Multi-fractal Geometry of Finite Networks of Spins
Paul Bogdan, Edmond Jonckheere, Sophie Schirmer

TL;DR
This paper introduces a geometric, fractal-based approach to analyze finite quantum spin networks, revealing complex self-similar structures and phase transition phenomena in information propagation.
Contribution
It develops a novel multi-fractal analysis method for finite spin networks and links their complex geometry to phase transition behavior in information transfer.
Findings
Quantum spin networks exhibit multi-fractal self-similar structures.
Finite spin chains show an informational phase transition similar to metal-insulator transitions.
The proposed framework quantifies complexity and criticality in spin network dynamics.
Abstract
Quantum spin networks overcome the challenges of traditional charge-based electronics by encoding the information into spin degrees of freedom. Although beneficial for transmitting information with minimal losses when compared to their charge-based counterparts, the mathematical formalization of the information propagation in a spin(tronic) network is challenging due to its complicated scaling properties. In this paper, we propose a geometric approach---specific to finite networks---for unraveling the information-theoretic phenomena of spin chains and rings by abstracting them as weighted graphs, where the vertices correspond to the spin excitation states and the edges represent the information theoretic distance between pair of nodes. The weighted graph representation of the quantum spin network dynamics exhibits a complex self-similar structure (where subgraphs repeat to some extent…
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