355 research outputs found

    Numerical methods for time-fractional evolution equations with nonsmooth data: a concise overview

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    Over the past few decades, there has been substantial interest in evolution equations that involving a fractional-order derivative of order α∈(0,1)\alpha\in(0,1) in time, due to their many successful applications in engineering, physics, biology and finance. Thus, it is of paramount importance to develop and to analyze efficient and accurate numerical methods for reliably simulating such models, and the literature on the topic is vast and fast growing. The present paper gives a concise overview on numerical schemes for the subdiffusion model with nonsmooth problem data, which are important for the numerical analysis of many problems arising in optimal control, inverse problems and stochastic analysis. We focus on the following aspects of the subdiffusion model: regularity theory, Galerkin finite element discretization in space, time-stepping schemes (including convolution quadrature and L1 type schemes), and space-time variational formulations, and compare the results with that for standard parabolic problems. Further, these aspects are showcased with illustrative numerical experiments and complemented with perspectives and pointers to relevant literature.Comment: 24 pages, 3 figure

    Galerkin FEM for fractional order parabolic equations with initial data in H−s, 0<s≤1H^{-s},~0 < s \le 1

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    We investigate semi-discrete numerical schemes based on the standard Galerkin and lumped mass Galerkin finite element methods for an initial-boundary value problem for homogeneous fractional diffusion problems with non-smooth initial data. We assume that Ω⊂Rd\Omega\subset \mathbb{R}^d, d=1,2,3d=1,2,3 is a convex polygonal (polyhedral) domain. We theoretically justify optimal order error estimates in L2L_2- and H1H^1-norms for initial data in H−s(Ω), 0≤s≤1H^{-s}(\Omega),~0\le s \le 1. We confirm our theoretical findings with a number of numerical tests that include initial data vv being a Dirac δ\delta-function supported on a (d−1)(d-1)-dimensional manifold.Comment: 13 pages, 3 figure

    The Galerkin Finite Element Method for A Multi-term Time-Fractional Diffusion equation

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    We consider the initial/boundary value problem for a diffusion equation involving multiple time-fractional derivatives on a bounded convex polyhedral domain. We analyze a space semidiscrete scheme based on the standard Galerkin finite element method using continuous piecewise linear functions. Nearly optimal error estimates for both cases of initial data and inhomogeneous term are derived, which cover both smooth and nonsmooth data. Further we develop a fully discrete scheme based on a finite difference discretization of the time-fractional derivatives, and discuss its stability and error estimate. Extensive numerical experiments for one and two-dimension problems confirm the convergence rates of the theoretical results.Comment: 22 pages, 4 figure

    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

    Numerical analysis of nonlinear subdiffusion equations

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    We present a general framework for the rigorous numerical analysis of time-fractional nonlinear parabolic partial differential equations, with a fractional derivative of order α∈(0,1)\alpha\in(0,1) in time. The framework relies on three technical tools: a fractional version of the discrete Gr\"onwall-type inequality, discrete maximal regularity, and regularity theory of nonlinear equations. We establish a general criterion for showing the fractional discrete Gr\"onwall inequality, and verify it for the L1 scheme and convolution quadrature generated by BDFs. Further, we provide a complete solution theory, e.g., existence, uniqueness and regularity, for a time-fractional diffusion equation with a Lipschitz nonlinear source term. Together with the known results of discrete maximal regularity, we derive pointwise L2(Ω)L^2(\Omega) norm error estimates for semidiscrete Galerkin finite element solutions and fully discrete solutions, which are of order O(h2)O(h^2) (up to a logarithmic factor) and O(τα)O(\tau^\alpha), respectively, without any extra regularity assumption on the solution or compatibility condition on the problem data. The sharpness of the convergence rates is supported by the numerical experiments

    Error Analysis of Semidiscrete Finite Element Methods for Inhomogeneous Time-Fractional Diffusion

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    We consider the initial boundary value problem for the inhomogeneous time-fractional diffusion equation with a homogeneous Dirichlet boundary condition and a nonsmooth right hand side data in a bounded convex polyhedral domain. We analyze two semidiscrete schemes based on the standard Galerkin and lumped mass finite element methods. Almost optimal error estimates are obtained for right hand side data f(x,t)∈L∞(0,T;H˙q(Ω))f(x,t)\in L^\infty(0,T;\dot H^q(\Omega)), −1<q≤1-1< q \le 1, for both semidiscrete schemes. For lumped mass method, the optimal L2(Ω)L^2(\Omega)-norm error estimate requires symmetric meshes. Finally, numerical experiments for one- and two-dimensional examples are presented to verify our theoretical results.Comment: 21 pages, 4 figure
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