2007

Algorithms for entanglement renormalization

Evenbly, G., Vidal, G.

Understand

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.

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