We provide a unified analysis of a posteriori and a priori error bounds for a broad class of discontinuous Galerkin and $C^0$-IP finite element approximations of fully nonlinear second-order elliptic Hamilton--Jacobi--Bellman and Isaacs equations with Cordes coefficients. We prove the existence and uniqueness of strong solutions in $H^2$ of Isaacs equations with Cordes coefficients posed on bounded convex domains. We then show the reliability and efficiency of computable residual-based error estimators for piecewise polynomial approximations on simplicial meshes in two and three space dimensions. We introduce an abstract framework for the a priori error analysis of a broad family of numerical methods and prove the quasi-optimality of discrete approximations under three key conditions of Lipschitz continuity, discrete consistency and strong monotonicity of the numerical method. Under these conditions, we also prove convergence of the numerical approximations in the small-mesh limit for minimal regularity solutions. We then show that the framework applies to a range of existing numerical methods from the literature, as well as some original variants. A key ingredient of our results is an original analysis of the stabilization terms. As a corollary, we also obtain a generalization of the discrete Miranda--Talenti inequality to piecewise polynomial vector fields.
翻译:我们统一分析一系列不连续的加列金和美元0美元-美元-IP的有限元素的后端和先验误差,将完全非线性第二等离子体汉密尔顿-贾科比-贝尔曼和艾萨克等方与科德斯系数相近。我们证明,在以撒方方公式中,以Cordes 系数为约束 convex 域,以2美元计算Cordes 系数,这些方程式的强有力解决方案的存在和独特性。然后,我们展示了在2个和3个空间维度的简化中间线上,可比较的基于残余误差估计仪的可靠性和效率。我们引入了一个抽象框架,用于对广泛数字方法组合的先验误分析,并证明利普西茨连续的三个关键条件下离散近差近率的准和独特性。在这些情况之下,我们还证明,在最小常规性解决方案中,以小偏差值为最小值的多端近似值的误差估计器。然后,我们展示了这个框架适用于一个原数域,即现有稳定性数据模型的模型,我们从一个原始的变式,也从一个原始的模型到一个原始的版本,从一个原始的模型到一个原始的模型,从一个原始的模型到一个原始的模型的版本,从一个原始的版本,从一个原始的版本到一个原始的版本的版本,从一个原始的版本,从一个原始的版本到一个原始的版本,从一个原始的模型到一个原始的版本,从一个原始的版本到一个原始的版本,从一个原始的版本的版本。