论文标题
对称梯度Sobolev空间,并具有重新反击的规范
Symmetric gradient Sobolev spaces endowed with rearrangement-invariant norms
论文作者
论文摘要
提出了一种通过其对称梯度定义的向量值函数的Sobolev类型空间嵌入定理的统一方法。所讨论的Sobolev空间是建立在一般重排的不变规范基于的。相关嵌入中的最佳目标空间是在所有重排空间的类别中确定的。特别是,所有对称梯度SOBOLEV嵌入到重排的目标空间中均表现出与在同一空间建立的完整梯度的相应嵌入相等的。还展示了将嵌入到均匀连续功能及其最佳目标空间中的鲜明条件。相比之下,这些嵌入可能比整个梯度的相应嵌入较弱。建立了对对称梯度SOBOLEV空间的独立兴趣的相关结果。它们包括在最小化的域上的最小假设下的全局近似和扩展定理。还提供了一种基于降低至一维不平等的方法的K功能的公式,这是我们方法的关键。在由非电力类型的非线性驱动的连续性力学中,在数学模型中使用的对称梯度Orlicz-Sobolev空间的情况特别集中。
A unified approach to embedding theorems for Sobolev type spaces of vector-valued functions, defined via their symmetric gradient, is proposed. The Sobolev spaces in question are built upon general rearrangement-invariant norms. Optimal target spaces in the relevant embeddings are determined within the class of all rearrangement-invariant spaces. In particular, all symmetric gradient Sobolev embeddings into rearrangementinvariant target spaces are shown to be equivalent to the corresponding embeddings for the full gradient built upon the same spaces. A sharp condition for embeddings into spaces of uniformly continuous functions, and their optimal targets, are also exhibited. By contrast, these embeddings may be weaker than the corresponding ones for the full gradient. Related results, of independent interest in the theory symmetric gradient Sobolev spaces, are established. They include global approximation and extension theorems under minimal assumptions on the domain. A formula for the K-functional, which is pivotal for our method based on reduction to one-dimensional inequalities, is provided as well. The case of symmetric gradient Orlicz-Sobolev spaces, of use in mathematical models in continuum mechanics driven by nonlinearities of non-power type, is especially focused.