Fault-tolerant quantum computation in photonic architectures relies on the efficient preparation of high-fidelity logical magic states under realistic constraints imposed by finite squeezing and photon loss. In this work, we study logical T-gate magic-state preparation in GKP-encoded photonic qubits using a repeat-until-success injection protocol combined with outer surface-code protection. We develop an architecture-level modeling framework based on a lightweight density-matrix simulator implemented with standard numerical linear algebra. Finite squeezing is mapped to effective logical dephasing, depolarizing noise is included at the logical level, and photon loss is treated as a heralded erasure process. This approach avoids explicit continuous-variable wavefunction simulation, hardware-specific photonic models, and quantum software frameworks, enabling transparent and computationally efficient exploration of architectural trade-offs. We perform systematic parameter sweeps over squeezing values from 8 to 16 dB, baseline loss probabilities between 0.01 and 0.03, and surface-code distances d = 1, 3, 5, and 7. Across this regime, we evaluate repeat-until-success probability, average injection overhead, and logical magic-state fidelity. We find that success probabilities exceed 0.94 across all studied parameters, with an average overhead close to unity. After outer-code protection, logical fidelities reach approximately 0.77 to 0.80 and show weak sensitivity to moderate photon loss but a strong dependence on squeezing. Phase-boundary analysis identifies minimum squeezing requirements needed to simultaneously achieve high success probability and logical fidelity. These results provide quantitative design guidance for scalable photonic fault-tolerant quantum architectures.
Fault-tolerant quantum computation in photonic architectures relies on the efficient preparation of high-fidelity logical magic states under realistic constraints imposed by finite squeezing and photon loss. In this work, we study logical T-gate magic-state preparation in GKP-encoded photonic qubits using a repeat-until-success injection protocol combined with outer surface-code protection. We develop an architecture-level modeling framework based on a lightweight density-matrix simulator implemented with standard numerical linear algebra. Finite squeezing is mapped to effective logical dephasing, depolarizing noise is included at the logical level, and photon loss is treated as a heralded erasure process. This approach avoids explicit continuous-variable wavefunction simulation, hardware-specific photonic models, and quantum software frameworks, enabling transparent and computationally efficient exploration of architectural trade-offs. We perform systematic parameter sweeps over squeezing values from 8 to 16 dB, baseline loss probabilities between 0.01 and 0.03, and surface-code distances d = 1, 3, 5, and 7. Across this regime, we evaluate repeat-until-success probability, average injection overhead, and logical magic-state fidelity. We find that success probabilities exceed 0.94 across all studied parameters, with an average overhead close to unity. After outer-code protection, logical fidelities reach approximately 0.77 to 0.80 and show weak sensitivity to moderate photon loss but a strong dependence on squeezing. Phase-boundary analysis identifies minimum squeezing requirements needed to simultaneously achieve high success probability and logical fidelity. These results provide quantitative design guidance for scalable photonic fault-tolerant quantum architectures.
Fault-tolerant quantum error correction is essential for implementing quantum algorithms of significant practical importance.In this work, we propose a highly effective use of the surface Gottesman-Kitaev-Preskill (GKP) code, i.e., the surface code consisting of bosonic GKP qubits instead of bare two-level qubits.In our proposal, we use error-corrected two-qubit gates between GKP qubits and introduce a maximum-likelihood decoding strategy for correcting shift errors in the two-GKP-qubit gates.Our proposed decoding reduces the total CNOT failure rate of the GKP qubits, e.g., from 0.87% to 0.36% at a GKP squeezing of 12 dB, compared to the case where the simple closest-integer decoding is used.Then, by concatenating the GKP code with the surface code, we find that the threshold GKP squeezing is given by 9.9 dB under the the assumption that finite squeezing of the GKP states is the dominant noise source.More importantly, we show that a low logical failure rate p L < 10 -7 can be achieved with moderate hardware requirements, e.g., 291 modes and 97 qubits at a GKP squeezing of 12 dB as opposed to 1457 bare qubits for the standard rotated surface code at an equivalent noise level (i.e., p = 0.36%).Such a low failure rate of our surface-GKP code is possible through the use of space-time correlated edges in the matching graphs of the surface-code decoder.Further, all edge weights in the matching graphs are computed dynamically based on analog information from the GKP error correction using the full history of all syndrome measurement rounds.We also show that a highly squeezed GKP state of GKP squeezing 12 dB can be experimentally realized by using a dissipative stabilization method, namely, the big-small-big method, with fairly conservative experimental parameters.Lastly, we introduce a three-level ancilla scheme to mitigate ancilla decay errors during a GKP state preparation.
The scalability of photonic implementations of fault-tolerant quantum computing based on Gottesman-Kitaev-Preskill (GKP) qubits is injured by the requirements of inline squeezing and reconfigurability of the linear optical network.In this work we propose a topologically error-corrected architecture that does away with these elements at no cost-in fact, at an advantage-to state preparation overheads.Our computer consists of three modules: a two-dimensional (2D) array of probabilistic sources of GKP states; a depthfour circuit of static beam splitters, phase shifters, and short delay lines; and a 2D array of homodyne detectors.The symmetry of our proposed circuit allows us to combine the effects of finite squeezing and uniform photon loss within the noise model, resulting in more comprehensive threshold estimates.These jumps over both architectural and analytical hurdles considerably expedite the construction of a photonic quantum computer.
