  We describe an iterative method to optimize the multi-scale entanglement
renormalization ansatz (MERA) for the low-energy subspace of local Hamiltonians
on a D-dimensional lattice. For translation invariant systems the cost of this
optimization is logarithmic in the linear system size. Specialized algorithms
for the treatment of infinite systems are also described. Benchmark simulation
results are presented for a variety of 1D systems, namely Ising, Potts, XX and
Heisenberg models. The potential to compute expected values of local
observables, energy gaps and correlators is investigated.
