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arxiv: 2605.29514 · v1 · pith:GEJM6HGUnew · submitted 2026-05-28 · 🪐 quant-ph

Non-Clifford Crosstalk Noise in Surface Codes Using Hybrid Stabilizer-Tensor Network Methods

Ben Harper , Azar C. Nakhl , Martin Sevior , Muhammad Usman This is my paper

Pith reviewed 2026-06-29 07:19 UTC · model grok-4.3

classification 🪐 quant-ph
keywords surface codescoherent crosstalkquantum error correctionlogical error ratesfault tolerance thresholdtensor network methodsstabilizer formalism
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The pith

Coherent crosstalk during syndrome extraction increases logical error rates in surface codes and lowers the threshold.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This paper develops hybrid stabilizer-tensor network methods to simulate coherent quantum crosstalk noise in surface code error correction. It demonstrates that coherent noise leads to higher logical error rates than incoherent models and reduces the threshold for fault tolerance. The distribution of the noise also affects the rates quantitatively. These findings indicate that simplified noise models can give overly optimistic predictions for real devices.

Core claim

Using hybrid stabilizer-tensor network simulation techniques, we simulate coherent quantum crosstalk noise during syndrome extraction on a surface code. We show that the inclusion of coherence increases logical error rates and lowers the code threshold. In addition, we show that the specific distribution of the noise can quantitatively change logical error rates. The methods allow simulation of quantum error correction with noise models previously inaccessible to classical simulation.

What carries the argument

Hybrid stabilizer-tensor network simulation techniques that capture the full dynamics of coherent quantum crosstalk noise during syndrome extraction.

If this is right

  • Incoherent noise models underestimate logical error rates when crosstalk is coherent.
  • Code thresholds calculated under incoherent assumptions are higher than those found with coherent noise.
  • The spatial distribution of crosstalk quantitatively changes logical error rates.
  • Hybrid methods enable analysis of noise models that standard classical simulations cannot handle.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Hardware designs may need to prioritize suppression of coherent phases in crosstalk to preserve code performance.
  • The simulation approach could be tested on other stabilizer codes such as color codes.
  • Existing threshold estimates in the literature may require downward revision once coherent crosstalk is included.

Load-bearing premise

The hybrid stabilizer-tensor network simulation techniques accurately capture the full dynamics of coherent quantum crosstalk noise during syndrome extraction on a surface code.

What would settle it

An exact simulation on a small surface code patch with coherent crosstalk that shows different logical error rates than the hybrid method predicts.

Figures

Figures reproduced from arXiv: 2605.29514 by Azar C. Nakhl, Ben Harper, Martin Sevior, Muhammad Usman.

Figure 1
Figure 1. Figure 1: FIG. 1. (a) A distance 5 rotated surface code. Data qubits ( [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: FIG. 2. Schmidt values squared for a surface code simula [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: FIG. 3. The logical error rate plotted for various levels of [PITH_FULL_IMAGE:figures/full_fig_p004_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: FIG. 4. Logical error rates for the surface code under the baseline Pauli noise model with no crosstalk compared with (a) [PITH_FULL_IMAGE:figures/full_fig_p006_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: FIG. 5. Logical error rates for the surface code where the sign [PITH_FULL_IMAGE:figures/full_fig_p006_5.png] view at source ↗
read the original abstract

Scalable realisation of quantum computing is reliant on the development of fault tolerant devices. Analysis of quantum error correction protocols typically considers incoherent noise models or noise-free syndrome measurements. While this is simple to simulate classically and straightforward to compute analytically, these simplifications are unable to capture the full dynamics of a noisy quantum system. In this work we use advanced hybrid stabilizer-tensor network simulation techniques to simulate coherent quantum crosstalk noise during syndrome extraction on a surface code. We show that the inclusion of coherence increases logical error rates and lowers the code threshold. In addition, we show that the specific distribution of the noise can quantitatively change logical error rates. The methods in this work allow simulation of quantum error correction with noise models previously inaccessible to classical simulation, providing new insights on the effect of crosstalk noise on quantum error correction codes.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

1 major / 1 minor

Summary. The manuscript introduces hybrid stabilizer-tensor network methods to simulate coherent, non-Clifford crosstalk noise during syndrome extraction on surface codes. It claims that including coherence increases logical error rates and lowers the code threshold relative to incoherent models, and that the spatial distribution of the noise quantitatively alters these rates. The approach is presented as enabling simulation of previously inaccessible noise models.

