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arXiv 2410.04441math.AP
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含奇异性与非正则数据的混合局部-非局部椭圆方程的存在性结果

Existence results for mixed local and nonlocal elliptic equations involving singularity and nonregular data

Souvik Bhowmick, Sekhar Ghosh

AI总结:

针对含奇异性与测度数据的混合局部-非局部椭圆方程,运用Schauder不动点定理、Marcinkiewicz空间嵌入等工具,证明弱解、极弱解与对偶解的存在性,拓展了相关算子的已有研究。

摘要:

本文证明了一类含奇异性与测度数据的椭圆问题的弱解、极弱解与对偶解的存在性,该问题表述为:在$Ω$中满足$-Δu+(-Δ)^s u = \frac{f(x)}{u^γ} +μ$,且在$\mathbb R^N \setminus Ω$中具有零Dirichlet边界数据$u=0$。通过逼近一系列关于$0<γ\leq1$和$γ>1$的问题,我们得到了弱解的存在性,证明过程运用了Schauder不动点定理与Marcinkiewicz空间嵌入。本文的创新点在于证明了问题$\mathcal{L}u=μ$的对偶解的存在性及其与弱解的等价性。此外,我们还证明了混合局部-非局部算子$\mathcal{L}=-Δ+(-Δ)^s$的极弱极大值原理与Kato型不等式,它们是保证该问题极弱解存在性的关键工具。结合Kato型不等式、极大值原理与上下解方法,我们证明了$0<γ<1$的极弱解存在性。本文工作拓展了Oliva与Petitta[ESAIM Control Optim. Calc. Var., 22(1):289--308, 2016.]以及Petitta[Adv. Nonlinear Stud., 16(1):115--124, 2016.]针对混合局部-非局部算子的相关研究。

英文摘要:

In this paper, we prove the existence of weak, veryweak and duality solutions to a class of elliptic problems involving singularity and measure data which is given by: $-Δu+(-Δ)^s u = \frac{f(x)}{u^γ} +μ$ in $Ω$ with the zero Dirichlet boundary data $u=0$ in $\mathbb R^N \setminus Ω$. The existence of weak solutions is obtained by approximating a sequence of problems for $0<γ\leq1$ and $γ>1$. We employ Schauder's fixed point theorem and embeddings of Marcinkiewicz spaces. The novelty of our work is that we prove the existence of a duality solution and its equivalence with weak solutions to the problem $\mathcal{L}u=μ$. Moreover, we prove a veryweak maximum principle and a Kato-type inequality for the mixed local-nonlocal operator $\mathcal{L}=-Δ+(-Δ)^s$, which are crucial tools to guarantee the existence of veryweak solutions to the problem. Using a Kato-type inequality, maximum principle together with sub-super solution method, we prove the existence of veryweak solution for $0<γ<1$. Our work extends the studies due to Oliva and Petitta [ESAIM Control Optim. Calc. Var., 22(1):289--308, 2016.] and Petitta [Adv. Nonlinear Stud., 16(1):115--124, 2016.] for the mixed local-nonlocal operator.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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