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arXiv · 0901.0214

Plaquette Renormalization Scheme for Tensor Network States

Ling Wang·Ying-Jer Kao·Anders W. Sandvik
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Abstract

We present a method for contracting a square-lattice tensor network in two dimensions, based on auxiliary tensors accomplishing successive truncations (renormalization) of 8-index tensors for 2 by 2 plaquettes into 4-index tensors. The scheme is variational, and thus the tensors can be optimized by minimizing the energy. Test results for the quantum phase transition of the transverse-field Ising model confirm that even the smallest possible tensors (two values for each tensor index at each renormalization level) produce much better results than the simple product (mean-field) state.

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Ling Wang, Ying-Jer Kao, Anders W. Sandvik. 2011-05-07. Plaquette Renormalization Scheme for Tensor Network States. https://doi.org/10.1103/physreve.83.056703

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