Schrödinger势的梯度估计:收敛到Brenier映射和定量稳定性

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2022-07-28 DOI:10.1080/03605302.2023.2215527
Alberto Chiarini, Giovanni Conforti, Giacomo Greco, Luca Tamanini
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引用次数: 7

摘要

在允许无界密度和支撑点的一般假设下,我们证明了在小时间极限下Schrödinger势的梯度收敛于(唯一确定的)Kantorovich势的梯度。此外,我们为Schrödinger问题(SP)的最优值和最优耦合提供了新的定量稳定性估计,我们用负阶加权齐次Sobolev范数表示。后者编码了边界之间2-Wasserstein距离的线性化行为。这两个结果的证明首次突出了Schrödinger电位的梯度边界的相关性,我们在这里建立了全面的一般性,在Schrödinger桥梁的短期行为分析中。最后,我们讨论了我们的结果如何转化为二次熵最优传输的框架,这是一个更适合机器学习和数据科学应用的SP版本。
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Gradient estimates for the Schrödinger potentials: convergence to the Brenier map and quantitative stability
Abstract We show convergence of the gradients of the Schrödinger potentials to the (uniquely determined) gradient of Kantorovich potentials in the small-time limit under general assumptions on the marginals, which allow for unbounded densities and supports. Furthermore, we provide novel quantitative stability estimates for the optimal values and optimal couplings for the Schrödinger problem (SP), that we express in terms of a negative order weighted homogeneous Sobolev norm. The latter encodes the linearized behavior of the 2-Wasserstein distance between the marginals. The proofs of both results highlight for the first time the relevance of gradient bounds for Schrödinger potentials, that we establish here in full generality, in the analysis of the short-time behavior of Schrödinger bridges. Finally, we discuss how our results translate into the framework of quadratic Entropic Optimal Transport, that is a version of SP more suitable for applications in machine learning and data science.
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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