Gottesman-Kitaev-Preskill (GKP) code[1,2] 

Description

Quantum lattice code for a non-degenerate lattice, thereby admitting a finite-dimensional logical subspace. Codes on \(n\) modes can be constructed from lattices with \(2n\)-dimensional full-rank Gram matrices \(A\).

The centralizer for the stabilizer group within the displacement operators case can be identified with the symplectic dual lattice \({\mathcal{L}}^{\perp}\) (i.e. all points in \(\mathbb{R}^{2n}\) that have integer symplectic inner product with all points in \({\mathcal{L}}\) ), such that logical operations are identified with the dual quotients \({\mathcal{L}}^{\perp}/{\mathcal{L}}\). The size of this dual quotient is the determinant of the Gram matrix, yielding the logical dimension \(d=\sqrt{\| \det{A}\|}\) [1]. Stabilizer generator matrices equivalent under symplectic transformations are classified by distinct Hermite normal forms [3].

The space of all single-mode GKP codes is the moduli space of elliptic curves, i.e., the three sphere with a trefoil knot removed [4].

Protection

The level of protection against displacement errors is quantified by the Euclidean code distance \(\Delta=\min_{x\in {\mathcal{L}}^{\perp}\setminus {\mathcal{L}}} \|x\|_2\) [3].

Rate

Transmission schemes with multimode GKP codes achieve, up to a constant-factor offset, the capacity of AD, a lower bound on displacement-noise, and a lower bound on thermal-noise Gaussian channel capacities [2,57]. Particular random lattice families of multimode GKP codes achieve the hashing bound of the displacement noise channel [2].

Encoding

GKP codes with fixed \(n\) and prime-dimensional logical Hilbert space are symplectically related to a disjoint product of single-mode GKP codes on \(n\) modes, such that encoding via Gaussian unitaries is possible.Dissipative stabilization of finite-energy GKP states using stabilizers conjugated by cooling ([8], Appx. B) or damping operator, i.e., a damped exponential of the total occupation number [9,10].

Gates

Gaussian operations and homodyne measurements on GKP states are classically simulable, and there is a sufficient condition for an additional element to achieve universal quantum computation [11].There is a relation between magic (i.e., how far away a state is from being a stabilizer state) and non-Gaussianity for GKP codewords [12,13]. In particular, implementing a non-Clifford logical gate requires a higher degree of non-Gaussianity than that expressed by ideal non-normalizable GKP states [13].By applying GKP error correction to Gaussian input states, computational universality can be achieved without additional non-Gaussian elements [14]. This procedure can be alternatively desscribed as performing heterodyne detection on one half of a GKP encoded Bell pair.Logical shadow tomography protocol [15].

Decoding

The MLD decoder for Gaussian displacement errors is realized by evaluating a lattice theta function, and in general the decision can be approximated by either solving (approximating) the closest vector problem (CVP) [16] (a.k.a. closest lattice point problem) or by using other effective iterative schemes when, e.g., the lattice represents a concatenated GKP code [3,1719]. While the decoder time scales exponentially with number of modes \(n\) generically, the time can be polynomial in \(n\) for certain codes [20].Babai's nearest plane algorithm [21] can be used for bounded-distance decoding [20].Combining AD noise with amplification yields displacement noise, the noise that GKP codes are designed to correct [7].ML decoder for correcting shift errors in GKP two-qubit gates [22].

Fault Tolerance

Logical Clifford operations are given by Gaussian unitaries, which map bounded-size errors to bounded-size errors [1]. For single-mode GKP codes, these operations correspond to non-trivial loops in the space of all single-mode GKP codes (the moduli space of elliptic curves, i.e., the three sphere with a trefoil knot removed) [4]. Such gates provide another example of monodromy under the particular notion of parallel transport introduced in Ref. [23].

Notes

Reviews on GKP codes presented in Refs. [2426].

Parent

  • Quantum lattice code — GKP codes are \(n\)-mode quantum lattice codes with \(2n\) stabilizers, i.e., constructed using a non-degenerate lattice.

Children

Cousins

  • Approximate quantum error-correcting code (AQECC) — Approximate error-correction offered by GKP codes yields achievable rates that are a constant away from the capacity of Guassian loss channels [2,57].
  • Amplitude-damping (AD) code — Transmission schemes with multimode GKP codes achieve, up to a constant-factor offset, the capacity of AD, displacement-noise, and thermal-noise Gaussian loss channels [2,57]. Combining AD noise with amplification yields displacement noise, the noise that GKP codes are designed to correct [7].
  • Quadrature-amplitude modulation (QAM) code — Finite-energy GKP codes are quantum analogues of lattice-based QAM codes in that both use a subset of points on a lattice.
  • Numerically optimized bosonic code — Numerically optimizing GKP code lattices yields codes for three, seven, and nine modes with larger distances and fidelities than known GKP codes [20]. Neural networks can be used to optimize approximate GKP states [27].

