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The inverse reflector problem arises in geometrical nonimaging optics: Given a light source and a target, the question is how to design a reflecting free-form surface such that a desired light density distribution is generated on the…

Numerical Analysis · Mathematics 2015-03-27 Kolja Brix , Yasemin Hafizogullari , Andreas Platen

This work establishes a framework for solving inverse boundary problems with the geodesic based quadratic Wasserstein distance ($W_{2}$). A general form of the Fr\'echet gradient is systematically derived by optimal transportation (OT)…

Numerical Analysis · Mathematics 2022-10-31 Gang Bao , Yixuan Zhang

In this paper, we show that the near field reflector problem is a nonlinear optimization problem. From the corresponding functional and constraint function, we derive the Monge-Amp\`ere type equation for such a problem.

Analysis of PDEs · Mathematics 2012-03-13 Jiakun Liu

We rephrase Monge's optimal transportation (OT) problem with quadratic cost--via a Monge-Amp\`ere equation--as an infinite-dimensional optimization problem, which is in fact a convex problem when the target is a log-concave measure with…

Numerical Analysis · Mathematics 2017-08-29 Michael Lindsey , Yanir A. Rubinstein

We consider the inverse refractor and the inverse reflector problem. The task is to design a free-form lens or a free-form mirror that, when illuminated by a point light source, produces a given illumination pattern on a target. Both…

Optics · Physics 2015-12-08 Kolja Brix , Yasemin Hafizogullari , Andreas Platen

We consider a PDE approach to numerically solving the reflector antenna problem by solving an Optimal Transport problem on the unit sphere with cost function $c(x,y) = -2\log \left\Vert x - y \right\Vert$. At each point on the sphere, we…

Numerical Analysis · Mathematics 2021-11-10 Brittany Froese Hamfeldt , Axel G R Turnquist

Optimal transport (OT) is a powerful geometric tool used to compare and align probability measures following the least effort principle. Despite its widespread use in machine learning (ML), OT problem still bears its computational burden,…

Machine Learning · Computer Science 2023-08-14 Oliver Struckmeier , Ievgen Redko , Anton Mallasto , Karol Arndt , Markus Heinonen , Ville Kyrki

Many problems in geometric optics or convex geometry can be recast as optimal transport problems: this includes the far-field reflector problem, Alexandrov's curvature prescription problem, etc. A popular way to solve these problems…

Numerical Analysis · Mathematics 2017-03-08 Jun Kitagawa , Quentin Mérigot , Boris Thibert

In this paper we propose a method to design a freeform lens including the effect of Fresnel reflections on the transmitted intensity. This method is elaborated for a lens with one freeform surface shaping a far-field target from a point…

Monotone gradient functions play a central role in solving the Monge formulation of the optimal transport (OT) problem, which arises in modern applications ranging from fluid dynamics to robot swarm control. When the transport cost is the…

Machine Learning · Computer Science 2025-09-25 Shreyas Chaudhari , Srinivasa Pranav , José M. F. Moura

We consider the following geometric optics problem: Construct a system of two reflectors which transforms a spherical wavefront generated by a point source into a beam of parallel rays. This beam has a prescribed intensity distribution. We…

Analysis of PDEs · Mathematics 2015-05-13 Tilmann Glimm

A numerical method for the solution of the elliptic Monge-Ampere Partial Differential Equation, with boundary conditions corresponding to the Optimal Transportation (OT) problem is presented. A local representation of the OT boundary…

Numerical Analysis · Mathematics 2012-08-27 Jean-David Benamou , Brittany D. Froese , Adam M. Oberman

We motivate then formulate a novel variant of the near-field reflector problem and call it the near-field reflector problem with spatial restrictions. Let $O$ be an anisotropic point source of light and assume that we are given a bounded…

Analysis of PDEs · Mathematics 2023-01-04 Dylanger Pittman

We focus on Optimal Transport PDE on the unit sphere $\mathbb{S}^2$ with a particular type of cost function $c(x,y) = F(x \cdot y, x \cdot \hat{e}, y \cdot \hat{e})$ which we call cost functions with preferential direction, where $\hat{e}…

Analysis of PDEs · Mathematics 2024-07-11 Axel G. R. Turnquist

Finding optimal trajectories for multiple traffic demands in a congested network is a challenging task. Optimal transport theory is a principled approach that has been used successfully to study various transportation problems. Its usage is…

Physics and Society · Physics 2024-10-10 Abdullahi Adinoyi Ibrahim , Michael Muehlebach , Caterina De Bacco

Inverse optimal transport (OT) refers to the problem of learning the cost function for OT from observed transport plan or its samples. In this paper, we derive an unconstrained convex optimization formulation of the inverse OT problem,…

Machine Learning · Computer Science 2021-07-06 Shaojun Ma , Haodong Sun , Xiaojing Ye , Hongyuan Zha , Haomin Zhou

In this paper, we discuss a mathematical model for inverse freeform design of an optical system with two reflectors in which light transfers from a point source to a point target. In this model, the angular light intensity emitted from the…

We propose a volumetric formulation for computing the Optimal Transport problem defined on surfaces in $\mathbb{R}^3$, found in disciplines like optics, computer graphics, and computational methodologies. Instead of directly tackling the…

Numerical Analysis · Mathematics 2024-05-16 Richard Tsai , Axel G. R. Turnquist

Optimal transportation of raw material from suppliers to customers is an issue arising in logistics that is addressed here with a continuous model relying on optimal transport theory. A physics informed neuralnetwork method is advocated…

Numerical Analysis · Mathematics 2025-08-19 Alexandre Caboussat , Anna Peruso

Many problems in machine learning involve calculating correspondences between sets of objects, such as point clouds or images. Discrete optimal transport provides a natural and successful approach to such tasks whenever the two sets of…

Machine Learning · Statistics 2019-02-28 David Alvarez-Melis , Stefanie Jegelka , Tommi S. Jaakkola
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