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XZZX surface code[14]

Alternative names: Wen plaquette model.

Description

Non-CSS variant of the rotated surface code whose generators are \(XZZX\) Pauli strings associated, clock-wise, to the vertices of each face of a two-dimensional lattice (with a qubit located at each vertex of the tessellation).

XZZX toric code often either refers to the construction on the two-dimensional torus or is an alternative name for the general construction. Twisted XZZX toric code refers to the construction on a torus with twisted (a.k.a. shifted) boundary conditions. The construction on surfaces with boundaries is often called the XZZX planar code. On a closed lattice, the Wen plaquette realization of the XZZX toric code has the same \(\mathbb{Z}_2\) topological order as the toric code, and translation by one lattice unit exchanges the \(e\) and \(m\) anyons [5; Appx. C].

Stabilizer generators for this code are shown in Fig. I.

Figure I: Stabilizer generators of a XZZX planar code with open boundaries. The generators are \(XZZX\) operators on the corners of squares in the bulk and \(XZ\) operators on the boundaries.

Protection

As a stabilizer code, \([[n=O(d^2), k=O(1), d]]\).

Decoding

MWPM decoder, which can be used for \(X\) and \(Z\) noise. For \(Y\) noise, a variant of the matching decoder could be used like it is used for the XY code in Ref. [6]. Decoding complexity scales as order \(O(n^3)\) because the code is non-CSS [7][6; Supplement].

Code Capacity Threshold

For large but finite \(X\)- or \(Z\)-biased noise, the code’s thresholds exceed the zero-rate hashing bound. The difference of the threshold from the hashing bound exceeds \(2.9\%\) at a \(Z\) or \(X\) bias of 300.\(50\%\) threshold for noise infinitely biased towards \(X\) or \(Y\) or \(Z\) errors using a maximum-likelihood decoder.Depolarizing noise: \(18.7(1)\%\) under tensor-network decoder [8] and \(17.5\%\) under AMBP4 [9].

Threshold

\(\approx 4.5\%\) using minimum-weight perfect matching decoder for depolarizing noise (bias \(\eta=0.5\)); \(\approx 10\%\) for infinite \(Z\) bias.\(4.15\%\) when \(98\%\) of depolarizing errors are converted into erasure errors with union-find decoder on a planar code, vs. \(0.937\%\) for pure depolarizing noise. The dominant source of noise in neutral atom arrays is spontaneous decay into detectable energy levels outside of the computational subspace. Since that decay occurs in a Rydberg level that is accessible from only one of the hyperfine states used for storage, the resulting channel is biased erasure [10].\(0.817\%\) and \(0.940\%\) with minimum-weight perfect matching and belief-matching decoder, respectively, for biased circuit-level noise [11].

Realizations

Superconducting circuits: Distance-five 25-qubit code implemented on a superconducting quantum processor by Google Quantum AI [12]. This code outperformed the average of several instances of the smaller distance-three nine-qubit \(XZZX\) variant of the surface-17 code realized on the same device, both in terms of logical error probability over 25 cycles and in terms of logical error per cycle. This increase in error-correcting capabilities while using more physical qubits supports the notion of an error threshold. Braiding of defects has been demonstrated for the distance-five code [13]. Leakage errors have been handled in a separate work in a distance-three code [14]. Google Quantum AI follow-up experiment realizing distance-5 and distance-7 codes with 100 rounds of correction using the Libra and transformer-based decoders. The logical error rate is suppressed by a factor of \(\approx 2\), demonstrating beyond-break-even error correction with a block quantum code [15]. Magic-state cultivation was demonstrated on a device by Google Quantum AI by code switching between a distance-three 6.6.6 color code and distance-five \(XZZX\) surface code and decoding with the Tesseract decoder [16]. Neutral atom arrays: Lukin group. Transversal CNOT gates performed on distance \(3\), \(5\), and \(7\) codes [17]. Below-threshold performance on distance \(3\) and \(5\) codes with multiple rounds of syndrome extraction and error correction [18].

Notes

A single \(X\) or \(Z\) error gives rise to two nearby defects, which can be viewed as endpoints of a string. That way, multiple \(Z\) errors can be decomposed into a combination of diagonal strings.Originally formulated as an example of \(\mathbb{Z}_2\) topological order in the Wen plaquette model [1].Popular summary of the Google Quantum AI above-threshold result in Quanta Magazine.

