Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash 100 tok/s
Gemini 2.5 Pro 58 tok/s Pro
GPT-5 Medium 29 tok/s
GPT-5 High 29 tok/s Pro
GPT-4o 103 tok/s
GPT OSS 120B 480 tok/s Pro
Kimi K2 215 tok/s Pro
2000 character limit reached

Remarks on sharp boundary estimates for singular and degenerate Monge-Ampère equations (2206.00492v2)

Published 1 Jun 2022 in math.AP

Abstract: By constructing appropriate smooth, possibly non-convex supersolutions, we establish sharp lower bounds near the boundary for the modulus of nontrivial solutions to singular and degenerate Monge-Amp`ere equations of the form $\det D2 u =|u|q$ with zero boundary condition on a bounded domain in $\mathbb{R}n$. These bounds imply that currently known global H\"older regularity results for these equations are optimal for all $q$ negative, and almost optimal for $0\leq q\leq n-2$. Our study also establishes the optimality of global $C{\frac{1}{n}}$ regularity for convex solutions to the Monge-Amp`ere equation with finite total Monge-Amp`ere measure. Moreover, when $0\leq q<n-2$, the unique solution has its gradient blowing up near any flat part of the boundary. The case of $q$ being $0$ is related to surface tensions in dimer models. We also obtain new global log-Lipschitz estimates, and apply them to the Abreu's equation with degenerate boundary data.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Summary

We haven't generated a summary for this paper yet.

Ai Generate Text Spark Streamline Icon: https://streamlinehq.com

Paper Prompts

Sign up for free to create and run prompts on this paper using GPT-5.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-up Questions

We haven't generated follow-up questions for this paper yet.

Authors (1)

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube