Do We Understand Putin's Russia?

Jonathan Haslam
George F. Kennan Professor in the School of Historical Studies
November 7, 2015
We should not assume that making sense of post-Soviet Russia was ever going to be easy. Great Powers that lose empires bear grudges and the speed with which an empire is lost can exacerbate the problem. No one can expect that a powerful country run by a former secret policeman is going to operate by the same rules of the game to which we are accustomed. Quite simply, what may seem sensible or rational to ourselves is irrelevant. In this public lecture, Jonathan Haslam, George F.

Topological effects in metals: from chiral and gyrotropic magnetic effects to quenched Majoranas

Joel Moore
University of California, Berkeley
November 7, 2015
The recent advances in our understanding of topological states of free-fermion insulators give some valuable concepts and tools for the analysis of metals. The first part of this talk focuses on low-energy electrodynamic responses of simple metals, including the question of when recently discovered Weyl semimetals show a "chiral magnetic effect" related to the chiral anomaly.

Topological and combinatorial methods in Theoretical Distributed Computing

Dmitry Feichtner-Kozlov
Institute for Algebra, Geometry, Topology, and their Applications, University of Bremen
November 7, 2015
In the first half of the talk I will give a very compressed introduction into parts of Theoretical Distributed Computing from the point of view of mathematician. I will describe how to construct simplicial models whose combinatorics contains important information about computability and complexity of standard distributed tasks. In the second part, I will outline our recent progress on estimating the complexity of the so-called Weak Symmetry Breaking task, where we are able to derive some quite surprising results.

Hierarchical clustering on asymmetric networks

Facundo Mémoli
Ohio State University
November 7, 2015
The problem of determining clusters in a data set admits different interpretations depending on whether the data is metric, symmetric but not necessarily metric, or asymmetric. Whereas there is a good degree of understanding of what are the natural methods for clustering symmetric data, the landscape of methods for clustering asymmetric data is not so well understood. It is possible to study and characterize hierarchical clustering methods that operate on asymmetric networks in an axiomatic manner.