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Journal Article
Conformal properties of hyperinvariant tensor networks
2022
Overview
Hyperinvariant tensor networks (hyMERA) were introduced as a way to combine the successes of
perfect tensor networks
(HaPPY) and the
multiscale entanglement renormalization ansatz
(MERA) in simulations of the AdS/CFT correspondence. Although this new class of tensor network shows much potential for simulating conformal field theories arising from hyperbolic bulk manifolds with quasiperiodic boundaries, many issues are unresolved. In this manuscript we analyze the challenges related to optimizing tensors in a hyMERA with respect to some quasiperiodic critical spin chain, and compare with standard approaches in MERA. Additionally, we show two new sets of tensor decompositions which exhibit different properties from the original construction, implying that the multitensor constraints are neither unique, nor difficult to find, and that a generalization of the analytical tensor forms used up until now may exist. Lastly, we perform randomized trials using a descending superoperator with several of the investigated tensor decompositions, and find that the constraints imposed on the spectra of local descending superoperators in hyMERA are compatible with the operator spectra of several minimial model CFTs.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
