Abstract
Due to the unfavorable scaling of tensor network methods with the refinement parameter M, new approaches are necessary to improve the efficiency of numerical simulations based on such states in particular for gapless, strongly entangled systems. In one-dimensional DMRG, the use of Abelian symmetries has lead to large computational gain. In higher-dimensional tensor networks, this is associated with significant technical efforts and additional approximations. We explain a formalism to implement such symmetries in two-dimensional tensor network states and present benchmark results that confirm the validity of these approximations in the context of projected entangled-pair state algorithms.
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