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This research investigates how graph geometry influences entanglement growth and transport in quantum many-body systems, revealing a robust localization regime between nearest-neighbor and all-to-all connectivity models. By modeling Anderson localization through structural disorder, the study offers critical insights for designing tunable-range analog quantum simulators and understanding dynamics in amorphous materials. The findings advance fundamental knowledge of quantum network architectures where interaction range is a key design parameter.
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Entanglement Entropy in Quantum Networks with Tunable Geometry

arXiv2 min read

arXiv:2607.16394v1 Announce Type: new Abstract: Quantum many-body Hamiltonians with two-body interactions can be represented by graphs, with sites as nodes and two-site couplings as edges. We investigate how the geometry of these graphs affects transport and entanglement growth. To do so, we study dynamics for quantum hopping on a random graph model with an effective range parameter. Tuning it, we interpolate between nearest-neighbor and all-to-all graphs, identifying a new localization regime that is robust in both single-particle and finite-density cases. This provides a model of Anderson localization induced by structural disorder, with implications for amorphous materials and tunable-range analog quantum simulators.

Abstract:Quantum many-body Hamiltonians with two-body interactions can be represented by graphs, with sites as nodes and two-site couplings as edges. We investigate how the geometry of these graphs affects transport and entanglement growth. To do so, we study dynamics for quantum hopping on a random graph model with an effective range parameter. Tuning it, we interpolate between nearest-neighbor and all-to-all graphs, identifying a new localization regime that is robust in both single-particle and finite-density cases. This provides a model of Anderson localization induced by structural disorder, with implications for amorphous materials and tunable-range analog quantum simulators.

arXiv:2607.16394 [quant-ph]

(or arXiv:2607.16394v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2607.16394 Focus to learn more arXiv-issued DOI via DataCite

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Full text under the publisher's open licence · 185 words

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