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This research investigates how the topology of geometric complex networks influences quantum localization, demonstrating that network structure alone can mimic the effects of random disorder typically required to halt wave diffusion. The study identifies a critical transition where small-world connectivity promotes extended states across the system, whereas non-small-world regimes lead to localization without external potentials. These findings offer new insights into controlling quantum transport through graph design rather than energetic tuning.
Sources coveringarXiv, Quantum Computing Report, techtimes.com
What this isA model's reading of the article and related coverage, written for aiqbench. Not the publisher's words.

Quantum Localization in Geometric Complex Networks

arXiv2 min read

arXiv:2610.15874v1 Announce Type: cross Abstract: Quantum localization, the phenomenon by which wave diffusion is halted, here understood as the superposition of propagating waves, can have many different origins, such as onsite random potentials in Anderson localization. However, some systems exhibit complex geometries and could potentially reproduce similar results without external potentials. In this work, we study how localization of single particle states is affected by the underlying topology of a simple but highly predictive complex network model: the geometric soft configuration model $\mathbb S^1$. By tuning the model's temperature and heterogeneity parameters, we are able to generate different structural patterns and focus on the transition from a small-world to a non-small-world regime. Our study suggests that small-world networks tend to have extended states, which spread the whole system's size, in contrast to non-small-world networks which tend to localize, showing how complex connectivity can play the role assigned to random energetic disorder.

Abstract:Quantum localization, the phenomenon by which wave diffusion is halted, here understood as the superposition of propagating waves, can have many different origins, such as onsite random potentials in Anderson localization. However, some systems exhibit complex geometries and could potentially reproduce similar results without external potentials. In this work, we study how localization of single particle states is affected by the underlying topology of a simple but highly predictive complex network model: the geometric soft configuration model $\mathbb S^1$. By tuning the model's temperature and heterogeneity parameters, we are able to generate different structural patterns and focus on the transition from a small-world to a non-small-world regime. Our study suggests that small-world networks tend to have extended states, which spread the whole system's size, in contrast to non-small-world networks which tend to localize, showing how complex connectivity can play the role assigned to random energetic disorder.

Disordered Systems and Neural Networks (cond-mat.dis-nn); Quantum Physics (quant-ph)

arXiv:2610.15874 [cond-mat.dis-nn]

(or arXiv:2610.15874v1 [cond-mat.dis-nn] for this version)

https://doi.org/10.48550/arXiv.2610.15874 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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Full text under the publisher's open licence · 246 words

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