Computational Complexity of Isometric Tensor-Network States

We determine the computational power of isometric tensor-network states (isoTNSs), a variational ansatz originally developed to numerically find and compute properties of gapped ground states and topological states in two dimensions. By mapping two-dimensional isoTNSs to (1+1)D unitary quantum circu...

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Bibliographic Details
Main Authors: Daniel Malz, Rahul Trivedi
Format: Article
Language:English
Published: American Physical Society 2025-04-01
Series:PRX Quantum
Online Access:http://doi.org/10.1103/PRXQuantum.6.020310
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