Numerical Continuation and SPDE Stability for the 2D Cubic-Quintic Allen-Cahn Equation

被引:12
作者
Kuehn, Christian [1 ]
机构
[1] Vienna Univ Technol, Inst Anal & Sci Comp, A-1040 Vienna, Austria
来源
SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION | 2015年 / 3卷 / 01期
关键词
Allen-Cahn; SPDE; cubic-quintic Ginzburg-Landau; Lyapunov equation; numerical continuation; spectral noise approximation; uncertainty quantification; finite differences; iterative linear solvers; critical transitions; bifurcation diagram; GENERALIZED GINZBURG-LANDAU; LYAPUNOV EQUATIONS; TRAVELING WAVES; WARNING SIGNS; TRANSITIONS; APPROXIMATION; BIFURCATION; PROPAGATION; SIMULATION; PACKAGE;
D O I
10.1137/140993685
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
We study the Allen-Cahn equation with a cubic-quintic nonlinear term and a Q-trace-class stochastic forcing in two spatial dimensions. This stochastic partial differential equation (SPDE) is used as a test case to understand how numerical continuation methods can be carried over to the SPDE setting. First, we compute the deterministic bifurcation diagram for the PDE, i.e., without stochastic forcing. In this case, two locally asymptotically stable steady state solution branches exist upon variation of the linear damping term. Then we consider the Lyapunov operator equation for the locally linearized system around steady states for the SPDE. We discretize the full SPDE using a combination of finite differences and spectral noise approximation obtaining a finite-dimensional system of stochastic ordinary differential equations (SODEs). The large system of SODEs is used to approximate the Lyapunov operator equation via covariance matrices. The covariance matrices are numerically continued along the two bifurcation branches. We show that we can quantify the stochastic fluctuations along the branches. We also demonstrate scaling laws near branch and fold bifurcation points. Furthermore, we perform computational tests to show that, even with a suboptimal computational setup, we can quantify the subexponential-timescale fluctuations near the deterministic steady states upon stochastic forcing on a standard desktop computer setup. Hence, the proposed method for numerical continuation of SPDEs has the potential to allow for rapid parametric uncertainty quantification of spatio-temporal stochastic systems.
引用
收藏
页码:762 / 789
页数:28
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