Quick Navigation

Topics

Quantum Networks

Entanglement Entropy in Quantum Networks with Tunable Geometry

arXiv
Authors: Andrea Azzali, Sridevi Kuriyattil, Andrew J. Daley, Marilù Chiofalo

Year

2026

Paper ID

73500

Status

Preprint

Abstract Read

~2 min

Abstract Words

96

Citations

N/A

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.

Why This Paper Matters

  • This paper contributes to the Quantum Networks research area in the Quantum Articles archive.
  • It adds a 2026 reference point for readers tracking recent quantum research.
  • Quantum many-body Hamiltonians with two-body interactions can be represented by graphs, with sites as nodes and two-site couplings as edges.

Paper Tools

Become a member to use research tools

Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.

Show Paper arXiv Publisher Share Cite This Paper Copy URL Compare Copy DOI Add to Reading List Category Correction Request

References & Citation Signals

Local Citation Graph (Related-Paper Links)

Current Paper #73500 #78842 Latent Symmetry in Quantum Zeno... #78829 Graphene double quantum dot as ... #78826 Percolation of Data Constraints... #78820 System-Design Optimization of a...

External citation index: OpenAlex citation signal

Community Reactions

Quick sentiment from readers on this paper.

Score: 0
Likes: 0 Dislikes: 0

Sign in to react to this paper.

Discussion & Reviews (Moderated)

Average Rating: 0.0 / 5 (0 ratings)

No written reviews yet.