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arXiv:2504.13383 · Physical Review A

Logical channels in approximate Gottesman-Kitaev-Preskill error correction

Mahnaz Jafarzadeh, Jonathan Conrad, Rafael N. Alexander, Ben Q. Baragiola

Published Oct 16, 2025• 1 citation
arXivHTMLPDF

Abstract

The Gottesman-Kitaev-Preskill (GKP) encoding is a top contender among bosonic codes for fault-tolerant quantum computation. However, analysis of the code is complicated by the fact that finite-energy code states leak out of the ideal GKP code space and are not orthogonal. We analyze a variant of the GKP stabilizer measurement circuit that virtually projects onto the ideal GKP code space between rounds of error correction, even when damped, finite-energy GKP states are used. This allows us to identify logical maps between projectors; however, due to finite-energy effects, these maps fail to resolve completely positive, trace-preserving (CPTP) channels on the logical GKP code space. We present two solutions to this problem based on channel twirling the damping operator. The first uses symmetries of standard binning (SB) decoding to passively twirl over the full stabilizer group. Doing so converts small amounts of damping into stochastic Gaussian random noise (GRN). The second uses active twirling over a minimal set of representative Pauli shifts that keeps the energy in the code finite and allows for arbitrary decoding. This approach is not limited to small damping and allows the study of decoding more general than SB, which can be optimized to the noise in the circuit. Focusing on damping, we compare decoding strategies tailored to different levels of effective squeezing. While our results indicate that SB decoding is suboptimal for finite-energy GKP states, we observe that the advantage of optimized decoding shrinks as the energy in the code increases. Moreover, the performance of both decoding strategies converges to that of the stabilizer-twirled GRN logical channel. These studies provide stronger arguments for two commonplace procedures in the analysis of GKP error correction in the fault-tolerance regime: $(i)$ using stochastically shifted GKP states in place of coherently damped ones, and $(ii)$ the use of SB decoding.

DOI
10.1103/c8hk-v1qf

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The Gottesman-Kitaev-Preskill (GKP) error-correcting code encodes a finite-dimensional logical space in one or more bosonic modes, and has recently been demonstrated in trapped ions and superconducting microwave cavities. In this work we introduce a new subsystem decomposition for GKP codes that we call the stabilizer subsystem decomposition, analogous to the usual approach to quantum stabilizer codes. The decomposition has the defining property that a partial trace over the nonlogical stabilizer subsystem is equivalent to an ideal decoding of the logical state, distinguishing it from previous GKP subsystem decompositions. We describe how to decompose arbitrary states across the subsystem decomposition using a set of transformations that move between the decompositions of different GKP codes. Besides providing a convenient theoretical view on GKP codes, such a decomposition is also of practical use. We use the stabilizer subsystem decomposition to efficiently simulate noise acting on single-mode GKP codes, and in contrast to more conventional Fock basis simulations, we are able to consider essentially arbitrarily large photon numbers for realistic noise channels, such as loss and dephasing. Published by the American Physical Society 2024

