Fun with replicas: tripartitions in tensor networks and gravity

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We analyse a simple correlation measure for tripartite pure states that we call G(A : B : C). The quantity is symmetric with respect to the subsystems A, B, C, invariant under local unitaries, and is bounded from above by log dA dB. For random tensor network states, we prove that G(A : B : C) is equal to the size of the minimal tripartition of the tensor network, i.e., the logarithmic bond dimension of the smallest cut that partitions the network into three components with A, B, and C. We argue that for holographic states with a fixed spatial geometry, G(A : B : C) is similarly computed by the minimal area tripartition. For general holographic states, G(A : B : C) is determined by the minimal area tripartition in a backreacted geometry, but a smoothed version is equal to the minimal tripartition in an unbackreacted geometry at leading order. We briefly discuss a natural family of quantities Gn(A : B : C) for integer n ≥ 2 that generalize G = G 2. In holography, the computation of Gn(A : B : C) for n > 2 spontaneously breaks part of a ℤ n × ℤ n replica symmetry. This prevents any naive application of the Lewkowycz-Maldacena trick in a hypothetical analytic continuation to n = 1.

OriginalsprogEngelsk
Artikelnummer8
TidsskriftJournal of High Energy Physics
Vol/bind2023
Udgave nummer5
Antal sider30
ISSN1126-6708
DOI
StatusUdgivet - 2023

Bibliografisk note

Funding Information:
G. Penington is supported by the UC Berkeley Physics Department, the Simons Foundation through the “It from Qubit” program, the Department of Energy via the GeoFlow consor- tium (QuantISED Award DE-SC0019380) and an early career award, and AFOSR award FA9550-22-1-0098. M. Walter acknowledges the European Research Council (ERC) through ERC Starting Grant 101040907-SYMOPTIC, the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy — EXC 2092 CASA — 390781972, the BMBF through project QuBRA, and NWO grant OCENW.KLEIN.267.

Publisher Copyright:
© 2023, The Author(s).

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