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A recovery based linear finite element method for the Monge–Ampère equation

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Abstract

In this paper, we study finite element approximations of a fourth-order perturbed semilinear partial differential equation that arises naturally in the computation of viscosity solutions to the fully nonlinear Monge–Ampère equation. We develop a novel recovery-based C0C^0 linear finite element method for discretizing this model problem. The key analytical tool is a Miranda–Talenti-type estimate for the recovery operator, which guides the formulation of the discrete scheme and guarantees its well-posedness. We rigorously establish convergence in the H2H^2 norm by employing a fixed-point argument. Furthermore, optimal H1H^1-error estimates are derived using a duality argument. Numerical experiments confirm the efficiency of the proposed method and validate the theoretical convergence results.

Introduction

In this paper, we consider the fully nonlinear Monge–Ampère equation with Dirichlet boundary conditions:

det⁡(D2u)=fin Ω,(1)\det(D^2 u) = f \quad\text{in } \Omega, \tag*{(1)}
u=gon ∂Ω,(2)u = g \quad\text{on } \partial\Omega, \tag*{(2)}

where Ω⊂R2\Omega\subset\mathbb{R}^2 is a convex polygonal domain with Lipschitz continuous boundary Γ=∂Ω\Gamma= \partial\Omega, and D2uD^2u denotes the Hessian matrix of the scalar function uu. The nonlinearity of the equation is captured by the determinant of the Hessian. Such equations arise in a variety of scientific and engineering contexts, such as in problems from differential geometry [23, 29], optical reflector design [43], and the theory of optimal transport [3, 41]. For the Monge–Ampère equation, alternative notions of solutions, such as Aleksandrov and viscosity solutions [9, 23, 26, 29], have been developed over the past century, as classical solutions may not exist even when the data ff and gg are smooth.

Due to its nonlinear nature and lack of classical variational structure, the development of numerical techniques for the Monge–Ampère equation is challenging. The first numerical methods can be traced back to the late 1980s when Oliker and Prussner [40] constructed the finite difference methods to compute the Aleksandrov solutions. In 2008, Oberman proposed a wide-stencil framework for solving the Monge–Ampère equation [39]. Thus far, a variety of numerical methods have been proposed for the approximation of Monge–Ampère equations, including filtered schemes [24, 25], L2L^2-projection methods and C0C^0 interior penalty methods [1, 4, 5, 6, 33], least-squares approaches [8, 16], vanishing moment methods [12, 18, 19, 20, 21, 32], and two-scale finite element methods [37, 38]. For a comprehensive overview, we refer the reader to the review articles [17, 34, 35].

We concentrate on the finite element approximation of the following singularly perturbed fourth-order semilinear partial differential equation:

−εΔ2uε+det⁡(D2uε)=fin Ω,(3)-\varepsilon\Delta^2 u^\varepsilon+ \det(D^2u^\varepsilon) = f \quad\text{in } \Omega, \tag*{(3)}
uε=gon ∂Ω,(4)u^\varepsilon= g \quad\text{on } \partial\Omega, \tag*{(4)}
Δuε=εon ∂Ω.(5)\Delta u^\varepsilon= \varepsilon\quad\text{on } \partial\Omega. \tag*{(5)}

The solution of the model problem (1.2) has been shown to converge uniformly (in the viscosity sense) to the viscosity solution of the Monge–Ampère equation (1.1) as ε→0+\varepsilon\to0^+, in the radially symmetric setting [20, 22]. Thus, equation (1.2) offers a regularization framework for computing viscosity solutions of the Monge–Ampère equation. Following the assumptions in [12, 18], we further suppose that the following a priori estimates hold:

