On the Convergence of Continuous and Discrete Unbalanced Optimal Transport Models for 1-Wasserstein Distance

IF 2.8 2区 数学 Q1 MATHEMATICS, APPLIED SIAM Journal on Numerical Analysis Pub Date : 2024-03-05 DOI:10.1137/22m1520748
Zhe Xiong, Lei Li, Ya-Nan Zhu, Xiaoqun Zhang
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Abstract

SIAM Journal on Numerical Analysis, Volume 62, Issue 2, Page 749-774, April 2024.
Abstract. We consider a Beckmann formulation of an unbalanced optimal transport (UOT) problem. The [math]-convergence of this formulation of UOT to the corresponding optimal transport (OT) problem is established as the balancing parameter [math] goes to infinity. The discretization of the problem is further shown to be asymptotic preserving regarding the same limit, which ensures that a numerical method can be applied uniformly and the solutions converge to the one of the OT problem automatically. Particularly, there exists a critical value, which is independent of the mesh size, such that the discrete problem reduces to the discrete OT problem for [math] being larger than this critical value. The discrete problem is solved by a convergent primal-dual hybrid algorithm and the iterates for UOT are also shown to converge to that for OT. Finally, numerical experiments on shape deformation and partial color transfer are implemented to validate the theoretical convergence and the proposed numerical algorithm.
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论 1-Wasserstein 距离的连续和离散非平衡最优传输模型的收敛性
SIAM 数值分析期刊》第 62 卷第 2 期第 749-774 页,2024 年 4 月。 摘要我们考虑了不平衡最优输运(UOT)问题的贝克曼公式。当平衡参数[math]达到无穷大时,UOT 的[math]-收敛性被确定为相应的最优传输(OT)问题。进一步证明了问题的离散化对同一极限具有渐近保全性,这确保了数值方法可以均匀地应用,并且解自动收敛到 OT 问题的解。特别是存在一个与网格大小无关的临界值,当[math]大于该临界值时,离散问题会简化为离散加时赛问题。离散问题通过收敛的初等-二元混合算法求解,UOT 的迭代也证明收敛于 OT 的迭代。最后,对形状变形和部分颜色转移进行了数值实验,以验证理论收敛性和所提出的数值算法。
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来源期刊
CiteScore
4.80
自引率
6.90%
发文量
110
审稿时长
4-8 weeks
期刊介绍: SIAM Journal on Numerical Analysis (SINUM) contains research articles on the development and analysis of numerical methods. Topics include the rigorous study of convergence of algorithms, their accuracy, their stability, and their computational complexity. Also included are results in mathematical analysis that contribute to algorithm analysis, and computational results that demonstrate algorithm behavior and applicability.
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