Biased Gottesman-Kitaev-Preskill repetition code
Matthew P. Stafford, Nicolas C. Menicucci

TL;DR
This paper demonstrates that a biased GKP repetition code with weight-two stabilizers can achieve high fault-tolerance thresholds and reduce logical error rates, offering a simpler alternative for quantum error correction in continuous-variable systems.
Contribution
It introduces a GKP-based repetition code with biasing that outperforms surface codes in threshold and simplifies decoding, using only weight-two stabilizers.
Findings
Threshold of σ=0.599 for noise standard deviation.
Significant error rate reductions with moderate bias and ≤9 data modes.
Achieves fault-tolerance with simple weight-two stabilizer measurements.
Abstract
Continuous-variable quantum computing architectures based upon the Gottesmann-Kitaev-Preskill (GKP) encoding have emerged as a promising candidate because one can achieve fault-tolerance with a probabilistic supply of GKP states and Gaussian operations. Furthermore, by generalising to rectangular-lattice GKP states, a bias can be introduced and exploited through concatenation with qubit codes that show improved performance under biasing. However, these codes (such as the XZZX surface code) still require weight-four stabiliser measurements and have complex decoding requirements to overcome. In this work, we study the code-capacity behaviour of a rectangular-lattice GKP encoding concatenated with a repetition code under an isotropic Gaussian displacement channel. We find a numerical threshold of for the noise's standard deviation, which outperforms the biased GKP planar…
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Taxonomy
TopicsAdvanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices · Quantum Computing Algorithms and Architecture
