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Based on a non-rigorous formalism called the “cavity method”, physicists have made intriguing predictions on phase transitions in discrete structures. One of the most remarkable ones is that in problems such as random k-SAT or random graph k-coloring, very shortly before the threshold for the existence of solutions there occurs another phase transition called condensation [Krzakala et al., PNAS 2007]. The existence of this phase transition seems to be intimately related to the difficulty of proving precise results on, e. g., the k-colorability threshold as well as to the performance of message passing algorithms. In random graph k-coloring, there is a precise conjecture as to the location of the condensation phase transition in terms of a distributional fixed point problem. In this paper we prove this conjecture, provided that k exceeds a certain constant k0.
Random constraint satisfaction problems have been on the agenda of various sciences such as discrete mathematics, computer science, statistical physics and a whole series of additional areas of application since the 1990s at least. The objective is to find a state of a system, for instance an assignment of a set of variables, satisfying a bunch of constraints. To understand the computational hardness as well as the underlying random discrete structures of these problems analytically and to develop efficient algorithms that find optimal solutions has triggered a huge amount of work on random constraint satisfaction problems up to this day. Referring to this context in this thesis we present three results for two random constraint satisfaction problems. ...