Sep 6, 3:30pm, Wean 8220
Amin Coja-Oghlan, Goethe University
(Frankfurt/Main)
Catching the k-NAESAT threshold
Abstract:
The best current estimates of the thresholds for the existence of solutions
in random constraint satisfaction problems mostly derive from the first and
the second moment method. Yet apart from a very few exceptional cases these
methods do not quite yield matching upper and lower bounds. Here we present
an enhanced second moment argument that allows us to narrow the gap to an
additive 2^{-(1-o_k(1))k} in the random k-NAESAT problem, one of the
standard benchmarks in random CSPs. Based on joint work with Konstantinos
Panagiotou and Lenka Zdeborova.