinear Volterra Integral Equations of the Second Kind

Using the Picard iteration method and treating the involved integration by numerical quadrature formulas, we propose a numerical scheme for the second kind nonlinear Volterra integral equa- tions. For enlarging the convergence region of the Picard iteration method, multistage algorithm is devised. We also introduce an algorithm for problems with some singularities at the limits of in- tegration including fractional integral equations. Numerical tests verify the validity of the pro- posed schemes.

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Exponential Spectral Risk Measures

Exponential Spectral Risk Measures

This paper has examined spectral risk measures based on an exponential utility function. We find that the exponential utility function leads to risk-aversion functions and spectral risk measures with intuitive and nicely behaved properties. These exponential SRMs are easy to estimate using numerical quadrature methods and accurate estimates can be obtained very quickly in real time. It is also easy to estimate confidence intervals for these SRMs using a parametric bootstrap. Illustrative results suggest that these confidence intervals are surprisingly narrow, and this indicates that SRM estimates are quite precise. Of course, the results presented here are based on an assumed normal distribution, and further work is needed to establish results for other distributions. 10

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Pricing exotic derivatives exploiting structure

Pricing exotic derivatives exploiting structure

In this paper we introduce a new fast and accurate numerical method for pricing exotic derivatives when discrete monitoring occurs, and the under- lying evolves according to a Markov one-dimensional stochastic processes. The approach exploits the structure of the matrix arising from the numerical quadrature of the pricing backward formulas to devise a convenient factor- ization that helps greatly in the speed-up of the recursion. The algorithm is general and is examined in detail with reference to the CEV (Constant Elasticity of Variance) process for pricing different exotic derivatives, such as Asian, barrier, Bermudan, lookback and step options for which up to date no efficient procedures are available. Extensive numerical experiments confirm the theoretical results. The MATLAB code used to perform the computation is available online at http://www1.mate.polimi.it/~marazzina/BP.htm. Keywords: CEV Process, Discrete Monitoring, Exotic Derivatives, Matrix Factorization, Numerical Quadrature, Option Pricing, Recursive Pricing Formula

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An adaptive variable order quadrature strategy

An adaptive variable order quadrature strategy

approximation theory [5, 15] (see also [8]), and has been applied with huge success in the context of FEMs for the numerical approximation of differential equations. Indeed, under certain conditions, the judicious combination of subinterval refine- ments (h-refinement) and selection of local approximation orders (p-refinement), which results in the class of so-called hp-FEMs, is able to achieve high-order alge- braic or exponential rates of convergence, even for solutions with local singularities; see, e.g. [18]. In an effort to automate the combined h- and p-refinement process, a number of hp-adaptive FEM approaches have been proposed in the literature; see, e.g, [13] and the references cited therein. In the current article, we pursue the smoothness estimation approach developed in [6, 21] (cf. also [11]), and translate the idea into the context of adaptive variable order numerical quadrature.

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Euler Maclaurin Expansions of Errors for Multidimensional Weakly Singular Integrals and Their Splitting Extrapolation Algorithm*

Euler Maclaurin Expansions of Errors for Multidimensional Weakly Singular Integrals and Their Splitting Extrapolation Algorithm*

We give the numerical results of the splitting extrapolation of types 1 and 2 and Gauss quadrature methods. Table 1 gives the relative error (RE) and CPU time for different dimension ( s ) and splitting times ( m ). From the Table 1, we can find that the splitting extrapolation method is suit for solving high dimen- sional integrals, and Gauss quadrature rule is difficult for solving more than five dimensional problems.

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Survey on the Numerical Methods for ODE's Using the Sequence of Successive Approximations

Survey on the Numerical Methods for ODE's Using the Sequence of Successive Approximations

to approximate the solution of (1). In this method he apply the classical trape- zoidal quadrature rule ( for functions with continuous second order derivatives ) in [22], to compute the integrals from (4) on the knots of the uniform partition. In [14] is used the sequence of successive approximations and the classical quadrature trapezoidal rule for functions with continuous second order deriva- tives to approximate the solutions of Fredholm and Volterra integral equations.

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Solving Singularly Perturbed Differential-Difference Equations using Special Finite Difference Method

Solving Singularly Perturbed Differential-Difference Equations using Special Finite Difference Method

We have described a special finite difference method for solving a singularly perturbed differential difference equation with layer behaviour at one end point. In the special second order method, we have used a second order finite difference approximation for second order derivative, a modified second order upwind finite difference approximation for first order derivative and a second order average difference approximation for y. This method controls the rapid changes that occur in the boundary layer region and it gives good results. To discuss the applicability of the method we have solved some model examples by taking different values of  ,  and  . We have presented maximum absolute errors for the standard examples chosen from the literature. The numerical solution is compared with the exact solution. It is observed from results that the present technique approximates the exact solution very well.

