2018
DOI: 10.1051/m2an/2018040
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Optimal error estimates for fully discrete Galerkin approximations of semilinear parabolic equations

Abstract: We consider a semilinear parabolic equation with a large class of nonlinearities without any growth conditions. We discretize the problem with a discontinuous Galerkin scheme dG(0) in time (which is a variant of the implicit Euler scheme) and with conforming finite elements in space. The main contribution of this paper is the proof of the uniform boundedness of the discrete solution. This allows us to obtain optimal error estimates with respect to various norms.

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Cited by 16 publications
(13 citation statements)
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References 26 publications
(30 reference statements)
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“…Now, arguing as in [21, Theorems 3.1 and 4.1] for n = 2 and [20] for n = 3, we deduce the existence of a positive constant, let us call it µc, that depends on the data on the problem but not on the discretization parameters such that…”
Section: Convergence and Error Estimatesmentioning
confidence: 52%
See 2 more Smart Citations
“…Now, arguing as in [21, Theorems 3.1 and 4.1] for n = 2 and [20] for n = 3, we deduce the existence of a positive constant, let us call it µc, that depends on the data on the problem but not on the discretization parameters such that…”
Section: Convergence and Error Estimatesmentioning
confidence: 52%
“…This corresponds to an implicit Euler scheme. It is proved in [18,20] that there exist h 0 > 0 and τ 0 > 0 such that…”
Section: Numerical Approximationmentioning
confidence: 99%
See 1 more Smart Citation
“…Further results on optimal rates under minimal regularity assumptions for linear parabolic PDEs can be found, e.g., in [5,9,21]. For semilinear parabolic problems optimal error estimates are also found in [33], where a discontinuous Galerkin method in time and space is considered. This paper is organized as follows.…”
Section: Introductionmentioning
confidence: 99%
“…It is also the state-of-the-art method in many recent papers for the numerical solution of evolution equations of the form (1.2). For example, we refer to [5,15,25,33].…”
Section: Introductionmentioning
confidence: 99%