∥uε∥Hj(Ω)=O(ε12−j)(j=2,3),∥uε∥Wj,∞(Ω)=O(ε1−j)(j=1,2),∥Φε∥L2(Ω)=O(ε−12),∥Φε∥L∞(Ω)=O(ε−1),(6)\begin{aligned} \lVert u^\varepsilon\rVert_{H^j(\Omega)} &= O\left(\varepsilon^{\frac{1}{2}-j}\right) \quad(j=2,3), \qquad \lVert u^\varepsilon\rVert_{W^{j,\infty}(\Omega)} = O\left(\varepsilon^{1-j}\right) \quad(j=1,2), \\ \lVert\Phi^\varepsilon\rVert_{L^2(\Omega)} &= O\left(\varepsilon^{-\frac{1}{2}}\right), \qquad \lVert\Phi^\varepsilon\rVert_{L^\infty(\Omega)} = O\left(\varepsilon^{-1}\right), \tag*{(6)} \end{aligned}

where Φε\Phi^\varepsilon denotes the cofactor matrix of the Hessian D2uεD^2u^\varepsilon. Additionally, we assume that problem (1.2) admits a unique convex solution uε∈H3(Ω)∩W2,∞(Ω)u^\varepsilon\in H^3(\Omega) \cap W^{2,\infty}(\Omega), and satisfies (6).

For the semilinear equation (1.2), one of the primary numerical challenges lies in discretizing the biharmonic operator. Classical finite element methods for the biharmonic operator, such as conforming finite element methods [21], mixed finite element methods [18], nonconforming finite element methods [32], and C0C^0 interior penalty methods [15, 35], have been applied to solve (1.2). Most of these studies use at least quadratic elements. In recent years, there has been increasing interest in designing linear finite element methods for solving fourth-order PDEs; see, e.g., [11, 13, 28, 30, 31, 44]. However, these approaches are not directly applicable to (1.2) due to difficulties in establishing stability conditions and the lack of consistency in the finite element functions. To the best of our knowledge, [12] is the first work devoted to the development of linear element methods for solving the model equation (1.2). However, certain assumptions are required in [12] to ensure stability.

The primary goal of this paper is to propose a new linear element-based method with rigorous mathematical theory. The main motivation comes from our recent work on the Hamilton–Jacobi–Bellman equation [14], where a novel gradient recovery operator is proposed using the Morley finite element function as a bridge. Unlike existing gradient recovery operators [27], the proposed operator is a true gradient of a Morley finite element function, which allows us to establish the consistency of the gradient recovery operator for finite element functions. In addition, a discrete Miranda–Talenti (MT) estimate for the gradient recovery operator is established in [14]. Unlike the analysis method in [12], our analysis uses the discrete MT estimate to design the finite element scheme and analyze the stability of the method. Based on the Banach fixed-point theorem, we prove the existence and uniqueness of the finite element solution, as well as a discrete H2H^2 error estimate. What we want to emphasize is that the lower-order norm error estimates based on the MT estimate are missing from the literature. To obtain the optimal error estimate in the H1H^1 norm, we employ a duality argument. Compared to the recovery-based finite element method in [12], our method achieves O(h2)O(h^2) (O(h)O(h)) convergence in the L2L^2 norm (H1H^1 norm), while the method in [12] only yields O(h)O(h) (O(h0.5)O(h^{0.5})) convergence in the L2L^2 norm (H1H^1 norm).

The remainder of the paper is organized as follows. In § 2, we introduce the necessary notation for finite element functions and review the gradient recovery operator developed in [14]. Section 3 is devoted to the design and analysis of a finite element scheme for the linearized model, with particular emphasis on the application of a discrete MT estimate. In Section 4, we present a recovery-based finite element method for the semilinear equation and establish error estimates in the discrete H2H^2 and H1H^1 norms. Section 5 contains several numerical experiments that illustrate the performance of the proposed method. Concluding remarks are provided in Section 6. Additional properties of the gradient recovery operator are discussed in Appendix A.