Cousins

  • Rotated surface code— The XZZX code is obtained from the rotated surface code by applying Hadamard gates on a subset of qubits such that \(XXXX\) and \(ZZZZ\) generators are both mapped to \(XZXZ\). Both rotated and XZZX codes offer improved performance over the original surface code for biased noise [19].
  • Chamon model code— The Chamon model code can be obtained from an XYZ product of three repetition codes [20]; see [21; Sec. 3.4]. Using only two repetition codes in the analogous 2D construction yields the XZZX code, making it a 2D analogue of the Chamon code [21; Sec. 2].
  • Repetition code— The Chamon model code can be obtained from an XYZ product of three repetition codes [20]; see [21; Sec. 3.4]. Using only two repetition codes in the analogous 2D construction yields the XZZX code, making it a 2D analogue of the Chamon code [21; Sec. 2].
  • Fracton stabilizer code— Subsystem symmetries play a role in finite-bias decoders for both XZZX and fracton codes [22]. The XZZX surface code resembles a Type-I fracton code with lineons in the limit of infinite noise bias [23].
  • Heavy-hexagon code— XZZX surface code can be adapted for a heavy-hexagonal point set [24].
  • Cluster-state code— XZZX surface code can be foliated for a noise-bias preserving MBQC [25] or FBQC [26] protocol; see also [27].
  • Concatenated cat code— The four-component cat code can be concatenated with the XZZX code to yield a fusion-based computation scheme on a 2D lattice [28].
  • GKP-surface code— GKP codes have been concatenated with XZZX surface codes [29].
  • Asymmetric quantum code (AQC)— The XZZX surface code can be foliated for a noise-bias preserving MBQC [25] or FBQC [26] protocol; see also [27].
  • Derby-Klassen (DK) code— The DK code encodes fermions into excitations of the Wen plaquette model [30].
  • XYZ color code— The XZZX surface (XYZ color) is a non-CSS analogue of the rotated surface (6.6.6 color) code such that the two codes are related by single-qubit Clifford rotations.
  • XYZ\(^2\) hexagonal stabilizer code— The XYZ\(^2\) hexagonal stabilizer code can be viewed as a concatenation of the \(YZZY\) surface code with one of the possible \([[2,1]]\) repetition codes, with the case of the bit-flip repetition code yielding a concatenation of the surface code with the dual-rail code [31].

Primary Hierarchy

Parents
The XZZX surface code is obtained from the rotated surface code by applying Hadamard gates on a subset of qubits such that \(XXXX\) and \(ZZZZ\) generators are both mapped to \(XZXZ\).
XZZX toric and planar codes can be treated in the general twist-defect surface code formalism [32].
The XZZX surface code is an example of \(\mathbb{Z}_2\) topological order as manifest in the Wen plaquette model [1].
XZZX surface code
Children
Imposing twisted (a.k.a. shifted) boundary conditions on the toric XZZX code yields the twisted XZZX code [2; Exam. 11 and Fig. 3][32; Fig. 6].

