2020/04/01 by Lisa Hänggli, Margret Heinze, Robert Koenig +1 · 45 citations
Computer Science · Mathematics · Physics and Astronomy · #Algorithm #Artificial intelligence #Code (set theory) #Combinatorics #Computer science #Decoding methods #Image (mathematics) #Mathematics #Noise (video) #Physics #Quantum #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #Quantum and electron transport phenomena #Quantum computer #Quantum error correction #Quantum mechanics #Qubit #Set (abstract data type) #Sigma #Topology (electrical circuits) #Toric code #quant-ph
paper · pdf · doi:10.1103/physreva.102.052408
published in Physical Review A 102(5) (American Physical Society) · 30 pages, 12 figures
arxiv created 2020/04/01 · openalex created_date 2020/04/10 · openalex publication_date 2020/11/10 · arxiv updated 2020/11/18 · openalex updated_date 2026/08/05
We study the code obtained by concatenating the standard single-mode Gottesman-Kitaev-Preskill (GKP) code with the surface code. We show that the noise tolerance of this surface--GKP code with respect to (Gaussian) displacement errors improves when a single-mode squeezing unitary is applied to each mode, assuming that the identification of quadratures with logical Pauli operators is suitably modified. We observe noise-tolerance thresholds of up to \ensuremathσ\ensuremath≈0.58 shift-error standard deviation when the surface code is decoded without using GKP syndrome information. In contrast, prior results by K. Fukui, A. Tomita, A. Okamoto, and K. Fujii, High-Threshold Fault-Tolerant Quantum Computation with Analog Quantum Error Correction, Phys. Rev. X 8, 021054 (2018) and C. Vuillot, H. Asasi, Y. Wang, L. P. Pryadko, and B. M. Terhal, Quantum error correction with the toric Gottesman-Kitaev-Preskill code, Phys. Rev. A 99, 032344 (2019) report a threshold between \ensuremathσ\ensuremath≈0.54 and \ensuremathσ\ensuremath≈0.55 for the standard (toric, respectively) surface--GKP code. The modified surface--GKP code effectively renders the mode-level physical noise asymmetric, biasing the logical-level noise on the GKP qubits. The code can thus benefit from the resilience of the surface code against biased noise. We use the approximate maximum likelihood decoding algorithm of S. Bravyi, M. Suchara, and A. Vargo, Efficient algorithms for maximum likelihood decoding in the surface code, Phys. Rev. A 90, 032326 (2014) to obtain our threshold estimates. Throughout, we consider an idealized scenario where measurements are noiseless and GKP states are ideal. Our paper demonstrates that Gaussian encodings of individual modes can enhance concatenated codes.