Diffusive geodesics wandering in networks of rigid chains

We introduce an ensemble of spatial networks built from the junctions of hindered-rotation chains, incorporating directional correlations between bonds, an aspect ignored in the standard network modeling paradigm. The emergent random networks support geodesics with a wandering exponent ξ=1/2, and a travel-time fluctuation exponent χ=0, consistent with the KPZ relation, yet violating the bound χ≥1/8 predicted in the Poissonian framework. Transverse deviations follow the Kolmogorov distribution, indicating similarities between Brownian bridge excursions and geodesics in a random medium with correlated edges orientations. These results reveal a new universality class of Euclidean first-passage percolation, where local orientational memory reshapes transport properties and challenges existing bounds for random spatial networks.

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Publication Details

Journal
Physical review. E
Published
2025-12-03
DOI
https://doi.org/10.1103/d6y6-j48y
Primary Topic
Complex Network Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Diffusive geodesics wandering in networks of rigid chains

Karl J. Friston
Physical review. E
Complex Network Analysis Techniques
article

Diffusive geodesics wandering in networks of rigid chains

Karl J. Friston
article en

Abstract

We introduce an ensemble of spatial networks built from the junctions of hindered-rotation chains, incorporating directional correlations between bonds, an aspect ignored in the standard network modeling paradigm. The emergent random networks support geodesics with a wandering exponent ξ=1/2, and a travel-time fluctuation exponent χ=0, consistent with the KPZ relation, yet violating the bound χ≥1/8 predicted in the Poissonian framework. Transverse deviations follow the Kolmogorov distribution, indicating similarities between Brownian bridge excursions and geodesics in a random medium with correlated edges orientations. These results reveal a new universality class of Euclidean first-passage percolation, where local orientational memory reshapes transport properties and challenges existing bounds for random spatial networks.

Physical review. EVol. 112(6)
University of Trento (IT), Fondazione Bruno Kessler (IT)
Openalex Percentile: Top 68%
Complex Network Analysis Techniques
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