English

Statistical mechanics model for Clifford random tensor networks and monitored quantum circuits

Statistical Mechanics 2025-04-18 v2 Disordered Systems and Neural Networks Strongly Correlated Electrons Quantum Physics

Abstract

We introduce an exact mapping of Clifford (stabilizer) random tensor networks (RTNs) and monitored quantum circuits, onto a statistical mechanics model. With Haar unitaries, the fundamental degrees of freedom ('spins') are permutations because all operators commuting with the action of the unitaries on a tensor product arise from permutations of the tensor factors ('Schur-Weyl duality'). For unitaries restricted to the smaller Clifford group, the set of commuting operators, the 'commutant', forming the new 'spin' degrees of freedom, will be larger. We use the recent full characterization of this commutant by Gross et al., Comm. Math. Phys. 385, 1325 (2021), to construct the Clifford statistical mechanics models for on-site Hilbert space dimensions which are powers of a prime number pp. We show that the Boltzmann weights are invariant under a symmetry group involving orthogonal matrices with entries in the finite number field Fp{\bf F}_p. This implies that the symmetry group, and consequently all universal properties of entanglement transitions in Clifford circuits and RTNs will in general depend on, and only on the prime pp. We show that Clifford monitored circuits with on-site Hilbert space dimension d=pMd=p^M are described by percolation in the limits dd \to \infty at (a) p=p= fixed but MM\to \infty, and at (b) M=1M= 1 but pp \to \infty. In the limit (a) we calculate the effective central charge, and in the limit (b) we derive the following universal minimal cut entanglement entropy SA=(3/π)lnplnLAS_A =(\sqrt{3}/\pi)\ln p \ln L_A for d=pd=p large at the transition. We verify those predictions numerically, and present extensive numerical results for critical exponents at the transition in monitored Clifford circuits for prime number on-site Hilbert space dimension d=pd=p for a variety of different values of pp, and find that they approach percolation values at large pp.

Keywords

Cite

@article{arxiv.2110.02988,
  title  = {Statistical mechanics model for Clifford random tensor networks and monitored quantum circuits},
  author = {Yaodong Li and Romain Vasseur and Matthew P. A. Fisher and Andreas W. W. Ludwig},
  journal= {arXiv preprint arXiv:2110.02988},
  year   = {2025}
}

Comments

23 pages, 5 figures. Abstract shortened to meet arxiv requirements, see pdf for full abstract. v2: Discussion on multifractality in Clifford circuits added. Published version

R2 v1 2026-06-24T06:40:54.734Z