Iterative scheme for solving optimal transportation problems arising in reflector design

TL;DR

This paper introduces an iterative numerical scheme for solving optimal transportation problems in reflector design, enabling finer mesh resolution and improved computational efficiency over traditional discretization methods.

Contribution

The paper proposes an iterative LP-based scheme that reduces constraints iteratively, allowing for finer meshes in reflector design problems using optimal transportation theory.

Findings

The scheme converges in tested cases.

It enables the use of much finer meshes.

It is adaptable to other beam shaping problems.

Abstract

We consider the geometric optics problem of finding a system of two reflectors that transform a spherical wavefront into a beam of parallel rays with prescribed intensity distribution. Using techniques from optimal transportation theory, it has been shown before that this problem is equivalent to an infinite dimensional linear programming (LP) problem. We investigate techniques for constructing the two reflectors numerically. A straightforward discretization of this problem has the disadvantage that the number of constraints increases rapidly with the mesh size. So with this technique only very coarse meshes are practical. To address this well-known issue we propose an iterative solution scheme. In each step an LP problem is solved. Information from the previous iteration step is used to reduce the number of constraints necessary. As a proof of concept we apply our proposed scheme to solve a problem with synthetic data. We give evidence that the scheme converges. We also show that it allows for much finer meshes than a simple discretization scheme. There exists a growing literature for the application of optimal transportation theory to other beam shaping problems. Our proposed scheme is easy to adapt for these problems as well.