Achievable rates for concatenated square Gottesman-Kitaev-Preskill codes
- URL: http://arxiv.org/abs/2505.10499v1
- Date: Thu, 15 May 2025 17:01:51 GMT
- Title: Achievable rates for concatenated square Gottesman-Kitaev-Preskill codes
- Authors: Mahadevan Subramanian, Guo Zheng, Liang Jiang,
- Abstract summary: The Gottesman-Kitaev-Preskill (GKP) codes are known to achieve optimal rates under displacement noise and pure loss channels.<n>These results highlight the capability of concatenation-based GKP codes and provides new methods for constructing good GKP lattices.
- Score: 1.9265037496741413
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The Gottesman-Kitaev-Preskill (GKP) codes are known to achieve optimal rates under displacement noise and pure loss channels, which establishes theoretical foundations for its optimality. However, such optimal rates are only known to be achieved at a discrete set of noise strength with the current self-dual symplectic lattice construction. In this work, we develop a new coding strategy using concatenated continuous variable - discrete variable encodings to go beyond past results and establish GKP's optimal rate over all noise strengths. In particular, for displacement noise, the rate is obtained through a constructive approach by concatenating GKP codes with a quantum polar code and analog decoding. For pure loss channel, we prove the existence of capacity-achieving GKP codes through a random coding approach. These results highlight the capability of concatenation-based GKP codes and provides new methods for constructing good GKP lattices.
Related papers
- Logical channels in approximate Gottesman-Kitaev-Preskill error correction [0.0]
The GKP encoding is a top contender among bosonic codes for fault-tolerant quantum computation.<n>We analyze a variant of the GKP stabilizer measurement circuit using damped, approximate GKP states.<n>We show that SB decoding is suboptimal for finite-energy GKP states.
arXiv Detail & Related papers (2025-04-18T00:13:42Z) - Threshold Selection for Iterative Decoding of $(v,w)$-regular Binary Codes [84.0257274213152]
Iterative bit flipping decoders are an efficient choice for sparse $(v,w)$-regular codes.<n>We propose concrete criteria for threshold determination, backed by a closed form model.
arXiv Detail & Related papers (2025-01-23T17:38:22Z) - Performance and achievable rates of the Gottesman-Kitaev-Preskill code for pure-loss and amplification channels [2.955647071443854]
We analytically obtain the near-optimal performance of any Gottesman-Kitaev-Preskill code under pure loss and pure amplification.<n>Our results establish GKP code as the first structured bosonic code family that achieves the capacity of loss and amplification.
arXiv Detail & Related papers (2024-12-09T18:03:31Z) - Factor Graph Optimization of Error-Correcting Codes for Belief Propagation Decoding [62.25533750469467]
Low-Density Parity-Check (LDPC) codes possess several advantages over other families of codes.
The proposed approach is shown to outperform the decoding performance of existing popular codes by orders of magnitude.
arXiv Detail & Related papers (2024-06-09T12:08:56Z) - The Near-optimal Performance of Quantum Error Correction Codes [2.670972517608388]
We derive the near-optimal channel fidelity, a concise and optimization-free metric for arbitrary codes and noise.
Compared to conventional optimization-based approaches, the reduced computational cost enables us to simulate systems with previously inaccessible sizes.
We analytically derive the near-optimal performance for the thermodynamic code and the Gottesman-Kitaev-Preskill (GKP) code.
arXiv Detail & Related papers (2024-01-04T01:44:53Z) - Correcting biased noise using Gottesman-Kitaev-Preskill repetition code
with noisy ancilla [0.6802401545890963]
Gottesman-Kitaev-Preskill (GKP) code is proposed to correct small displacement error in phase space.
If noise in phase space is biased, square-lattice GKP code can be ancillaryd with XZZX surface code or repetition code.
We study the performance of GKP repetition codes with physical ancillary GKP qubits in correcting biased noise.
arXiv Detail & Related papers (2023-08-03T06:14:43Z) - Gaussian conversion protocol for heralded generation of qunaught states [66.81715281131143]
bosonic codes map qubit-type quantum information onto the larger bosonic Hilbert space.
We convert between two instances of these codes GKP qunaught states and four-foldsymmetric binomial states corresponding to a zero-logical encoded qubit.
We obtain GKP qunaught states with a fidelity of over 98% and a probability of approximately 3.14%.
arXiv Detail & Related papers (2023-01-24T14:17:07Z) - Neural Belief Propagation Decoding of Quantum LDPC Codes Using
Overcomplete Check Matrices [60.02503434201552]
We propose to decode QLDPC codes based on a check matrix with redundant rows, generated from linear combinations of the rows in the original check matrix.
This approach yields a significant improvement in decoding performance with the additional advantage of very low decoding latency.
arXiv Detail & Related papers (2022-12-20T13:41:27Z) - Finite Rate QLDPC-GKP Coding Scheme that Surpasses the CSS Hamming Bound [9.466536273518134]
We show how to exploit GottesmanKitaev-Preskill (GKP) code with generic quantum low-density parity-check (QLDPC) codes.
We also discuss new fundamental and practical questions that arise from this work on channel capacity under GKP analog information.
arXiv Detail & Related papers (2021-11-13T03:42:12Z) - Composably secure data processing for Gaussian-modulated continuous
variable quantum key distribution [58.720142291102135]
Continuous-variable quantum key distribution (QKD) employs the quadratures of a bosonic mode to establish a secret key between two remote parties.
We consider a protocol with homodyne detection in the general setting of composable finite-size security.
In particular, we analyze the high signal-to-noise regime which requires the use of high-rate (non-binary) low-density parity check codes.
arXiv Detail & Related papers (2021-03-30T18:02:55Z) - Plug-And-Play Learned Gaussian-mixture Approximate Message Passing [71.74028918819046]
We propose a plug-and-play compressed sensing (CS) recovery algorithm suitable for any i.i.d. source prior.
Our algorithm builds upon Borgerding's learned AMP (LAMP), yet significantly improves it by adopting a universal denoising function within the algorithm.
Numerical evaluation shows that the L-GM-AMP algorithm achieves state-of-the-art performance without any knowledge of the source prior.
arXiv Detail & Related papers (2020-11-18T16:40:45Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.