In this paper we develop and analyse domain decomposition methods for linear systems of equations arising from conforming finite element discretisations of positive Maxwell-type equations. Convergence of domain decomposition methods rely heavily on the efficiency of the coarse space used in the second level. We design adaptive coarse spaces that complement the near-kernel space made of the gradient of scalar functions. This extends the results in [2] to the variable coefficient case and non-convex domains at the expense of a larger coarse space.

翻译：在本文中,我们开发并分析由于正对正Maxwell型方程式的符合有限元素分解而形成方程式线性系统的域分解方法。 域分解方法的趋同在很大程度上取决于二级使用粗粗空间的效率。 我们设计适应性粗糙空间,以补充由星际函数梯度形成的近内核空间。 这将[2]的结果扩大到可变系数立方体和非凝固域,而以更大的粗空为代价。