English

Nishimori Threshold Estimation for Bayesian Inference and $\mathbb{Z}_q$ Surface Code Decoding

Quantum Physics 2026-07-20 v1 Disordered Systems and Neural Networks Statistical Mechanics

Abstract

In quantum error correction, the error threshold provides essential quantitative guidance for the ability to bring about fault-tolerance through decoding the effects of incoherent noise, weak measurement or inference. However, the numerical value of an error threshold is typically only accessible through large-scale numerical simulations of the underlying noise model. Here we introduce an analytical estimate of error thresholds falling into the Nishimori universality class via a Fourier--Walsh projection scheme that maps the critical point of the underlying disorder-free statistical-mechanics model to the Born-disordered Nishimori critical point. Using a minimal replica theory approach, this closed-form estimate is obtained from a projection of the exact replicated single-bond weight which we find to reproduce (within a percentage point) the known numerical thresholds of random-bond and random-plaquette Ising models / Z2\mathbb Z_2 stabilizer codes in spatial dimensions d=25d=2-5, and extends to Potts variables with q4q\le4. The main application of our projection scheme is to Zq\mathbb Z_q surface codes, whose decoding problem maps to the disordered qq-state clock model. For q5q\ge5 the clean clock model has \textit{two} Berezinskii--Kosterlitz--Thouless transitions, which the projection maps to two Nishimori temperatures that bound an intermediate information-critical phase. The resulting threshold values not only accurately agree with recent decohered-Zq\mathbb Z_q-toric-code numerics, but are found to satisfy the Gilbert--Varshamov self-dual entropy relation lnqHq(T1)+Hq(T2),\ln q \simeq H_q(T_1^\ast)+H_q(T_2^\ast), although no duality condition is imposed in the construction. Our approach thereby points to a deeper connection between the clean and Born-disordered models, while allowing for instant analytical estimates of error thresholds for a variety of stabilizer codes.

Cite

@article{arxiv.2607.18374,
  title  = {Nishimori Threshold Estimation for Bayesian Inference and $\mathbb{Z}_q$ Surface Code Decoding},
  author = {Rohit Mukherjee and Simon Trebst},
  journal= {arXiv preprint arXiv:2607.18374},
  year   = {2026}
}

Comments

22 pages, 5 figures