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Holography and criticality in matchgate tensor networks.

ABSTRACT: The AdS/CFT correspondence conjectures a holographic duality between gravity in a bulk space and a critical quantum field theory on its boundary. Tensor networks have come to provide toy models to understand these bulk-boundary correspondences, shedding light on connections between geometry and entanglement. We introduce a versatile and efficient framework for studying tensor networks, extending previous tools for Gaussian matchgate tensors in 1 + 1 dimensions. Using regular bulk tilings, we show that the critical Ising theory can be realized on the boundary of both flat and hyperbolic bulk lattices, obtaining highly accurate critical data. Within our framework, we also produce translation-invariant critical states by an efficiently contractible tensor network with the geometry of the multiscale entanglement renormalization ansatz. Furthermore, we establish a link between holographic quantum error-correcting codes and tensor networks. This work is expected to stimulate a more comprehensive study of tensor network models capturing bulk-boundary correspondences.

SUBMITTER: Jahn A

PROVIDER: S-EPMC6688869 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Holography and criticality in matchgate tensor networks.

Jahn A A Gluza M M Pastawski F F Eisert J J

Science advances 20190809 8

The AdS/CFT correspondence conjectures a holographic duality between gravity in a bulk space and a critical quantum field theory on its boundary. Tensor networks have come to provide toy models to understand these bulk-boundary correspondences, shedding light on connections between geometry and entanglement. We introduce a versatile and efficient framework for studying tensor networks, extending previous tools for Gaussian matchgate tensors in 1 + 1 dimensions. Using regular bulk tilings, we sho ...[more]

PMID: 31448328

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Dataset Information

Holography and criticality in matchgate tensor networks.

Publications

Holography and criticality in matchgate tensor networks.

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