## SS 2018: Infinite dimensional calculus of variations (M4)

Lectures: Tuesday, 13:00 (ct), RUD 25, 3.007 and Thursday, 09:00 (ct), RUD 25, 3.007
Tutorial: Tuesday, 15.00 (ct), RUD 25, 3.007

### Content

In the theory of calculus of variations, we consider functionals defined on sets of functions with the goal to find critical points of these functionals. Typical applications are: The circle maximizes the area for a given perimeter. The soap film minimizes the area for given volume. A stable elastic deformation minimizes the elastic energy. The lecture starts by recalling the classical theory starting from Bernoulli to Weierstrass for the one-dimensional setting. Using simple functional analytic methods we extend the theory to the multidimensional case including nonlinear elasticity theory.

### Requirements

• Linear functional analysis

### Literature

• B. Dacorogna, Direct Methods in the Calculus of Variations
• B. Dacorogna, Introduction to the Calculus of Variations

### Exams

The oral exams take place from July 30--31, 2018 and from August 2--3, 2018.

## WS 2017/18: Optimal transport and Wasserstein gradient flows

Lecture: Tuesday, 9.00 am (ct), RUD 25, 4.007, weekly
Tutorial: Tuesday, 11.00 am (ct), RUD 25, 4.007, every 2nd week

### Scope

The optimal transport problem was already formulated by Gaspard Monge in the 18 century. It deals with the relocation of an initial distribution of mass to a final distribution, such that the cost of transport is minimal. The formulation of this problem was generalized by Kantorovich in 1942. Besides the original applications in economy, new connections to Problems in geometry, probability theory, and analysis emerged. In particular, in the recent decades a strong connection between partial differential equations, that describe diffusion processes, could be made. These diffusion problems can be formulated as gradient flows of the system's entropy and the so-called Wasserstein distance.

In this module, we introduce the problem of optimal transport, discuss basic results and applications: Monge- and Kantorovich formulation, existence of optimal transport plans, dual formulation, dynamical formulation, diffusion equations as Wasserstein gradient flows.

### Requirements

• Linear functional analysis
• Measure theory

### References

• Ambrosio, Gigli, Savaré, Gradient Flows in Metric Spaces and in the Space of Probability Measures, Lecture in Mathematics ETH Zürich, 2005
• Santambrogio, Optimal Transport for Applied Mathematicians: Calculus of Variations, PDEs, and Modeling, Birkhäuser, 2015

### Ergänzungen

Charakterisierung von Wasserstein-Geodäten

### Exercises

1. Exercise 1 (for 24 Oct, 2017), corrected on 21 October, 2017
2. Exercise 2 (for 7 Nov, 2017)
3. Exercise 3 (for 28 Nov, 2017), corrected on 26 October, 2017
4. Exercise 4 (for 22 Jan, 2018)
5. Exercise 5 (for 6 Feb, 2018)