In this paper we discuss a reduced basis method for linear evolution PDEs, which is based on the application of the Laplace transform. The main advantage of this approach consists in the fact that, differently from time stepping methods, like Runge-Kutta integrators, the Laplace transform allows to compute the solution directly at a given instant, which can be done by approximating the contour integral associated to the inverse Laplace transform by a suitable quadrature formula. In terms of the reduced basis methodology, this determines a significant improvement in the reduction phase - like the one based on the classical proper orthogonal decomposition (POD) - since the number of vectors to which the decomposition applies is drastically reduced as it does not contain all intermediate solutions generated along an integration grid by a time stepping method. We show the effectiveness of the method by some illustrative parabolic PDEs arising from finance and also provide some evidence that the method we propose, when applied to a simple advection equation, does not suffer the problem of slow decay of singular values which instead affects methods based on time integration of the Cauchy problem arising from space discretization.
翻译:在本文中,我们讨论了线性进化PDE的简化基础方法,该方法以Laplace变换的应用为基础。这一方法的主要优点在于,与时间步法不同,如龙格-库塔集成器,Laplace变换法允许在特定瞬间直接计算解决方案,这可以通过通过适当的二次变换公式来接近与逆向变换Laplace相联的轮廓构件。从缩小基础方法来看,这决定了减排阶段的显著改进,如基于古典正正统分解法(POD)的减值阶段,因为用于分解的矢量数量急剧减少,因为它并不包含通过时间步法在集成电网上产生的所有中间解决方案。我们通过一些从融资中产生的示例性分解式分解法展示了该方法的有效性,并且提供了一些证据,证明我们提出的方法在应用简单的倾斜方方程式时,不会遇到单值缓慢衰减的问题,而会影响基于空间分解问题的时间整合的方法。