  An algorithm is presented which computes a translationally invariant matrix
product state approximation of the ground state of an infinite 1D system; it
does this by embedding sites into an approximation of the infinite
``environment'' of the chain, allowing the sites to relax, and then merging
them with the environment in order to refine the approximation. By making use
of matrix product operators, our approach is able to directly model any
long-range interaction that can be systematically approximated by a series of
decaying exponentials. We apply our techniques to compute the ground state of
the Haldane-Shastry model and present results.
