论文标题
半线性非局部扩散方程的概率方案,具有体积约束
A probabilistic scheme for semilinear nonlocal diffusion equations with volume constraints
论文作者
论文摘要
这项工作提出了一种概率方案,用于求解具有体积约束和可集成核的半线性非局部扩散方程。感兴趣的非本地模型由时间依赖性的半连续性局部差异方程(PIDE)定义,在该方程(PIDE)中,整数分化的操作员既由局部对流扩散和非局部扩散算子组成。我们的数值方案基于非线性Feynman-KAC公式的直接近似,该公式在非线性脚踏方程与随机微分方程之间建立了联系。 Feynman-KAC表示的剥削成功地避免了解决非局部运算符引起的密集线性系统。与现有随机方法相比,我们的方法在平衡时间和空间离散误差后可以实现一阶收敛,这是非局部扩散问题现有概率/随机方法的显着改善。建立了我们的数值方案的错误分析。我们的方法的有效性在两个数值示例中显示。第一个示例考虑了三维非局部扩散方程,以数值验证误差分析结果。第二个例子提出了一个物理问题,该物理问题是由磁性限制融合等离子体中的热传输的研究所激发的。
This work presents a probabilistic scheme for solving semilinear nonlocal diffusion equations with volume constraints and integrable kernels. The nonlocal model of interest is defined by a time-dependent semilinear partial integro-differential equation (PIDE), in which the integro-differential operator consists of both local convection-diffusion and nonlocal diffusion operators. Our numerical scheme is based on the direct approximation of the nonlinear Feynman-Kac formula that establishes a link between nonlinear PIDEs and stochastic differential equations. The exploitation of the Feynman-Kac representation successfully avoids solving dense linear systems arising from nonlocality operators. Compared with existing stochastic approaches, our method can achieve first-order convergence after balancing the temporal and spatial discretization errors, which is a significant improvement of existing probabilistic/stochastic methods for nonlocal diffusion problems. Error analysis of our numerical scheme is established. The effectiveness of our approach is shown in two numerical examples. The first example considers a three-dimensional nonlocal diffusion equation to numerically verify the error analysis results. The second example presents a physics problem motivated by the study of heat transport in magnetically confined fusion plasmas.