Module description
Syllabus
Canonical ensembles and distributions, transfer matrices, asymptotic methods (Laplace and saddle point integration), approximation methods (mean-field, variational, perturbative), methods for disordered systems (replica, cavity, restricted annealing), application of statistical mechanics to physical and biological systems, to information processing, optimization, and to models of risk for economic, financial, and general process-networks.
Prerequisites
Good knowledge of multivariate calculus, linear algebra and probability concepts.
Assessment details
2 hr written examination.
Educational aims & objectives
Aims
The course aims to give an introduction to the concepts and tools of statistical mechanics of complex and disordered systems. It will be explained how to use these tools and concepts to investigate complex biological, physical, economic and financial systems.
Teaching pattern
Two hours of lectures and one hour of tutorial per week throughout the term
Suggested reading list
Indicative reading list - link to Leganto system where you can search with module code for lists