Random Tensor Networks with Non-trivial Links

Author:

Cheng Newton,Lancien Cécilia,Penington Geoff,Walter Michael,Witteveen FreekORCID

Abstract

AbstractRandom tensor networks are a powerful toy model for understanding the entanglement structure of holographic quantum gravity. However, unlike holographic quantum gravity, their entanglement spectra are flat. It has therefore been argued that a better model consists of random tensor networks with link states that are not maximally entangled, i.e., have non-trivial spectra. In this work, we initiate a systematic study of the entanglement properties of these networks. We employ tools from free probability, random matrix theory, and one-shot quantum information theory to study random tensor networks with bounded and unbounded variation in link spectra, and in cases where a subsystem has one or multiple minimal cuts. If the link states have bounded spectral variation, the limiting entanglement spectrum of a subsystem with two minimal cuts can be expressed as a free product of the entanglement spectra of each cut, along with a Marchenko–Pastur distribution. For a class of states with unbounded spectral variation, analogous to semiclassical states in quantum gravity, we relate the limiting entanglement spectrum of a subsystem with two minimal cuts to the distribution of the minimal entanglement across the two cuts. In doing so, we draw connections to previous work on split transfer protocols, entanglement negativity in random tensor networks, and Euclidean path integrals in quantum gravity.

Funder

Royal Library, Copenhagen University Library

Publisher

Springer Science and Business Media LLC

Subject

Mathematical Physics,Nuclear and High Energy Physics,Statistical and Nonlinear Physics

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Holographic properties of superposed quantum geometries;Physical Review D;2024-08-23

2. One-shot holography;SciPost Physics;2024-06-04

3. Entanglement of purification in random tensor networks;Physical Review D;2024-05-06

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