Topological dualities via tensor networks
C. Wille, J. Eisert, A. Altland

TL;DR
This paper introduces a tensor network-based unified framework to understand dualities between topologically ordered, fermionic, and classical systems, enabling precise lattice mappings and analysis of phase transitions and boundary phenomena.
Contribution
It proposes a novel tensor network approach that unifies dualities across different physical systems with lattice precision and facilitates the study of phase transitions and boundary modes.
Findings
Tensor network formalism effectively maps dual systems.
The approach captures phase transition behaviors.
It simplifies the fermion-boson mapping within 2D systems.
Abstract
The ground state of the toric code, that of the two-dimensional class D superconductor, and the partition sum of the two-dimensional Ising model are dual to each other. This duality is remarkable inasmuch as it connects systems commonly associated to different areas of physics -- that of long range entangled topological order, (topological) band insulators, and classical statistical mechanics, respectively. Connecting fermionic and bosonic systems, the duality construction is intrinsically non-local, a complication that has been addressed in a plethora of different approaches, including dimensional reduction to one dimension, conformal field theory methods, and operator algebra. In this work, we propose a unified approach to this duality, whose main protagonist is a tensor network (TN) assuming the role of an intermediate translator. Introducing a fourth node into the net of dualities…
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