Numerical Ergodicity of Stochastic Allen–Cahn Equation driven by Multiplicative White Noise
Zhihui Liu
我们建立了完全离散的单体SPDE方案的独特人体工学,具有多项式增长漂移和由乘法白噪声驱动的边界扩散系数。 我们方法的主要成分取决于Lyapapov条件的满意度,然后是一个统一的时刻估计,结合完全离散的规律性属性。 我们将原始随机方程转换为等效随机方程,其中离散随机卷积物被均匀控制以得出所需的均匀矩的估计。 将主要结果应用于由乘法白噪声驱动的随机艾伦 - 卡恩方程表明这种完全离散对于任何接口厚度都是独特的人体工程学。 数值实验验证了我们的理论结果。
We establish the unique ergodicity of a fully discrete scheme for monotone SPDEs with polynomial growth drift and bounded diffusion coefficients driven by multiplicative white noise. The main ingredient of our method depends on the satisfaction of a Lyapunov condition followed by a uniform moments' estimate, combined with the regularity property for the full discretization. We transform the original stochastic equation into an equivalent random equation where the discrete stochastic convolutions...