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  • Letter

Disentangling the Kitaev quantum spin liquid using the Clifford circuits augmented matrix product states method

Xiang Li1,*, Xiangjian Qian1,2,*, and Mingpu Qin1,3,†

  • 1Key Laboratory of Artificial Structures and Quantum Control (Ministry of Education), School of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai 200240, China
  • 2Tsung-Dao Lee Institute, Shanghai Jiao Tong University, Shanghai 200240, China
  • 3Hefei National Laboratory, Hefei 230088, China

  • *These authors contributed equally to this work.
  • †Contact author: qinmingpu@sjtu.edu.cn

Phys. Rev. B 113, L201112 – Published 14 May, 2026

DOI: https://doi.org/10.1103/7tdt-kx4l

Abstract

In this work, we investigate the Kitaev honeycomb model employing the recently developed Clifford circuits augmented matrix product states (CAMPS) method. While the model in the gapped phase is known to reduce to the toric code model—whose ground state is entirely constructible from Clifford circuits—we demonstrate that the very different gapless quantum spin liquid (QSL) phase can also be significantly disentangled with Clifford circuits. Specifically, CAMPS simulations reveal that approximately two-thirds of the entanglement entropy in the isotropic point arises from Clifford-circuit contributions, enabling dramatically more efficient computations compared to conventional matrix product state (MPS) methods. Crucially, this finding implies that the Kitaev QSL state retains significant “Clifford-simulatable” structure, even in the gapless phase with non-Abelian anyon excitations when time reversal symmetry is broken. This property not only enhances classical simulation efficiency significantly but also suggests substantial resource reduction for preparing such states on quantum devices. As an application, we leverage CAMPS to study the Kitaev-Heisenberg model and determine the most accurate phase boundary between the antiferromagnetic phase and the Kitaev QSL phase in the model. Our results highlight how Clifford circuits can effectively disentangle the intricate entanglement of Kitaev QSLs, opening avenues for efficiently simulating related and similar strongly correlated models.

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