Breaking the Entanglement-Structure Trade-off: Many-Body Localization Protects Emergent Holographic Geometry in Random Tensor Networks
Zhihua Liang

TL;DR
This paper demonstrates that many-body localization (MBL) can protect emergent holographic geometry in random tensor networks, preventing thermalization and preserving entanglement structure.
Contribution
It reveals MBL as a mechanism that sustains holographic geometry and entanglement structure in tensor networks, contrasting with thermal phases and classical automata.
Findings
MBL prevents thermalization of holographic geometry in tensor networks.
Optimal MBL regime with specific disorder and anisotropy parameters maintains high mutual information.
MBL preserves the spatial structure of entanglement rather than just its total amount.
Abstract
We present a systematic numerical investigation of the "entanglement geometry gravity" chain in random tensor networks (RTN) established by the ER EPR conjecture and Jacobson's thermodynamic derivation. First, we verify the kinematic foundation: the entanglement first law (slope=1.000), the encoding of geometry by mutual information (correlation=0.92), and the locality of holographic perturbations (3.3x). We also confirm that gravitational dynamics (JT gravity) does not emerge, identifying a sharp kinematics-dynamics boundary. Second, and more importantly, we discover that many-body localization (MBL) is the mechanism that protects emergent holographic geometry from thermalization. Replacing Haar-random evolution (geometry lifetime ) with an XXZ Hamiltonian plus on-site disorder, we observe a finite-size crossover at disorder strength…
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