A nonlinear least-squares convexity enforcing 𝐶⁰ interior penalty method for the Monge–Ampère equation on strictly convex smooth planar domains
We construct a nonlinear least-squares finite element method for computing the smooth convex solutions of the Dirichlet boundary value problem of the Monge-Ampère equation on strictly convex smooth domains in <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="double-struck upper R squared"> <mml:semantics> <mml:msup> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mi mathvariant="double-struck">R</mml:mi> </mml:mrow> </mml:mrow> <mml:mn>2</mml:mn> </mml:msup> <mml:annotation encoding="application/x-tex">{\mathbb {R}}^2</mml:annotation> </mml:semantics> </mml:math> </inline-formula>. It is based on an isoparametric <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="upper C Superscript 0"> <mml:semantics> <mml:msup> <mml:mi>C</mml:mi> <mml:mn>0</mml:mn> </mml:msup> <mml:annotation encoding="application/x-tex">C^0</mml:annotation> </mml:semantics> </mml:math> </inline-formula> finite element space with exotic degrees of freedom that can enforce the convexity of the approximate solutions. <italic>A priori</italic> and <italic>a posteriori</italic> error estimates together with corroborating numerical results are presented.
Authors
- Susanne C. Brenner (ORCID: https://orcid.org/0000-0001-8330-5667)
- Zhiyu Tan (ORCID: https://orcid.org/0009-0001-0058-1429)
- Hongchao Zhang (ORCID: https://orcid.org/0000-0003-2518-6975)
- Li-yeng Sung (ORCID: https://orcid.org/0000-0002-6100-2160)
Institutions
- Louisiana State University (US)
- Xiamen University (CN)
Publication Details
- Journal
- Communications of the American Mathematical Society
- Published
- 2024-10-09
- DOI
- https://doi.org/10.1090/cams/39
- Citations
- 1
- Primary Topic
- Nonlinear Partial Differential Equations
- Type
- article
- Field-Weighted Citation Impact
- 0.97
Funders
- National Science Foundation