: A local search algorithm operating on an instance of a Boolean constraint satisfaction problem (in particular, k-SAT) can be viewed as a stochastic process traversing successive adjacent states in an "energy landscape" defined by the problem instance on the n-dimensional Boolean hypercube. We investigate analytically the worst-case topography of such landscapes in the context of satisfiable k-SAT via a random ensemble of "k-regular" linear equations modulo 2. We show that for each fixed k = 3, 4, . . ., the typical k-SAT energy landscape induced by an instance drawn from the ensemble has a set of 2(n) local energy minima, each separated by an unconditional (n) energy barrier from each of the O(1) ground states, that is, solution states with zero energy. The main technical aspect of the analysis is that a random k-regular 0/1-matrix constitutes a strong boundary expander with almost full GF(2)-linear rank, a property which also enables us to prove an exponential lo...