论文标题

Lagrangian平均曲率方程的梯度估计值,具有关键和超临界阶段

Gradient estimates for the Lagrangian mean curvature equation with critical and supercritical phase

论文作者

Bhattacharya, Arunima, Mooney, Connor, Shankar, Ravi

论文摘要

在本文中,如果Lagrangian阶段至关重要且超临界,并且$ c^{2} $,我们证明了拉格朗日平均曲率方程的内部梯度估计。结合[BHA21,BHA22]中证明的先验内部Hessian估计值,这解决了使用$ C^0 $边界数据的关键和超临界拉格朗日平均曲率方程的Dirichlet边界值问题。我们还为较低的规律性阶段提供了统一的梯度估计,以满足某些其他假设。

In this paper, we prove interior gradient estimates for the Lagrangian mean curvature equation, if the Lagrangian phase is critical and supercritical and $C^{2}$. Combined with the a priori interior Hessian estimates proved in [Bha21, Bha22], this solves the Dirichlet boundary value problem for the critical and supercritical Lagrangian mean curvature equation with $C^0$ boundary data. We also provide a uniform gradient estimate for lower regularity phases that satisfy certain additional hypotheses.

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