Tensor network states and algorithms in the presence of a global SU(2) symmetry
Sukhwinder Singh, Guifre Vidal

TL;DR
This paper develops tensor network algorithms that explicitly incorporate SU(2) symmetry, enabling more efficient simulations of quantum systems with spin conservation by leveraging symmetry properties.
Contribution
It provides a detailed implementation of non-Abelian SU(2) symmetry in tensor networks, extending previous work on Abelian symmetries and demonstrating practical applications.
Findings
Efficient SU(2)-invariant tensor network algorithms developed.
Application to quantum spin chains reveals low energy spectra.
Framework can be extended to other exotic symmetries.
Abstract
The benefits of exploiting the presence of symmetries in tensor network algorithms have been extensively demonstrated in the context of matrix product states (MPSs). These include the ability to select a specific symmetry sector (e.g. with a given particle number or spin), to ensure the exact preservation of total charge, and to significantly reduce computational costs. Compared to the case of a generic tensor network, the practical implementation of symmetries in the MPS is simplified by the fact that tensors only have three indices (they are trivalent, just as the Clebsch-Gordan coefficients of the symmetry group) and are organized as a one-dimensional array of tensors, without closed loops. Instead, a more complex tensor network, one where tensors have a larger number of indices and/or a more elaborate network structure, requires a more general treatment. In two recent papers, namely…
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