Numerical Algorithms for Time-Fractional Subdiffusion Equation with Second-Order Accuracy
Author(s) -
Fanhai Zeng,
Changpin Li,
Fawang Liu,
Ian Turner
Publication year - 2015
Publication title -
siam journal on scientific computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.674
H-Index - 147
eISSN - 1095-7197
pISSN - 1064-8275
DOI - 10.1137/14096390x
Subject(s) - mathematics , discretization , norm (philosophy) , convergence (economics) , piecewise , fractional calculus , polynomial , stability (learning theory) , algorithm , numerical analysis , piecewise linear function , mathematical analysis , computer science , economics , machine learning , political science , law , economic growth
This article aims to fill in the gap of the second-order accurate schemes for the time-fractional subdiffusion equation with unconditional stability. Two fully discrete schemes are first proposed for the time-fractional subdiffusion equation with space discretized by finite element method and time discretized by the fractional linear multistep methods. These two methods are unconditionally stable with maximum global convergence order of O ( τ + h r +1 )in the L 2 norm, where τ and h are the step sizes in time and space, respectively, and r is the degree of the piecewise polynomial space. The average convergence rates for the two methods in time are also investigated, which shows that the average convergence rates of the two methods are O ( τ 1 . 5 + h r +1 ). Furthermore, two improved algorithms are constructed, and they are also unconditionally stable and convergent of order O ( τ 2 + h r +1 ). Numerical examples are provided to verify the theoretical analysis. Comparisons between the present algorithms and the existing ones are included, showing that our numerical algorithms exhibit better performances than the known ones
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