2,529 research outputs found

    Efficient multistep methods for tempered fractional calculus: Algorithms and Simulations

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    In this work, we extend the fractional linear multistep methods in [C. Lubich, SIAM J. Math. Anal., 17 (1986), pp.704--719] to the tempered fractional integral and derivative operators in the sense that the tempered fractional derivative operator is interpreted in terms of the Hadamard finite-part integral. We develop two fast methods, Fast Method I and Fast Method II, with linear complexity to calculate the discrete convolution for the approximation of the (tempered) fractional operator. Fast Method I is based on a local approximation for the contour integral that represents the convolution weight. Fast Method II is based on a globally uniform approximation of the trapezoidal rule for the integral on the real line. Both methods are efficient, but numerical experimentation reveals that Fast Method II outperforms Fast Method I in terms of accuracy, efficiency, and coding simplicity. The memory requirement and computational cost of Fast Method II are O(Q)O(Q) and O(QnT)O(Qn_T), respectively, where nTn_T is the number of the final time steps and QQ is the number of quadrature points used in the trapezoidal rule. The effectiveness of the fast methods is verified through a series of numerical examples for long-time integration, including a numerical study of a fractional reaction-diffusion model

    Fast and oblivious convolution quadrature

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    We give an algorithm to compute NN steps of a convolution quadrature approximation to a continuous temporal convolution using only O(NlogN)O(N \log N) multiplications and O(logN)O(\log N) active memory. The method does not require evaluations of the convolution kernel, but instead O(logN)O(\log N) evaluations of its Laplace transform, which is assumed sectorial. The algorithm can be used for the stable numerical solution with quasi-optimal complexity of linear and nonlinear integral and integro-differential equations of convolution type. In a numerical example we apply it to solve a subdiffusion equation with transparent boundary conditions

    A Gauss-Jacobi Kernel Compression Scheme for Fractional Differential Equations

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    A scheme for approximating the kernel ww of the fractional α\alpha-integral by a linear combination of exponentials is proposed and studied. The scheme is based on the application of a composite Gauss-Jacobi quadrature rule to an integral representation of ww. This results in an approximation of ww in an interval [δ,T][\delta,T], with 0<δ0<\delta, which converges rapidly in the number JJ of quadrature nodes associated with each interval of the composite rule. Using error analysis for Gauss-Jacobi quadratures for analytic functions, an estimate of the relative pointwise error is obtained. The estimate shows that the number of terms required for the approximation to satisfy a prescribed error tolerance is bounded for all α(0,1)\alpha\in(0,1), and that JJ is bounded for α(0,1)\alpha\in(0,1), T>0T>0, and δ(0,T)\delta\in(0,T)

    Error Estimates for Approximations of Distributed Order Time Fractional Diffusion with Nonsmooth Data

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    In this work, we consider the numerical solution of an initial boundary value problem for the distributed order time fractional diffusion equation. The model arises in the mathematical modeling of ultra-slow diffusion processes observed in some physical problems, whose solution decays only logarithmically as the time tt tends to infinity. We develop a space semidiscrete scheme based on the standard Galerkin finite element method, and establish error estimates optimal with respect to data regularity in L2(D)L^2(D) and H1(D)H^1(D) norms for both smooth and nonsmooth initial data. Further, we propose two fully discrete schemes, based on the Laplace transform and convolution quadrature generated by the backward Euler method, respectively, and provide optimal convergence rates in the L2(D)L^2(D) norm, which exhibits exponential convergence and first-order convergence in time, respectively. Extensive numerical experiments are provided to verify the error estimates for both smooth and nonsmooth initial data, and to examine the asymptotic behavior of the solution.Comment: 25 pages, 2 figure
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