32,713 research outputs found

    Approximation of Elements of Exponentials of Differential Operators With Rational Quadrature

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    We explore the possibility of improving the accuracy of approximations of elements of exponentials of differential operators, by using a rational function, instead of a polynomial function, as the interpolating function. Since a rational function behaves more like a decaying exponential function, it seems logical that the approximation should be more accurate. Through the use of high accuracy rational interpolants, we experiment with a numerical integration method to determine explicitly whether the error produced by a rational type approximation will indeed be less than that produced by a polynomial type approximation

    ON SUBDIAGONAL RATIONAL PADE APPROXIMATIONS AND THE BRENNER-THOMEE APPROXIMATION THEOREM FOR OPERATOR SEMIGROUPS

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    The computational powers of Mathematica are used to prove polynomial identities that are essential to obtain growth estimates for subdiagonal rational Pade approximations of the exponential function and to obtain new estimates of the constants of the Brenner-Thomee Approximation Theorem of Semigroup Theory

    Representation of conformal maps by rational functions

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    The traditional view in numerical conformal mapping is that once the boundary correspondence function has been found, the map and its inverse can be evaluated by contour integrals. We propose that it is much simpler, and 10-1000 times faster, to represent the maps by rational functions computed by the AAA algorithm. To justify this claim, first we prove a theorem establishing root-exponential convergence of rational approximations near corners in a conformal map, generalizing a result of D. J. Newman in 1964. This leads to the new algorithm for approximating conformal maps of polygons. Then we turn to smooth domains and prove a sequence of four theorems establishing that in any conformal map of the unit circle onto a region with a long and slender part, there must be a singularity or loss of univalence exponentially close to the boundary, and polynomial approximations cannot be accurate unless of exponentially high degree. This motivates the application of the new algorithm to smooth domains, where it is again found to be highly effective

    Evaluating matrix functions for exponential integrators via Carathéodory-Fejér approximation and contour integrals

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    Among the fastest methods for solving stiff PDE are exponential integrators, which require the evaluation of f(A)f(A), where AA is a negative definite matrix and ff is the exponential function or one of the related ``φ\varphi functions'' such as φ1(z)=(ez−1)/z\varphi_1(z) = (e^z-1)/z. Building on previous work by Trefethen and Gutknecht, Gonchar and Rakhmanov, and Lu, we propose two methods for the fast evaluation of f(A)f(A) that are especially useful when shifted systems (A+zI)x=b(A+zI)x=b can be solved efficiently, e.g. by a sparse direct solver. The first method method is based on best rational approximations to ff on the negative real axis computed via the Carathéodory-Fejér procedure, and we conjecture that the accuracy scales as (9.28903… )−2n(9.28903\dots)^{-2n}, where nn is the number of complex matrix solves. In particular, three matrix solves suffice to evaluate f(A)f(A) to approximately six digits of accuracy. The second method is an application of the trapezoid rule on a Talbot-type contour

    Approximation of SPDE covariance operators by finite elements: A semigroup approach

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    The problem of approximating the covariance operator of the mild solution to a linear stochastic partial differential equation is considered. An integral equation involving the semigroup of the mild solution is derived and a general error decomposition is proven. This formula is applied to approximations of the covariance operator of a stochastic advection-diffusion equation and a stochastic wave equation, both on bounded domains. The approximations are based on finite element discretizations in space and rational approximations of the exponential function in time. Convergence rates are derived in the trace class and Hilbert--Schmidt norms with numerical simulations illustrating the results.Comment: 31 pages, 8 figures; added derivation of trace error formula; to appear in IMA Journal of Numerical Analysi
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