2025/12/04 by Ulysse Marquis, Marquis, Ulysse · 1 voice
Computer Science · Physics and Astronomy · #Complex Network Analysis Techniques #Theoretical and Computational Physics #Topological and Geometric Data Analysis #cond-mat.dis-nn #cond-mat.stat-mech #math.PR
paper · pdf · doi:10.48550/arxiv.2512.04682
openalex publication_date 2025/12/04 · openalex created_date 2025/12/06 · openalex updated_date 2026/07/28
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.