  Exact many-body quantum problems are known to be computationally hard due to
the exponential scaling of the numerical resources required. Since the advent
of the Density Matrix Renormalization Group, it became clear that a successful
strategy to work around this obstacle was to develop numerical methods based on
the well-known theoretical renormalization group. In recent years, it was
realized that quantum states engineered via numerical renormalization allow a
variational representation in terms of a tensor network picture. The discovery
provided a further boost to the effectiveness of these techniques, not only due
to the increased flexibility and manipulability, but also because tensor
network states embed a direct interface to the entanglement they carry, so that
one can directly address many-body quantum correlations within these
variational ansatz states. This lead to the application of several numerical
tools, originally developed in the field of quantum-information, to approach
condensed matter problems.