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The Gottesman-Kitaev-Preskill (GKP) encoding is a top contender among bosonic codes for fault-tolerant quantum computation. However, analysis of the code is complicated by the fact that finite-energy code states leak out of the ideal GKP code space and are not orthogonal. We analyze a variant of the GKP stabilizer measurement circuit that virtually projects onto the ideal GKP code space between rounds of error correction, even when damped, finite-energy GKP states are used. This allows us to identify logical maps between projectors; however, due to finite-energy effects, these maps fail to resolve completely positive, trace-preserving (CPTP) channels on the logical GKP code space. We present two solutions to this problem based on channel twirling the damping operator. The first uses symmetries of standard binning (SB) decoding to passively twirl over the full stabilizer group. Doing so converts small amounts of damping into stochastic Gaussian random noise (GRN). The second uses active twirling over a minimal set of representative Pauli shifts that keeps the energy in the code finite and allows for arbitrary decoding. This approach is not limited to small damping and allows the study of decoding more general than SB, which can be optimized to the noise in the circuit. Focusing on damping, we compare decoding strategies tailored to different levels of effective squeezing. While our results indicate that SB decoding is suboptimal for finite-energy GKP states, we observe that the advantage of optimized decoding shrinks as the energy in the code increases. Moreover, the performance of both decoding strategies converges to that of the stabilizer-twirled GRN logical channel. These studies provide stronger arguments for two commonplace procedures in the analysis of GKP error correction in the fault-tolerance regime: (i)(i)(i) using stochastically shifted GKP states in place of coherently damped ones, and (ii)(ii)(ii) the use of SB decoding.
In order to solve practical problems on a quantum computer, it is necessary to use fault-tolerant quantum error correction schemes to overcome noise: the errors arising from imperfections in physical components. The Gottesman-Kitaev-Preskill (GKP) code aims at achieving this in a hardware efficient manner by encoding finite-dimensional logical subspaces in the Hilbert space of one or more continuous variable modes. In near term implementations, however, it is not feasible to eliminate errors entirely, so it is natural to also employ alternative error mitigation techniques together with error correction. In this work, we study a quantum error mitigation method known as probabilistic error cancellation in the context of the GKP code. We compare Steane-type and teleportation-based GKP error correction, and calculate the sampling overheads associated with the technique for square and hexagonal GKP codes. We employ the stabilizer subsystem decomposition for GKP codes to obtain an effective logical channel for noisy operations that is used to express the ideal one of a target logical unitary. We consider noise from finite squeezing on the data and the two ancilla modes, needed for error correction, and examine the relationship between the sampling overhead and the noise for different decoding methods. Our results are calculated for single- and two-qubit GKP Clifford gates and one round of error correction, and show the nontrivial combination of error correction and mitigation in continuous variable codes.
The Gottesman-Kitaev-Preskill (GKP) code is a promising bosonic quantum error-correcting code, encoding logical qubits into a bosonic mode in such a way that many physically relevant noise types can be corrected effectively. A particularly relevant noise channel is the pure loss channel, which the GKP code is known to protect against. In particular, it is commonly pointed out that losses can be corrected by the GKP code by transforming the losses into random Gaussian displacements through a quantum-limited amplification channel. However, implementing such amplification in practice is not ideal and could easily introduce an additional overhead of noise from associated experimental imperfections. Here, we analyze the performance of teleportation-based GKP error correction against loss in the absence of an amplification channel. We show that amplification is not required to perform GKP error correction and that performing amplification actually worsens the performance for practically relevant parameter regimes.
The Gottesman-Kitaev-Preskill (GKP) code is an exciting route to fault-tolerant quantum computing since Gaussian resources and GKP Pauli-eigenstate preparation are sufficient to achieve universal quantum computing. However, there is a disconnect between the noise model that GKP qubits are in theory designed to correct—uniform random displacement errors—and the conditions that affect GKP qubits in superconducting devices in practice: realistic noise channels, logical gates, and inefficient measurements. In this work we bridge this gap in three ways. First, we approximate the effect loss and dephasing on approximate GKP codestates using a random displacement channel, and show that this approximation matches well with numerics. Second, we analyze the error-spreading properties of GKP Clifford gates and describe how a modification in the decoder following the implementation of each gate can reduce the gate infidelity by multiple orders of magnitude. Finally, we consider the effect of homodyne measurement inefficiencies on logical state readout and analyze a scheme to improve the measurement efficiency using the theory of quantum trajectories.
Bosonic codes provide an alternative option for quantum error correction. An important category of bosonic codes called the Gottesman-Kitaev-Preskill (GKP) code has aroused much interest recently. Theoretically, the error correction ability of the GKP code is limited since it can only correct small shift errors in position and momentum quadratures. A natural approach to promote the GKP error correction for large-scale, fault-tolerant quantum computation is concatenating encoded GKP states with a stabilizer code. The performance of the XZZX surface-GKP code, i.e., the single-mode GKP code concatenated with the XZZX surface code is investigated in this paper under two different noise models. Firstly, in the code-capacity noise model, the asymmetric rectangular GKP code with parameter $\ensuremath{\lambda}$ is introduced. Using the minimum weight perfect matching decoder combined with the continuous-variable GKP information, the optimal threshold of the XZZX-surface GKP code reaches $\ensuremath{\sigma}\ensuremath{\approx}0.67$ when $\ensuremath{\lambda}=2.1$, compared with the threshold $\ensuremath{\sigma}\ensuremath{\approx}0.60$ of the standard surface-GKP code. Secondly, we analyze the shift errors of two-qubit gates in the actual implementation and build the full circuit-level noise model. By setting the appropriate bias parameters, the logical error rate is reduced by several times in some cases. These results indicate the XZZX surface-GKP codes are more suitable for asymmetric concatenation under the general noise models. We also estimate the overhead of the XZZX-surface GKP code which uses about 291 GKP states with the noise parameter 18.5 dB ($\ensuremath{\kappa}/g\ensuremath{\approx}0.71%$) to encode a logical qubit with the error rate $2.53\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}7}$, compared with the qubit-based surface code using 3041 qubits to achieve almost the same logical error rate.
The performance of Gottesman-Kitaev-Preskill (GKP) codes, an approach to hardware-efficient quantum error correction, is limited by the finite squeezing capabilities of current experimental platforms. To circumvent this hardware demand, we introduce Energy-Scaled Zero-Noise Extrapolation (ES-ZNE), a quantum error mitigation protocol that uses the mean photon number of the GKP code as a tunable effective noise parameter. The protocol measures logical observables at a series of accessible finite energies and extrapolates the results to the ideal, infinite-energy limit using an ansatz based on the code's asymptotic error scaling. Through simulating a GKP qubit under a pure-loss channel, we demonstrate that ES-ZNE successfully mitigates finite-energy errors, recovering the ideal expectation values (within numerical uncertainty) in the shallow-noise regime. Furthermore, by computationally removing artifacts arising from the finite-energy encoding, our method characterizes the intrinsic performance of the ideal GKP code, revealing a sharp error threshold beyond which the code's corrective power diminishes. These results establish ES-ZNE as a practical, software-based strategy for enhancing the performance of near-term bosonic quantum processors, trading sampling overhead for demanding physical resources like high squeezing.
The Gottesman-Kitaev-Preskill (GKP) error-correcting code encodes a finite-dimensional logical space in one or more bosonic modes, and has recently been demonstrated in trapped ions and superconducting microwave cavities. In this work we introduce a new subsystem decomposition for GKP codes that we call the stabilizer subsystem decomposition, analogous to the usual approach to quantum stabilizer codes. The decomposition has the defining property that a partial trace over the nonlogical stabilizer subsystem is equivalent to an ideal decoding of the logical state, distinguishing it from previous GKP subsystem decompositions. We describe how to decompose arbitrary states across the subsystem decomposition using a set of transformations that move between the decompositions of different GKP codes. Besides providing a convenient theoretical view on GKP codes, such a decomposition is also of practical use. We use the stabilizer subsystem decomposition to efficiently simulate noise acting on single-mode GKP codes, and in contrast to more conventional Fock basis simulations, we are able to consider essentially arbitrarily large photon numbers for realistic noise channels, such as loss and dephasing. Published by the American Physical Society 2024