Non-locality, non-linearity, and existence of solutions to the Dirichlet problem for least gradient functions in metric measure spaces

IF 1.3 2区 数学 Q1 MATHEMATICS Revista Matematica Iberoamericana Pub Date : 2022-01-08 DOI:10.4171/rmi/1385
Joshua Kline
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引用次数: 2

Abstract

We study the Dirichlet problem for least gradient functions for domains in metric spaces equipped with a doubling measure and supporting a (1,1)-Poincaré inequality when the boundary of the domain satisfies a positive mean curvature condition. In this setting, it was shown by Malý, Lahti, Shanmugalingam, and Speight that solutions exist for continuous boundary data. We extend these results, showing existence of solutions for boundary data that is approximable from above and below by continuous functions. We also show that for each f ∈ L 1 ( ∂ Ω) , there is a least gradient function in Ω whose trace agrees with f at points of continuity of f , and so we obtain existence of solutions for boundary data which is continuous almost everywhere. This is in contrast to a result of Spradlin and Tamasan, who constructed an L 1 -function on the unit circle which has no least gradient solution in the unit disk in R 2 . Modifying the example of Spradlin and Tamasan, we show that the space of solvable L 1 -functions on the unit circle is non-linear, even though the unit disk satisfies the positive mean curvature condition.
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度量测度空间中最小梯度函数Dirichlet问题解的非局部性、非线性和存在性
研究了具有双重测度且支持(1,1)- poincar不等式的度量空间中,当区域边界满足正平均曲率条件时,最小梯度函数的Dirichlet问题。在这种情况下,Malý、Lahti、Shanmugalingam和Speight证明了连续边界数据存在解。我们推广了这些结果,证明了连续函数上下近似的边界数据解的存在性。我们还证明了对于每个f∈L 1(∂Ω),在Ω中存在一个最小梯度函数,其迹在f的连续性点处与f一致,从而得到了边界数据几乎处处连续的解的存在性。这与Spradlin和Tamasan的结果相反,他们在单位圆上构造了一个在r2的单位圆盘上没有最小梯度解的L -函数。修正了Spradlin和Tamasan的例子,证明了单位圆上可解的L -函数空间是非线性的,即使单位圆盘满足正平均曲率条件。
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来源期刊
CiteScore
2.40
自引率
0.00%
发文量
61
审稿时长
>12 weeks
期刊介绍: Revista Matemática Iberoamericana publishes original research articles on all areas of mathematics. Its distinguished Editorial Board selects papers according to the highest standards. Founded in 1985, Revista is a scientific journal of Real Sociedad Matemática Española.
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