Reliable quantum memory is essential for scalable quantum networks and fault-tolerant photonic quantum computing. We present a quantitative analysis of an all-optical quantum memory architecture in which a Gottesman-Kitaev-Preskill (GKP) encoded qubit is stored in a fibre loop and periodically stabilized using teleportation-based error correction. By modelling fibre propagation as a pure-loss channel and representing each correction round as an effective logical map acting on the Bloch vector, we obtain a compact description of the full multi-round memory channel. We show that syndrome decoder optimization plays a crucial role in the experimentally relevant finite-squeezing regime. The optimal decoder deviates from standard square-grid GKP decoder in both tile-size and tile-shape, leading to significant improved logical performance. Using this optimized decoding strategy, we identify a squeezing-dependent optimal spacing between correction nodes that maximizes the memory lifetime. Remarkably, this optimal segment length is largely independent of the desired storage time, providing a simple and practical design rule for fibre-loop quantum memory. We further find a squeezing threshold of approximately 6.7 dB below which intermediate error correction becomes counterproductive, while above threshold the achievable storage time increases approximately exponentially with squeezing. For example, at 17 dB squeezing, storage times exceeding 400 ms can be achieved with logical infidelity below 1%. These results establish clear performance benchmarks and reveal the fundamental trade-off between photon loss, squeezing, and correction frequency in continuous-variable architectures. Our findings provide actionable design principles for near-term photonic quantum memory and clarify the path toward scalable all-optical fault-tolerant quantum storage.
Photonic quantum networks require error-correction architectures that remain useful with finite-energy bosonic states, pure-loss fiber transmission, and explicit resource accounting. In this light, we study a concatenated architecture in which each physical rail is a finitely squeezed Gottesman--Kitaev--Preskill (GKP) qubit transmitted through a pure-loss fiber segment, corrected by teleportation-based GKP error correction with finitely squeezed ancillae, and decoded by an outer quantum parity code (QPC). The GKP layer converts continuous homodyne syndromes into effective rail-level Pauli marginals, while the QPC layer suppresses the residual qubit-level errors. For the concatenated code family considered here, we find a finite-squeezing threshold of 5.06dB at zero propagation loss. In the memory setting, the QPC layer lowers the squeezing at which repeated error correction becomes beneficial from 6.7dB for bare GKP correction to 5.2dB for QPC(3,3) and 4.3dB for QPC(5,5), and improves the average-fidelity ratio by up to 75--90% in the relevant intermediate-noise regime. In the repeater setting, avoiding pre-amplification gives larger secret-key fractions at moderate squeezing, but also produces an optimal squeezing because highly squeezed GKP peaks become sensitive to loss-induced inward displacement. Resource-normalized rates show that QPC concatenation can exceed the repeaterless PLOB benchmark by orders of magnitude and extend the communication reach, at short repeater spacing, to distances of order 104km with 14dB squeezing. However, QPC concatenation becomes detrimental when each elementary hop is too lossy. These results provide quantitative design rules for finite-squeezing GKP--QPC quantum memories and repeaters.
Continuous-variable measurement-based quantum computation on cluster states has in recent years shown great potential for scalable, universal, and fault-tolerant quantum computation when combined with the Gottesman-Kitaev-Preskill (GKP) code and quantum error correction.However, no complete fault-tolerant architecture exists that includes everything from cluster-state generation with finite squeezing to gate implementations with realistic noise and error correction.In this work, we propose a simple architecture for the preparation of a cluster state in three dimensions in which gates can be efficiently implemented by gate teleportation.To accommodate scalability, we propose architectures that allow both spatial and temporal multiplexing, with the temporally encoded version requiring as little as two squeezed light sources.Because of its three-dimensional structure, the architecture supports topological qubit error correction, while GKP error correction is efficiently realized within the architecture by teleportation.To validate fault tolerance, the architecture is simulated using surface-GKP codes, including noise from GKP states as well as gate noise caused by finite squeezing in the cluster state.We find a fault-tolerant squeezing threshold of 12.7 dB, with room for further improvement.
Fault-tolerant quantum error correction is essential for implementing quantum algorithms of significant practical importance. In this work, we propose a highly effective use of the surface-GKP code, i.e., the surface code consisting of bosonic GKP qubits instead of bare two-dimensional qubits. In our proposal, we use error-corrected two-qubit gates between GKP qubits and introduce a maximum likelihood decoding strategy for correcting shift errors in the two-GKP-qubit gates. Our proposed decoding reduces the total CNOT failure rate of the GKP qubits, e.g., from 0.87% to 0.36% at a GKP squeezing of 12dB, compared to the case where the simple closest-integer decoding is used. Then, by concatenating the GKP code with the surface code, we find that the threshold GKP squeezing is given by 9.9dB under the the assumption that finite-squeezing of the GKP states is the dominant noise source. More importantly, we show that a low logical failure rate pL<10−7 can be achieved with moderate hardware requirements, e.g., 291 modes and 97 qubits at a GKP squeezing of 12dB as opposed to 1457 bare qubits for the standard rotated surface code at an equivalent noise level (i.e., p=0.36%). Such a low failure rate of our surface-GKP code is possible through the use of space-time correlated edges in the matching graphs of the surface code decoder. Further, all edge weights in the matching graphs are computed dynamically based on analog information from the GKP error correction using the full history of all syndrome measurement rounds. We also show that a highly-squeezed GKP state of GKP squeezing ≳12dB can be experimentally realized by using a dissipative stabilization method, namely, the Big-small-Big method, with fairly conservative experimental parameters. Lastly, we introduce a three-level ancilla scheme to mitigate ancilla decay errors during a GKP state preparation.