Tensor networks model mixed states in topological quantum matter

Bader Aldossari of the Georgia Institute of Technology and colleagues have developed a new way to model intrinsically mixed-state topological phases, quantum matter exhibiting nontrivial topological phenomena even with inherent noise. The researchers constructed tensor network representations for these phases, which emerge in noisy, long-range entangled quantum systems and demonstrate the method’s applicability to scenarios like maeb decoherence in the ZN toric code. The team’s approach reveals a tensor network representation for a mixed-state chiral semion that has no equivalent in “clean”, pure-state quantum systems, suggesting the possibility of topological order unique to noisy environments. Together, these results establish tensor networks as a natural platform for analyzing noisy intrinsically mixed-state topological matter. Tensor networks now model topological phases arising from decoherence, a process where quantum information leaks from a system, in a way previously inaccessible to simulation. The framework allows for the construction of tensor network representations for a wide range of intrinsically mixed topological phases originating from strongly disordered or decohered pure-state…