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arXiv:2512.03583

Energy-Scaled Zero-Noise Extrapolation for Gottesman-Kitaev-Preskill Code

Gui-Zhong Luo, Matthew Otten

quant-phSubmitted Dec 3, 2025• Announced Dec 4, 2025• 0 citations
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Abstract

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.

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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: $(i)$ using stochastically shifted GKP states in place of coherently damped ones, and $(ii)$ the use of SB decoding.

arXiv:2504.13383•Physical Review A•Oct 16, 2025•1 citation
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.
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 candidate for realizing fault-tolerant quantum computation. Among existing error-correction protocols for GKP code, the Steane-type scheme is a canonical and widely adopted paradigm, yet its intrinsic noise propagation pattern limits further performance improvement. In this work, we propose a preprocessing-based Steane-type (P-Steane) scheme, which introduces a tunable preprocessing stage with squeezing parameters aaa and bbb to actively reshape noise propagation, thereby constituting a parameter framework. This framework spans a spectrum of protocols beyond existing methods, reproducing the performance of both the ME-Steane scheme (a=1a=1a=1, b=1b=1b=1) and the teleportation-based scheme (a=1/2a=1/\sqrt{2}a=1/2​, b=2b=\sqrt{2}b=2​) as special cases. Crucially, in the small-noise regime and when the data qubit is noisier than the ancilla qubits, P-Steane scheme achieves the minimum product of position- and momentum-quadrature output noise variances when 2a=b2a = b2a=b, and consistently outperforms the ME-Steane scheme within a specific squeezing-parameter range under this condition.
Concatenation of a bosonic code with a qubit code is one of the promising ways to achieve fault-tolerant quantum computation. As one of the most important bosonic codes, the Gottesman-Kitaev-Preskill (GKP) code is proposed to correct small displacement errors in phase space. If the noise in phase space is biased, the square-lattice GKP code can be concatenated with the repetition code that promises a high fault-tolerant threshold to suppress the logical error. In this work, we study the performance of GKP repetition codes with finite-energy ancillary GKP qubits in correcting biased noise. We find that there exists a critical value of noise variance for the ancillary GKP qubit such that the logical Pauli error rate decreases when increasing the code size. Furthermore, one round of GKP error correction has to be performed before concatenating with the repetition code. Our study paves the way for practical implementation of error correction by concatenating the GKP code with low-level qubit codes.
Bosonic quantum error-correcting codes encode logical information in a harmonic oscillator, with the Gottesman-Kitaev-Preskill (GKP) and number-phase (NP) codes representing two fundamentally different encoding paradigms. Although both have been extensively studied, it remains unclear under what physical noise conditions (including photon loss and dephasing) one encoding intrinsically outperforms the other. Here we estimate a quantitative performance boundary between GKP and NP codes under general photon loss-dephasing noise. By optimizing code parameters within each encoding family, we identify the noise regimes in which each code exhibits a fundamental advantage. In particular, we find that the crossover occurs when the dephasing strength is approximately two orders of magnitude smaller than the loss strength, revealing a sharp separation between operational regimes. Beyond this specific comparison, our work establishes a practical and extensible methodology for benchmarking bosonic codes and optimizing their parameters, providing concrete guidance for the experimental selection and deployment of bosonic encodings in realistic noise environments.
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) 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.