"A quantum information approach to statistical mechanics."

"I will show how one can apply quantum information tools to study various problems in statistical mechanics. We focus on classical spin models, which are toy models used in a variety of fields such as magnetism or quantum gravity, and we tackle them from three different angles. First, we show how the partition function of a class of widely different classical spin models (models in different dimensions, different types of many-body interactions, different symmetries, etc) can be mapped to the partition function a single model. Second, we give efficient quantum algorithms to estimate the partition function of various classical spin models, such as the Ising or Potts model. Finally, we outline the possibility of applying quantum information tools to a model of discrete quantum gravity called causal dynamical triangulation."