Tensor Network Representations for Intrinsically Mixed-State Topological Orders
Abstract
Tensor networks are an efficient platform to represent interesting quantum states of matter as well as to compute physical observables and information-theoretic quantities. We present a general protocol to construct fixed-point tensor network representations for intrinsically mixed-state topological phases, which exhibit nontrivial topological phenomena and do not have pure-state counterparts. The method exploits the power of anyon condensation in Choi states and is applicable to the cases where the target states arise from pure-state topological phases subject to strong decoherence/disorders in the Abelian sectors. Representative examples include decoherence of toric code, decohered non-Abelian quantum double as well as pure / decoherence of arbitrary CSS codes. An example of chiral topological phases which cannot arise from local commuting projector models are also presented.
Cite
@article{arxiv.2507.22989,
title = {Tensor Network Representations for Intrinsically Mixed-State Topological Orders},
author = {Bader Aldossari and Sergey Blinov and Zhu-Xi Luo},
journal= {arXiv preprint arXiv:2507.22989},
year = {2025}
}
Comments
15 pages, 10 figures