  In the out-of-equilibrium evolution induced by a quench, fast degrees of
freedom generate long-range entanglement that is hard to encode with standard
tensor networks. However, local observables only sense such long-range
correlations through their contribution to the reduced local state as a
mixture. We present a tensor network method that identifies such long-range
entanglement and efficiently transforms it into mixture, much easier to
represent. In this way, we obtain an effective description of the time-evolved
state as a density matrix that captures the long-time behavior of local
operators with finite computational resources.