References

[1]
X.-G. Wen, “Quantum Orders in an Exact Soluble Model”, Physical Review Letters 90, (2003) arXiv:quant-ph/0205004 DOI
[2]
A. A. Kovalev, I. Dumer, and L. P. Pryadko, “Design of additive quantum codes via the code-word-stabilized framework”, Physical Review A 84, (2011) arXiv:1108.5490 DOI
[3]
B. M. Terhal, F. Hassler, and D. P. DiVincenzo, “From Majorana fermions to topological order”, Physical Review Letters 108, (2012) arXiv:1201.3757 DOI
[4]
J. P. Bonilla Ataides, D. K. Tuckett, S. D. Bartlett, S. T. Flammia, and B. J. Brown, “The XZZX surface code”, Nature Communications 12, (2021) arXiv:2009.07851 DOI
[5]
L. Bhardwaj, D. Gaiotto, and A. Kapustin, “State sum constructions of spin-TFTs and string net constructions of fermionic phases of matter”, Journal of High Energy Physics 2017, (2017) arXiv:1605.01640 DOI
[6]
D. K. Tuckett, S. D. Bartlett, S. T. Flammia, and B. J. Brown, “Fault-Tolerant Thresholds for the Surface Code in Excess of 5% Under Biased Noise”, Physical Review Letters 124, (2020) arXiv:1907.02554 DOI
[7]
K.-Y. Kuo and C.-Y. Lai, “Comparison of 2D topological codes and their decoding performances”, 2022 IEEE International Symposium on Information Theory (ISIT) 186 (2022) arXiv:2202.06612 DOI
[8]
D. K. Tuckett, S. D. Bartlett, and S. T. Flammia, “Ultrahigh Error Threshold for Surface Codes with Biased Noise”, Physical Review Letters 120, (2018) arXiv:1708.08474 DOI
[9]
K.-Y. Kuo and C.-Y. Lai, “Exploiting degeneracy in belief propagation decoding of quantum codes”, npj Quantum Information 8, (2022) arXiv:2104.13659 DOI
[10]
Y. Wu, S. Kolkowitz, S. Puri, and J. D. Thompson, “Erasure conversion for fault-tolerant quantum computing in alkaline earth Rydberg atom arrays”, Nature Communications 13, (2022) arXiv:2201.03540 DOI
[11]
O. Higgott, T. C. Bohdanowicz, A. Kubica, S. T. Flammia, and E. T. Campbell, “Improved Decoding of Circuit Noise and Fragile Boundaries of Tailored Surface Codes”, Physical Review X 13, (2023) arXiv:2203.04948 DOI
[12]
“Suppressing quantum errors by scaling a surface code logical qubit”, Nature 614, 676 (2023) arXiv:2207.06431 DOI
[13]
T. I. Andersen et al., “Non-Abelian braiding of graph vertices in a superconducting processor”, (2023) arXiv:2210.10255
[14]
K. C. Miao et al., “Overcoming leakage in quantum error correction”, Nature Physics 19, 1780 (2023) arXiv:2211.04728 DOI
[15]
“Quantum error correction below the surface code threshold”, Nature 638, 920 (2024) arXiv:2408.13687 DOI
[16]
E. Rosenfeld et al., “Magic state cultivation on a superconducting quantum processor”, (2025) arXiv:2512.13908
[17]
D. Bluvstein et al., “Logical quantum processor based on reconfigurable atom arrays”, Nature 626, 58 (2023) arXiv:2312.03982 DOI
[18]
D. Bluvstein et al., “A fault-tolerant neutral-atom architecture for universal quantum computation”, Nature 649, 39 (2025) arXiv:2506.20661 DOI
[19]
D. Forlivesi, L. Valentini, and M. Chiani, “Logical Error Rates of XZZX and Rotated Quantum Surface Codes”, (2023) arXiv:2312.17057
[20]
D. Maurice. Codes correcteurs quantiques pouvant se décoder itérativement. PhD thesis, Université Pierre et Marie Curie-Paris VI, 2014.
[21]
A. Leverrier, S. Apers, and C. Vuillot, “Quantum XYZ Product Codes”, Quantum 6, 766 (2022) arXiv:2011.09746 DOI
[22]
B. J. Brown and D. J. Williamson, “Parallelized quantum error correction with fracton topological codes”, Physical Review Research 2, (2020) arXiv:1901.08061 DOI
[23]
J. F. S. Miguel, D. J. Williamson, and B. J. Brown, “A cellular automaton decoder for a noise-bias tailored color code”, Quantum 7, 940 (2023) arXiv:2203.16534 DOI
[24]
Y. Kim, J. Kang, and Y. Kwon, “Design of Quantum error correcting code for biased error on heavy-hexagon structure”, (2022) arXiv:2211.14038
[25]
J. Claes, J. E. Bourassa, and S. Puri, “Tailored cluster states with high threshold under biased noise”, npj Quantum Information 9, (2023) arXiv:2201.10566 DOI
[26]
H. Bombín, C. Dawson, N. Nickerson, M. Pant, and J. Sullivan, “Increasing error tolerance in quantum computers with dynamic bias arrangement”, (2023) arXiv:2303.16122
[27]
A. M. Stephens, W. J. Munro, and K. Nemoto, “High-threshold topological quantum error correction against biased noise”, Physical Review A 88, (2013) arXiv:1308.4776 DOI
[28]
H. K. Babla, J. D. Teoh, J. Claes, D. K. Weiss, S. Singh, R. J. Schoelkopf, and S. Puri, “Fault-tolerant Fusion-based Quantum Computing with the Four-legged Cat Code”, (2025) arXiv:2508.03796
[29]
J. Zhang, Y.-C. Wu, and G.-P. Guo, “Concatenation of the Gottesman-Kitaev-Preskill code with the XZZX surface code”, Physical Review A 107, (2023) arXiv:2207.04383 DOI
[30]
R. W. Chien and J. D. Whitfield, “Custom fermionic codes for quantum simulation”, (2020) arXiv:2009.11860
[31]
B. Srivastava, Y. Xiao, A. F. Kockum, B. Criger, and M. Granath, “Sequential decoding of the XYZ\(^2\) hexagonal stabilizer code”, (2025) arXiv:2505.03691
[32]
R. Sarkar and T. J. Yoder, “A graph-based formalism for surface codes and twists”, Quantum 8, 1416 (2024) arXiv:2101.09349 DOI
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Zoo Code ID: xzzx

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“XZZX surface code”, The Error Correction Zoo (V. V. Albert & P. Faist, eds.), 2024. https://errorcorrectionzoo.org/c/xzzx
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@incollection{eczoo_xzzx, title={XZZX surface code}, booktitle={The Error Correction Zoo}, year={2024}, editor={Albert, Victor V. and Faist, Philippe}, url={https://errorcorrectionzoo.org/c/xzzx} }
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