NANAFeb 27, 2017

An Analysis of the Crank-Nicolson Method for Subdiffusion

arXiv:1607.0694891 citationsh-index: 44
AI Analysis

For researchers in fractional PDEs, this work provides a robust and efficient numerical scheme with rigorous error analysis, though it is an incremental improvement over existing methods.

The paper analyzes a Crank-Nicolson type time stepping scheme for subdiffusion equations with Caputo fractional derivatives, achieving second-order accuracy in time for both smooth and nonsmooth data, as demonstrated through numerical experiments.

In this work, we analyze a Crank-Nicolson type time stepping scheme for the subdiffusion equation, which involves a Caputo fractional derivative of order $α\in (0,1)$ in time. It hybridizes the backward Euler convolution quadrature with a $θ$-type method, with the parameter $θ$ dependent on the fractional order $α$ by $θ=α/2$, 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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