Novel quantum phases on graphs using abelian gauge theory

TL;DR

This paper constructs and analyzes quantum models on graphs using abelian gauge theory, revealing diverse topological phases, entanglement properties, and anyon excitations, expanding understanding of quantum topological matter beyond traditional systems.

Contribution

It introduces new frustration-free, gapped Hamiltonians on graphs with variable ground state degeneracies and detailed entanglement and excitation analyses, advancing topological quantum phase research.

Findings

Ground state degeneracy can be topological, extensive, or mixed.

Entanglement entropy varies with basis, showing topological entanglement entropy in one case.

Identifies anyon-like excitations responsible for topological entanglement entropy.

Abstract

Graphs are topological spaces that include broader objects than discretized manifolds, making them interesting playgrounds for the study of quantum phases not realized by symmetry breaking. In particular they are known to support anyons of an even richer variety than the two-dimensional space. We explore this possibility by building a class of frustration-free and gapped Hamiltonians based on discrete abelian gauge groups. The resulting models have a ground state degeneracy that can be either a topological invariant, an extensive quantity or a mixture of the two. For two basis of the degenerate ground states which are complementary in quantum theory, the entanglement entropy is exactly computed. The result for one basis has a constant global term, known as the topological entanglement entropy, implying long-range entanglement. On the other hand, the topological entanglement entropy vanishes in the result for the other basis. Comparisons are made with similar occurrences in the toric code. We analyze excitations and identify anyon-like excitations that account for the topological entanglement entropy. An analogy between the ground states of this system and the $\theta$-vacuum for a $U(1)$ gauge theory on a circle is also drawn.