超临界相拉格朗日平均曲率流奇异性的先验估计

IF 1.3 2区数学 Q1 MATHEMATICS

Nonlinear Analysis-Theory Methods & Applications Pub Date : 2025-05-13 DOI:10.1016/j.na.2025.113844

Arunima Bhattacharya, Jeremy Wall

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引用次数: 0

摘要

本文在拉格朗日相为超临界的条件下，证明了拉格朗日平均曲率流奇异性的内部先验估计。我们证明了当拉格朗日相是临界和超临界时，雅可比不等式是成立的。我们进一步将我们的结果推广到更广泛的一类拉格朗日平均曲率型方程。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A priori estimates for Singularities of the Lagrangian Mean Curvature Flow with supercritical phase

In this paper, we prove interior a priori estimates for singularities of the Lagrangian mean curvature flow assuming the Lagrangian phase is supercritical. We prove a Jacobi inequality that holds good when the Lagrangian phase is critical and supercritical. We further extend our results to a broader class of Lagrangian mean curvature type equations.

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来源期刊

Nonlinear Analysis-Theory Methods & Applications 数学-数学

CiteScore

3.30

自引率

0.00%

发文量

265

审稿时长

60 days

期刊介绍： Nonlinear Analysis focuses on papers that address significant problems in Nonlinear Analysis that have a sustainable and important impact on the development of new directions in the theory as well as potential applications. Review articles on important topics in Nonlinear Analysis are welcome as well. In particular, only papers within the areas of specialization of the Editorial Board Members will be considered. Authors are encouraged to check the areas of expertise of the Editorial Board in order to decide whether or not their papers are appropriate for this journal. The journal aims to apply very high standards in accepting papers for publication.