Preliminaries

Notation

Let ∣D∣|D| denote the Lebesgue measure of a measurable set D⊂R2D \subset\mathbb{R}^2. For s≥0s \ge0 and p∈[1,∞]p \in[1,\infty], we denote by Ws,p(D)W^{s,p}(D) the standard Sobolev space on the domain DD. In particular, we write L0p(D):=W00,p(D)L^p_0(D) := W^{0,p}_0(D) and Hs(D):=Ws,2(D)H^s(D) := W^{s,2}(D). The corresponding norm and semi-norm on Ws,p(D)W^{s,p}(D) are denoted by ∥⋅∥Ws,p(D)\|\cdot\|_{W^{s,p}(D)} and ∣⋅∣Ws,p(D)|\cdot|_{W^{s,p}(D)}, respectively. Let H01(D)H^1_0(D) denote the subspace of H1(D)H^1(D) consisting of functions that vanish on ∂D\partial D in the trace sense. The inner product in L2(D)L^2(D) is denoted by (⋅,⋅)L2(D)(\cdot,\cdot)_{L^2(D)}, and let

V:=H2(Ω),V0:=H2(Ω)∩H01(Ω),Vg:={v∈V:v∣∂Ω=g}.V := H^2(\Omega), \qquad V_0 := H^2(\Omega) \cap H^1_0(\Omega), \qquad V_g := \{v \in V : v|_{\partial\Omega} = g\}.

Let Th\mathcal{T}_h be a shape-regular and conforming simplicial triangulation of the domain Ω\Omega. For each element T∈ThT \in\mathcal{T}_h, denote its diameter by hT:=diam⁡(T)h_T := \operatorname{diam}(T), and let h:=max⁡T∈ThhTh := \max_{T \in\mathcal{T}_h} h_T represent the mesh size. Let Vh\mathcal{V}_h and Eh\mathcal{E}_h denote the sets of vertices and edges in Th\mathcal{T}_h, respectively. For each edge e∈Ehe \in\mathcal{E}_h, let heh_e denote its length. The edge set Eh\mathcal{E}_h is partitioned into interior and boundary edges, denoted by EhI\mathcal{E}^I_h and EhB\mathcal{E}^B_h, respectively. Likewise, the vertex set Vh\mathcal{V}_h is divided into interior and boundary vertices, denoted by VhI\mathcal{V}^I_h and VhB\mathcal{V}^B_h. For each element T∈ThT \in\mathcal{T}_h, we let VT\mathcal{V}_T and MT\mathcal{M}_T denote the sets of vertices and midpoints of the edges of TT, respectively. We define Tp\mathcal{T}_p as the collection of elements in Th\mathcal{T}_h that share a common vertex pp, and Te\mathcal{T}_e as the set of elements sharing a common edge e∈Ehe \in\mathcal{E}_h. Finally, let MhI\mathcal{M}^I_h and MhB\mathcal{M}^B_h denote the sets of interior and boundary edge midpoints, respectively, and define Mh:=MhI∪MhB\mathcal{M}_h := \mathcal{M}^I_h \cup\mathcal{M}^B_h.

For any edge e∈Ehe \in\mathcal{E}_h, we fix a (constant) unit normal vector ne∈R2n_e \in\mathbb{R}^2 to ee. In the case where e∈EhBe \in\mathcal{E}^B_h, we take nen_e to be the outward unit normal vector to ∂Ω\partial\Omega restricted to ee. We denote by tet_e the unit tangent vector to ee obtained by rotating nen_e counterclockwise by π/2\pi/2. The jump operator ⟦⋅⟧\llbracket\cdot\rrbracket across ee is then defined as in [36]:

⟦v⟧:=v∣Tout−v∣Tinif e=∂Tout∩∂Tin∈EhI,⟦v⟧:=v∣Toutif e=∂Tout∩∂Ω∈EhB.\begin{aligned} \llbracket v \rrbracket&:= v|_{T_{\mathrm{out}}} - v|_{T_{\mathrm{in}}} && \text{if } e = \partial T_{\mathrm{out}} \cap\partial T_{\mathrm{in}} \in\mathcal{E}^I_h, \\ \llbracket v \rrbracket&:= v|_{T_{\mathrm{out}}} && \text{if } e = \partial T_{\mathrm{out}} \cap\partial\Omega\in\mathcal{E}^B_h. \end{aligned}

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