  In this letter, we show how the Survey Propagation algorithm can be
generalized to include external forcing messages, and used to address
selectively an exponential number of glassy ground states. These capabilities
can be used to explore efficiently the space of solutions of random NP-complete
constraint satisfaction problems, providing a direct experimental evidence of
replica symmetry breaking in large-size instances. Finally, a new lossy data
compression protocol is introduced, exploiting as a computational resource the
clustered nature of the space of addressable states.
