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arXiv · 2106.08911

Physics in non-fixed spatial dimensions via random networks

Abstract

We study the quantum statistical electronic properties of random networks which inherently lack a fixed spatial dimension. We use tools like the density of states (DOS) and the inverse participation ratio(IPR) to uncover various phenomena, such as unconventional properties of the energy spectrum and persistent localized states(PLS) at various energies, corresponding to quantum phases with with zero-dimensional(0D) and one-dimensional(1D) order. For small ratio of edges over vertices in the network $RT$ we find properties resembling graphene/honeycomb lattices, like a similar DOS containing a linear dispersion relation at the band center at energy E=0. In addition we find PLS at various energies including E=-1,0,1 and others, for example related to the golden ratio. At E=0 the PLS lie at disconnected vertices, due to partial bipartite symmetries of the random networks (0D order). At E=-1,1 the PLS lie mostly at pairs of vertices(bonds), while the rest of the PLS at other energies, like the ones related to the golden ratio, lie at lines of vertices of fixed length(1D order), at the spatial boundary of the network, resembling the edge states in confined graphene systems with zig-zag edges. As the ratio $RT$ is increased the DOS of the network approaches the Wigner semi-circle, corresponding to random symmetric matrices(Hamiltonians) and the PLS are reduced and gradually disappear as the connectivity in the network increases. Finally we calculate the spatial dimension $D$ of the network and its fluctuations, obtaining both integer and non-integer values and examine its relation to the electronic properties derived. Our results imply that universal physics can manifest in physical systems irrespectively of their spatial dimension. Relations to emergent spacetime in quantum and emergent gravity approaches are also discussed.

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BibTeXRIS

Ioannis Kleftogiannis, Ilias Amanatidis. 2022-03-11. Physics in non-fixed spatial dimensions via random networks. https://doi.org/10.1103/physreve.105.024141

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