Optimal transport theory and applications to physics

Optimal Transport theory contains the core of the solutions to diverse problems in applied mathematics and physics. Recent advances and developments of fast new algorithms have paved the way for major breakthroughs in different domains of physics. Optimal Transport is also widely investigated in signal processing and machine learning as it defines a distance between very general measures and entities of various nature, essential for object recognition and classification. The goal of this workshop is to describe these recent breakthroughs, highlight connections with physical phenomena and harbour discussions to define new challenges, help start projects between participants and draw new research path in the field. The aim is to exploit applications of optimal transport theory to physical phenomena to bring together different expertise, from mathematics, Physics and computational science.