2,048 research outputs found

    Solving periodic semilinear stiff PDEs in 1D, 2D and 3D with exponential integrators

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    Dozens of exponential integration formulas have been proposed for the high-accuracy solution of stiff PDEs such as the Allen-Cahn, Korteweg-de Vries and Ginzburg-Landau equations. We report the results of extensive comparisons in MATLAB and Chebfun of such formulas in 1D, 2D and 3D, focusing on fourth and higher order methods, and periodic semilinear stiff PDEs with constant coefficients. Our conclusion is that it is hard to do much better than one of the simplest of these formulas, the ETDRK4 scheme of Cox and Matthews

    Fourth-order time-stepping for stiff PDEs on the sphere

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    We present in this paper algorithms for solving stiff PDEs on the unit sphere with spectral accuracy in space and fourth-order accuracy in time. These are based on a variant of the double Fourier sphere method in coefficient space with multiplication matrices that differ from the usual ones, and implicit-explicit time-stepping schemes. Operating in coefficient space with these new matrices allows one to use a sparse direct solver, avoids the coordinate singularity and maintains smoothness at the poles, while implicit-explicit schemes circumvent severe restrictions on the time-steps due to stiffness. A comparison is made against exponential integrators and it is found that implicit-explicit schemes perform best. Implementations in MATLAB and Chebfun make it possible to compute the solution of many PDEs to high accuracy in a very convenient fashion

    A New Algorithm for Computing the Actions of Trigonometric and Hyperbolic Matrix Functions

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    A new algorithm is derived for computing the actions f(tA)Bf(tA)B and f(tA1/2)Bf(tA^{1/2})B, where ff is cosine, sinc, sine, hyperbolic cosine, hyperbolic sinc, or hyperbolic sine function. AA is an n×nn\times n matrix and BB is n×n0n\times n_0 with n0≪nn_0 \ll n. A1/2A^{1/2} denotes any matrix square root of AA and it is never required to be computed. The algorithm offers six independent output options given tt, AA, BB, and a tolerance. For each option, actions of a pair of trigonometric or hyperbolic matrix functions are simultaneously computed. The algorithm scales the matrix AA down by a positive integer ss, approximates f(s−1tA)Bf(s^{-1}tA)B by a truncated Taylor series, and finally uses the recurrences of the Chebyshev polynomials of the first and second kind to recover f(tA)Bf(tA)B. The selection of the scaling parameter and the degree of Taylor polynomial are based on a forward error analysis and a sequence of the form ∥Ak∥1/k\|A^k\|^{1/k} in such a way the overall computational cost of the algorithm is optimized. Shifting is used where applicable as a preprocessing step to reduce the scaling parameter. The algorithm works for any matrix AA and its computational cost is dominated by the formation of products of AA with n×n0n\times n_0 matrices that could take advantage of the implementation of level-3 BLAS. Our numerical experiments show that the new algorithm behaves in a forward stable fashion and in most problems outperforms the existing algorithms in terms of CPU time, computational cost, and accuracy.Comment: 4 figures, 16 page

    ParaExp using Leapfrog as Integrator for High-Frequency Electromagnetic Simulations

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    Recently, ParaExp was proposed for the time integration of linear hyperbolic problems. It splits the time interval of interest into sub-intervals and computes the solution on each sub-interval in parallel. The overall solution is decomposed into a particular solution defined on each sub-interval with zero initial conditions and a homogeneous solution propagated by the matrix exponential applied to the initial conditions. The efficiency of the method depends on fast approximations of this matrix exponential based on recent results from numerical linear algebra. This paper deals with the application of ParaExp in combination with Leapfrog to electromagnetic wave problems in time-domain. Numerical tests are carried out for a simple toy problem and a realistic spiral inductor model discretized by the Finite Integration Technique.Comment: Corrected typos. arXiv admin note: text overlap with arXiv:1607.0036
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