We propose a tensor network method for investigating strongly disordered systems that is based on an adaptation of entanglement renormalization [G. Vidal, Phys. Rev. Lett. 99, 220405 (2007)]. This method makes use of the strong disorder renormalization group to determine the order in which lattice sites are coarse-grained, which sets the overall structure of the corresponding tensor network ansatz, before optimization using variational energy minimization. Benchmark results from the disordered $XXZ$ model demonstrates that this approach accurately captures ground-state entanglement in disordered systems, even at long distances. This approach leads to a new class of efficiently contractible tensor network ansatz for one-dimensional systems, which may be understood as a generalization of the multiscale entanglement renormalization ansatz for disordered systems.

• Received 24 August 2017

DOI:https://doi.org/10.1103/PhysRevB.96.155136