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An Entropic Optimal Transport Numerical Approach to the Reflector Problem

Benamou, Jean-David; Ijzerman, Wilbert; Rukhaia, Giorgi (2020), An Entropic Optimal Transport Numerical Approach to the Reflector Problem, Methods and Applications of Analysis, 27, 4, p. 311 – 340. 10.4310/MAA.2020.v27.n4.a1

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Type
Article accepté pour publication ou publié
Date
2020
Journal name
Methods and Applications of Analysis
Volume
27
Number
4
Publisher
International Press
Pages
311 – 340
Publication identifier
10.4310/MAA.2020.v27.n4.a1
Metadata
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Author(s)
Benamou, Jean-David
CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
Ijzerman, Wilbert
Eindhoven University of Technology [Eindhoven] [TU/e]
Rukhaia, Giorgi
CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
Abstract (EN)
The point source far field reflector design problem is one of the main classic optimal transport problems with a non-euclidean displacement cost [Wang, 2004] [Glimm and Oliker, 2003]. This work describes the use of Entropic Optimal Transport and the associated Sinkhorn algorithm [Cuturi, 2013] to solve it numerically. As the reflector modelling is based on the Kantorovich potentials , several questions arise. First, on the convergence of the discrete entropic approximation and here we follow the recent work of [Berman, 2017] and in particular the imposed discretization requirements therein. Secondly, the correction of the Entropic bias induced by the Entropic OT, as discussed in particular in [Ramdas et al., 2017] [Genevay et al., 2018] [Feydy et al., 2018], is another important tool to achieve reasonable results. The paper reviews the necessary mathematical and numerical tools needed to produce and discuss the obtained numerical results. We find that Sinkhorn algorithm may be adapted, at least in simple academic cases, to the resolution of the far field reflector problem. Sinkhorn canonical extension to continuous potentials is needed to generate continuous reflector approximations. The use of Sinkhorn divergences [Feydy et al., 2018] is useful to mitigate the entropic bias.
Subjects / Keywords
inverse reflector problem; optimal transportation; non-linear optimization

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