In this article we establish exponential moment bounds, moment bounds in fractional order smoothness spaces, a uniform Hölder continuity in time, and strong convergence rates for a class of fully discrete exponential Euler-type numerical approximations of infinite dimensional stochastic convolution processes. The considered approximations involve specific taming and truncation terms and are therefore well suited to be used in the context of SPDEs with non-globally Lipschitz continuous nonlinearities.

中文翻译：

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随机卷积的驯服截断数值逼近的指数矩界和强收敛速度

在本文中，我们建立了无穷维随机卷积过程的一类完全离散的指数Euler型数值逼近的指数矩边界，分数阶平滑空间中的矩边界，一致的Hölder时间连续性以及强收敛速度。所考虑的近似值涉及特定的驯服和截断项，因此非常适合用于具有非全局Lipschitz连续非线性的SPDE。