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arxiv: 1704.02912 · v2 · pith:F7LIFX4Enew · submitted 2017-04-10 · 🧮 math.NA · cs.NA

Sharp convergence rates of time discretization for stochastic time-fractional PDEs subject to additive space-time white noise

classification 🧮 math.NA cs.NA
keywords alphastochastictimeconvergencedimensionmathbbnoisenumerical
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The stochastic time-fractional equation $\partial_t \psi -\Delta\partial_t^{1-\alpha} \psi = f + \dot W$ with space-time white noise $\dot W$ is discretized in time by a backward-Euler convolution quadrature for which the sharp-order error estimate \[ {\mathbb E}\|\psi(\cdot,t_n)-\psi_n\|_{L^2(\mathcal{O})}^2=O(\tau^{1-\alpha d/2}) \] is established for $\alpha\in(0,2/d)$, where $d$ denotes the spatial dimension, $\psi_n$ the approximate solution at the $n^{\rm th}$ time step, and $\mathbb{E}$ the expectation operator. In particular, the result indicates optimal convergence rates of numerical solutions for both stochastic subdiffusion and diffusion-wave problems in one spatial dimension. Numerical examples are presented to illustrate the theoretical analysis.

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