Significance. If the simulations are shown to be faithful, the results would be significant for fault-tolerant quantum computing by demonstrating that coherent crosstalk effects cannot be safely approximated as incoherent and that noise distribution matters. This challenges common modeling assumptions and provides concrete guidance on threshold degradation.

major comments (1)
  1. [Methods section on hybrid stabilizer-tensor network simulation] Methods section on hybrid stabilizer-tensor network simulation: the central claim that coherence increases logical error rates and lowers thresholds rests on the method accurately capturing non-unitary coherent dynamics without truncation artifacts. The manuscript should include explicit validation, such as bond-dimension convergence tests or comparisons against exact methods on small lattices, to confirm that reported error rates and thresholds are not affected by approximation choices.
minor comments (1)
  1. [Results figures and tables] Figure captions and results tables should explicitly state the surface-code distances, number of syndrome rounds, and noise strengths used, to allow direct comparison with prior threshold studies.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their careful review and constructive feedback on our manuscript. We appreciate the recognition of the potential significance of our results for fault-tolerant quantum computing. Below, we provide a point-by-point response to the major comment and outline the revisions we will make.

read point-by-point responses

  1. Referee: Methods section on hybrid stabilizer-tensor network simulation: the central claim that coherence increases logical error rates and lowers thresholds rests on the method accurately capturing non-unitary coherent dynamics without truncation artifacts. The manuscript should include explicit validation, such as bond-dimension convergence tests or comparisons against exact methods on small lattices, to confirm that reported error rates and thresholds are not affected by approximation choices.

    Authors: We concur that validating the hybrid stabilizer-tensor network method against truncation effects is essential to substantiate our findings on the impact of coherent crosstalk noise. Although the manuscript employs established techniques from tensor network simulations, we acknowledge that explicit checks were not detailed. In the revised version, we will add sections presenting bond-dimension convergence tests for representative noise parameters and comparisons to exact methods on small lattices (e.g., distance-3 surface codes) to demonstrate that the logical error rates and thresholds are converged and not artifacts of the approximation. revision: yes

Circularity Check

0 steps flagged

No significant circularity detected

full rationale

The paper's central results are obtained directly from hybrid stabilizer-tensor network simulations of coherent crosstalk noise on surface codes. These simulations produce the reported increases in logical error rates and threshold reductions as numerical outputs, without any load-bearing derivation that reduces a claimed prediction to a fitted parameter, self-definition, or self-citation chain. The abstract and described method treat the simulation technique as an independent computational tool whose validity rests on its ability to capture non-unitary dynamics, not on internal redefinition of its own outputs. No equations or steps in the provided material exhibit the enumerated circularity patterns.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

Abstract-only review provides minimal detail on parameters or assumptions; no free parameters, invented entities, or non-standard axioms are explicitly stated.

axioms (1)
  • domain assumption Hybrid stabilizer-tensor network methods can simulate coherent crosstalk noise in surface-code syndrome extraction.
    Core methodological premise stated in the abstract.

pith-pipeline@v0.9.1-grok · 5673 in / 1042 out tokens · 27998 ms · 2026-06-29T07:19:31.005266+00:00 · methodology

discussion (0)

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Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. QMCtwin: Master-Equation Simulation of Syndrome Statistics Beyond Pauli Noise

    quant-ph 2026-06 unverdicted novelty 7.0

    QMCtwin simulates master-equation syndrome statistics for a distance-7 surface code and reveals biases and correlations absent in Pauli-twirled models.

Reference graph

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