Statistical Physics Approaches to Static and Dynamical Properties

Suggestions for further readings:

Lecture 1: Typical and Rare Properties of Random Graphs

Lecture 2: Dynamical Processes on Random Graphs

Lecture 3: Storage of spatial maps in Hopfield-like models. For details about the statistical mechanics derivation of the phase diagram of the model, see this paper.

Solutions to exercises here

- B. Bollobas, Random Graphs, Cambridge University Press (2001)
- N.C. Wormald, The differential equation method for random graph processes and greedy algorithms, in Lectures on Approximation and Randomized Algorithms (M. Karonski and H.J. Proemel, eds), pp. 73-155. PWN, Warsaw (1999)
- D.J. Amit, Modeling Brain Function: The World of Attractor Neural Networks, Cambridge University Press (1992)
- for more on statistical mechanics and random Boolean systems, see R. Monasson, Introduction to Phase Transitions in Random Optimization Problems, Lecture Notes of Les Houches Summer School, Elsevier (2006) and references therein.