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Numerical algorithms for differential equations with periodicity

Abstract: This thesis presents new numerical methods for solving differential equations with periodicity. Spectral methods for solving linear and nonlinear ODEs, linear ODE eigenvalue problems and linear time-dependent PDEs on a periodic interval are reviewed, and a novel approach for computing multiplication matrices is presented.Choreographies, periodic solutions of the n-body problem that share a common orbit, are computed for the first time to high accuracy using an algorithm based on approximation by trigonometric polynomials and optimization techniques with exact gradient and exact Hessian matrix. New choreographies in spaces of constant curvature are found.Exponential integrators for solving periodic semilinear stiff PDEs in 1D, 2D and 3D periodic domains are reviewed, and 30 exponential integrators are compared on 11 PDEs. It is shown that the complicated fifth-, sixth- and seventh-order methods do not really outperform one of the simplest exponential integrators, the fourth-order ETDRK4 scheme of Cox and Matthews.Finally, algorithms for solving semilinear stiff PDEs on the sphere with spectral accuracy in space and fourth-order accuracy in time are proposed. These are based on a new variant of the double Fourier sphere method in coefficient space and standard implicit-explicit time-stepping schemes. A comparison is made against exponential integrators and it is found that implicit-explicit schemes perform better.The algorithms described in each chapter of this thesis have been implemented in MATLAB and made available as part of Chebfun.

Type of Award:DPhil Level of Award:Doctoral Awarding Institution:University of Oxford

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European Research Council more by this funder

Grant number291068 Received ByProject

  Item Description

Type: Thesis Keywords: Stiff PDEs Choreographies Stiff ODEs Nonlinear ODEs PDEs on the sphere Fourier spectral methods Periodic Differential Equations Subjects: Applied Mathematics Numerical Mathematics Applied PDEs Numerical PDEs

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Author: Hadrien Montanelli - AffiliationUniversity of Oxford Role Author - - - Nick Trefethen More by this supervisor - Role Supervisor -

Source: https://ora.ox.ac.uk/objects/uuid:cc001282-4285-4ca2-ad06-31787b540c61



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