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arxiv: 1607.06948 · v2 · pith:KRTWGO6Rnew · submitted 2016-07-23 · 🧮 math.NA

An Analysis of the Crank-Nicolson Method for Subdiffusion

classification 🧮 math.NA
keywords schemecrank-nicolsonmethodalphathetatimeaccuracyanalysis
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In this work, we analyze a Crank-Nicolson type time stepping scheme for the subdiffusion equation, which involves a Caputo fractional derivative of order $\alpha\in (0,1)$ in time. It hybridizes the backward Euler convolution quadrature with a $\theta$-type method, with the parameter $\theta$ dependent on the fractional order $\alpha$ by $\theta=\alpha/2$, and naturally generalizes the classical Crank-Nicolson method. We develop essential initial corrections at the starting two steps for the Crank-Nicolson scheme, and together with the Galerkin finite element method in space, obtain a fully discrete scheme. The overall scheme is easy to implement, and robust with respect to data regularity. A complete error analysis of the fully discrete scheme is provided, and a second-order accuracy in time is established for both smooth and nonsmooth problem data. Extensive numerical experiments are provided to illustrate its accuracy, efficiency and robustness, and a comparative study also indicates its competitive with existing schemes.

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