References

[1]
D. Gottesman, A. Kitaev, and J. Preskill, “Encoding a qubit in an oscillator”, Physical Review A 64, (2001) arXiv:quant-ph/0008040 DOI
[2]
J. Harrington and J. Preskill, “Achievable rates for the Gaussian quantum channel”, Physical Review A 64, (2001) arXiv:quant-ph/0105058 DOI
[3]
J. Conrad, J. Eisert, and F. Arzani, “Gottesman-Kitaev-Preskill codes: A lattice perspective”, Quantum 6, 648 (2022) arXiv:2109.14645 DOI
[4]
J. Conrad, A. G. Burchards, and S. T. Flammia, “Lattices, Gates, and Curves: GKP codes as a Rosetta stone”, (2024) arXiv:2407.03270
[5]
K. Sharma et al., “Bounding the energy-constrained quantum and private capacities of phase-insensitive bosonic Gaussian channels”, New Journal of Physics 20, 063025 (2018) arXiv:1708.07257 DOI
[6]
M. Rosati, A. Mari, and V. Giovannetti, “Narrow bounds for the quantum capacity of thermal attenuators”, Nature Communications 9, (2018) arXiv:1801.04731 DOI
[7]
K. Noh, V. V. Albert, and L. Jiang, “Quantum Capacity Bounds of Gaussian Thermal Loss Channels and Achievable Rates With Gottesman-Kitaev-Preskill Codes”, IEEE Transactions on Information Theory 65, 2563 (2019) arXiv:1801.07271 DOI
[8]
N. C. Menicucci, “Fault-Tolerant Measurement-Based Quantum Computing with Continuous-Variable Cluster States”, Physical Review Letters 112, (2014) arXiv:1310.7596 DOI
[9]
B. Royer, S. Singh, and S. M. Girvin, “Stabilization of Finite-Energy Gottesman-Kitaev-Preskill States”, Physical Review Letters 125, (2020) arXiv:2009.07941 DOI
[10]
B. Royer, S. Singh, and S. M. Girvin, “Encoding Qubits in Multimode Grid States”, PRX Quantum 3, (2022) arXiv:2201.12337 DOI
[11]
C. Calcluth et al., “Sufficient Condition for Universal Quantum Computation Using Bosonic Circuits”, PRX Quantum 5, (2024) arXiv:2309.07820 DOI
[12]
O. Hahn et al., “Quantifying Qubit Magic Resource with Gottesman-Kitaev-Preskill Encoding”, Physical Review Letters 128, (2022) arXiv:2109.13018 DOI
[13]
O. Hahn, G. Ferrini, and R. Takagi, “Bridging magic and non-Gaussian resources via Gottesman-Kitaev-Preskill encoding”, (2024) arXiv:2406.06418
[14]
B. Q. Baragiola et al., “All-Gaussian Universality and Fault Tolerance with the Gottesman-Kitaev-Preskill Code”, Physical Review Letters 123, (2019) arXiv:1903.00012 DOI
[15]
J. Conrad, J. Eisert, and S. T. Flammia, “Chasing shadows with Gottesman-Kitaev-Preskill codes”, (2024) arXiv:2411.00235
[16]
E. Agrell et al., “Closest point search in lattices”, IEEE Transactions on Information Theory 48, 2201 (2002) DOI
[17]
C. Vuillot et al., “Quantum error correction with the toric Gottesman-Kitaev-Preskill code”, Physical Review A 99, (2019) arXiv:1810.00047 DOI
[18]
K. Noh and C. Chamberland, “Fault-tolerant bosonic quantum error correction with the surface–Gottesman-Kitaev-Preskill code”, Physical Review A 101, (2020) arXiv:1908.03579 DOI
[19]
N. Raveendran et al., “Finite Rate QLDPC-GKP Coding Scheme that Surpasses the CSS Hamming Bound”, Quantum 6, 767 (2022) arXiv:2111.07029 DOI
[20]
M. Lin, C. Chamberland, and K. Noh, “Closest Lattice Point Decoding for Multimode Gottesman-Kitaev-Preskill Codes”, PRX Quantum 4, (2023) arXiv:2303.04702 DOI
[21]
L. Babai, “On Lovász’ lattice reduction and the nearest lattice point problem”, Combinatorica 6, 1 (1986) DOI
[22]
K. Noh, C. Chamberland, and F. G. S. L. Brandão, “Low-Overhead Fault-Tolerant Quantum Error Correction with the Surface-GKP Code”, PRX Quantum 3, (2022) arXiv:2103.06994 DOI
[23]
D. Gottesman and L. L. Zhang, “Fibre bundle framework for unitary quantum fault tolerance”, (2017) arXiv:1309.7062
[24]
B. M. Terhal, J. Conrad, and C. Vuillot, “Towards scalable bosonic quantum error correction”, Quantum Science and Technology 5, 043001 (2020) arXiv:2002.11008 DOI
[25]
A. L. Grimsmo and S. Puri, “Quantum Error Correction with the Gottesman-Kitaev-Preskill Code”, PRX Quantum 2, (2021) arXiv:2106.12989 DOI
[26]
A. J. Brady et al., “Advances in bosonic quantum error correction with Gottesman–Kitaev–Preskill Codes: Theory, engineering and applications”, Progress in Quantum Electronics 100496 (2024) arXiv:2308.02913 DOI
[27]
Y. Zeng et al., “Neural Network-Based Design of Approximate Gottesman-Kitaev-Preskill Code”, (2024) arXiv:2411.01265
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Zoo Code ID: multimodegkp

Cite as:
“Gottesman-Kitaev-Preskill (GKP) code”, The Error Correction Zoo (V. V. Albert & P. Faist, eds.), 2022. https://errorcorrectionzoo.org/c/multimodegkp
BibTeX:
@incollection{eczoo_multimodegkp, title={Gottesman-Kitaev-Preskill (GKP) code}, booktitle={The Error Correction Zoo}, year={2022}, editor={Albert, Victor V. and Faist, Philippe}, url={https://errorcorrectionzoo.org/c/multimodegkp} }
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