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A New Proof of Inequality for Continuous Linear Functionals

A New Proof of Inequality for Continuous Linear Functionals

It is well known that a Hilbert space can be given a Gaussian measure. Let H be a Hilbert space equipped with Gaussian measure and L a continuous linear functional acting on H. Smale in 6 a pioneering work on continuous complexity theory defined an average with respect to the Gaussian measure error for quadrature rules. A result of Smale 6 says that the average error is proportional to L. More precisely,

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A direct method and convergence analysis for some system of singular integro-differential equations

A direct method and convergence analysis for some system of singular integro-differential equations

A class of singular integro-differential equations in Lebesgue spaces are stud- ied. There are many applications of the singular integro-differential equations discussed in this paper. An example in modeling the stress distribution of an elas- tic medium with holes is discussed in the paper. Direct numerical schemes using a collocation method and a mechanical quadrature rule designed for the singular integro-differential equations are proposed for arbitrary smooth closed contours. Convergence analysis of these methods are given. Numerical examples are also provided.

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Numerical resolution of large deflections in cantilever beams by Bernstein spectral method and a convolution quadrature.

Numerical resolution of large deflections in cantilever beams by Bernstein spectral method and a convolution quadrature.

In this paper, we present a numerical method for the simulation of a cantilever beam expressed as a boundary value problem with mixed conditions. We first introduce a basis by Bernstein polynomials satisfying homogeneous mixed boundary conditions. Then, a Bernstein–spectral method is presented for the numerical simulation of the problem. Also, a convolution quadrature method combined with a second order backward difference for the handling of the Neumann condition at the free end of the cantilever is presented for the discretization of the problem. It is discussed that the resulting nonlinear system has a special structure that makes it possible to be approximated by a linear system. This paper is organized as follows. Section 2 describes the physical aspects and modeling of a cantilever beam with regard to the static governing equations of the Euler–Bernoulli beam. Section 3 introduces a basis by Bernstein polynomials in order to use with the spectral method for the discretization of the problem. In section 4, we we the transformation to a Volterra integral equation and the convolution quadrature method is presented. The numerical experiments are provided in Section 5. The paper ends with some concluding remarks.

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Discrete adomian decomposition method for solving fredholm integral equations of the second kind

Discrete adomian decomposition method for solving fredholm integral equations of the second kind

There are several analytical and numerical methods use to solve nonlinear FIE as mentioned in the previous section but these analytical solution methods are not easy to use and require tedious calculation. Also when applying these methods to solve linear and nonlinear Fredholm integral equations many definite integrals need to be computed.

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An Ostrowski Type Inequality for Convex Functions

An Ostrowski Type Inequality for Convex Functions

All the inequalities in (1.8) are sharp and the constant 1 2 is the best possible. In this paper we establish an Ostrowski type inequality for convex functions. Applications for quadrature rules, for integral means, for probability distribution functions, and for HH−divergences in Information Theory are also considered.

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The Differential Quadrature Solution of Reaction Diffusion Equation Using Explicit and Implicit Numerical Schemes

The Differential Quadrature Solution of Reaction Diffusion Equation Using Explicit and Implicit Numerical Schemes

to make comparison between two methods and detect which of them is better. The numerical results obtained in this paper ensure that the problems have small desired time to reach it. Thus they have very small step size which is preferred and use RK4 to solve the system of ordinary differential equations in order to decrease the computational time. On the other hand, the problems which have high desired time to reach it, thus have large incremental time (stiff problems) which are preferred and use implicit Euler with perturbation method to solve the system of ordinary differential equations.

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A Method to Approximate Solution of the First Kind Abel Integral Equation Using Navot's Quadrature and Simpson's Rule

A Method to Approximate Solution of the First Kind Abel Integral Equation Using Navot's Quadrature and Simpson's Rule

Since the kernel and the deriving term of the integral equation (1.7) are expressed by weakly singular integrals, we must use a numerical method which is able to compute these integrals with weak singularity at the end points. For this purpose, Navot's quadrature rule is used. This special quadrature is applied for functions having a singularity of any type on or near the integration interval.

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Method for Integrating Tabular Functions that Considers Errors

Method for Integrating Tabular Functions that Considers Errors

In classical analysis, integration is a well-posed problem. In the theory of functions, Lebesgue integration may be logically interpreted as being the inverse to the differentiation operator. The set of absolutely continuous functions in a given interval coincides with the set of functions represented in the form of an indefinite Lebesgue integral with a variable upper bound of some integrable function plus a constant. However, the indicated property of being the inverse to differentiation is not longer valid a discrete set, since the operation of numerical differentiation is ill-posed.

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Application of CAS wavelet to construct quadrature rules for numerical ‎integration‎‎

Application of CAS wavelet to construct quadrature rules for numerical ‎integration‎‎

In this paper, new quadrature rules to approx- imate double and triple integrals with variables limits are presented. For this purpose, the CAS wavelets have been used. Presented quadrature rules in this paper can approximate some im- proper integrals. To show the efficiency of pre- sented methods, some test problems are consid- ered.

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