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Statistical mechanical mapping and maximum-likelihood thresholds for the surface code under generic single-qubit coherent errors

Published 29 Oct 2024 in quant-ph, cond-mat.dis-nn, and cond-mat.stat-mech | (2410.22436v1)

Abstract: The surface code, one of the leading candidates for quantum error correction, is known to protect encoded quantum information against stochastic, i.e., incoherent errors. The protection against coherent errors, such as from unwanted gate rotations, is however understood only for special cases, such as rotations about the $X$ or $Z$ axes. Here we consider generic single-qubit coherent errors in the surface code, i.e., rotations by angle $\alpha$ about an axis that can be chosen arbitrarily. We develop a statistical mechanical mapping for such errors and perform entanglement analysis in transfer matrix space to numerically establish the existence of an error-correcting phase, which we chart in a subspace of rotation axes to estimate the corresponding maximum-likelihood thresholds $\alpha_\text{th}$. The classical statistical mechanics model we derive is a random-bond Ising model with complex couplings and four-spin interactions (i.e., a complex-coupled Ashkin-Teller model). The error correcting phase, $\alpha<\alpha_\text{th}$, where the logical error rate decreases exponentially with code distance, is shown to correspond in transfer matrix space to a gapped one-dimensional quantum Hamiltonian exhibiting spontaneous breaking of a $\mathbb{Z}2$ symmetry. Our numerical results rest on two key ingredients: (i) we show that the state evolution under the transfer matrix -- a non-unitary (1+1)-dimensional quantum circuit -- can be efficiently numerically simulated using matrix product states. Based on this approach, (ii) we also develop an algorithm to (approximately) sample syndromes based on their Born probability. The $\alpha\text{th}$ values we find show that the maximum likelihood thresholds for coherent errors are larger than those for the corresponding incoherent errors (from the Pauli twirl), and significantly exceed the values found using minimum weight perfect matching.

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