Symmetries in topological tensor network states: classification, construction and detection
Jos\'e Garre-Rubio

TL;DR
This thesis advances the understanding of symmetry-enriched topological phases using tensor network states, specifically PEPS, by classifying, constructing, and detecting various phases and their symmetry properties in 2D models.
Contribution
It provides a classification scheme for symmetry-enriched topological phases in PEPS, introduces physical maps for group extension theory, and proposes methods to detect quantum phases and symmetry fractionalization.
Findings
Classified symmetry-enriched topological phases via group extension theory
Constructed representative states for each phase class
Proposed gauge-invariant order parameters for phase detection
Abstract
This thesis contributes to the understanding of symmetry-enriched topological phases focusing on their descriptions in terms of tensor network states. The Projected Entangled Pair State (PEPS) formalism allows us to locally encode the main properties of the models (like topological order, symmetries and their interplay) in the tensors. We have used that encoding to classify, construct and detect some classes of symmetry-enriched topological phases in 2D PEPS. For that purpose, we have studied what the allowed freedom in the tensors generating the same tensor network state is. These results are the so-called 'fundamental theorems' and they give the necessary knowledge to properly study symmetries (actions that leave the states invariant). We focus our study on the family of PEPS describing quantum double models of , the so-called -injective PEPS, and on global on-site symmetries…
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Taxonomy
TopicsScientific Research and Discoveries
