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arXiv 2402.17154math.AP
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超冷却Stefan问题在一般维度中的存在性

Existence for the Supercooled Stefan Problem in General Dimensions

University of Arizona(亚利桑那大学);University of California at Los Angeles(加州大学洛杉矶分校);University of British Columbia(不列颠哥伦比亚大学)

Sunhi Choi, Inwon C. Kim, Young-Heon Kim

AI总结:

本文证明了超冷却Stefan问题弱解在全局时间内的存在性,适用于一般空间维度和各类初始数据,并展示了解在随机顺序下的最大性。

摘要:

我们证明了超冷却Stefan问题弱解在全局时间内的存在性。我们的结果适用于一般空间维度和一般类别的初始数据。此外,我们的解在某种随机顺序下是最大的,所有起始于相同初始数据的可比弱解中。我们的方法基于布朗运动停止时间的自由目标优化问题,其中主要思想是引入一个超调和成本函数。我们将展示我们的成本函数选择使目标测度尽可能接近给定的领域边界。我们证明中的一个关键成分是双问题的使用:我们证明了双问题的实现,并利用双最优解来表征原问题的最优解。由此,底层的粒子动力学产生了一个超冷却Stefan问题的解。

英文摘要:

We prove the global-time existence of weak solutions to the supercooled Stefan problem. Our result holds in general space dimensions and with a general class of initial data. In addition, our solution is maximal in the sense of a certain stochastic order, among all comparable weak solutions starting from the same initial data. Our approach is based on a free target optimization problem for Brownian stopping times, where the main idea is to introduce a superharmonic cost function in the optimization problem. We will show that our choice of the cost function causes the target measure to accumulate near the prescribed domain boundary as much as possible. A central ingredient in our proof lies in the usage of dual problem: we prove the dual attainment and use the dual optimal solution to characterize the primal optimal solution. It follows in turn that the underlying particle dynamics yields a solution to the supercooled Stefan problem.

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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