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arXiv:2302.13015 · International Conference on Communications

Performance Analysis of Quantum Error-Correcting Surface Codes over Asymmetric Channels

Lorenzo Valentini, Diego Forlivesi, Marco Chiani

Published May 28, 2023• 6 citations
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Abstract

One of the main challenge for an efficient implementation of quantum information technologies is how to counteract quantum noise. Quantum error correcting codes are therefore of primary interest for the evolution towards quantum computing and quantum Internet. We here analyze the performance of surface codes, one of the most important class for practical implementations, on both symmetric and asymmetric quantum channels. We derive approximate expressions, confirmed by simulations, to evaluate the performance of surface codes and of XZZX codes, and provide a metric to assess the advantage of codes with respect to uncoded systems. Our findings allow to characterize the performance by means of analytical formulas of surface codes, like, for example, the [[13, 1, 3]], the [[23, 1, 3/5]], the [[33, 1, 3/7]], and the [[41, 1, 5]] surface codes.

DOI
10.1109/icc45041.2023.10279096

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One of the main challenge for an efficient implementation of quantum information technologies is how to counteract quantum noise. Quantum error correcting codes are therefore of primary interest for the evolution towards quantum computing and quantum Internet. We here analyze the performance of surface codes, one of the most important class for practical implementations, on both symmetric and asymmetric quantum channels. We derive approximate expressions, confirmed by simulations, to evaluate the performance of surface codes and of XZZX codes, and provide a metric to assess the advantage of codes with respect to uncoded systems. Our findings allow to characterize the performance by means of analytical formulas of surface codes, like, for example, the [[13, 1, 3]], the [[23, 1, 3/5]], the [[33, 1, 3/7]], and the [[41, 1, 5]] surface codes.
Surface codes are versatile quantum error-correcting codes known for their planar geometry, making them ideal for practical implementations. While the original proposal used PauliXor PauliZoperators in a square structure, these codes can be improved by rotating the lattice or incorporating a mix of generators in the XZZX variant. However, a comprehensive theoretical analysis of the logical error rate for these variants has been lacking. To address this gap, we present theoretical formulas based on recent advancements in understanding the weight distribution of stabilizer codes. For example, over an asymmetric channel with asymmetryA= 10 and a physical error ratep→ 0, we observe that the logical error rate asymptotically approachespL→ 10p2for the rotated [[9, 1, 3]] XZZX code andpL→ 18.3p2for the [[13, 1, 3]] surface code. Additionally, we observe a particular behavior regarding rectangular lattices in the presence of asymmetric channels. Our findings demonstrate that implementing both rotation and XZZX modifications simultaneously can lead to suboptimal performance. Thus, in scenarios involving a rectangular lattice, it is advisable to avoid using both modifications simultaneously.
To advance the field of quantum computing, quantum error correction codes are essential to preserve and elaborate quantum information. Among the various candidates for near-term quantum error correction, surface codes stand out due to their structure and the availability of efficient decoding strategies. Performance assessments of these codes have been focused mainly on the qubit error probability, overlooking the impact of decoherence over time when decoders with different latencies are employed. In this paper, we present a simple framework to address this limitation, deriving performance metrics that incorporate the time complexity of the decoding process.
Performing large calculations with a quantum computer will likely require a fault-tolerant architecture based on quantum error-correcting codes. The challenge is to design practical quantum error-correcting codes that perform well against realistic noise using modest resources. Here we show that a variant of the surface code-the XZZX code-offers remarkable performance for fault-tolerant quantum computation. The error threshold of this code matches what can be achieved with random codes (hashing) for every single-qubit Pauli noise channel; it is the first explicit code shown to have this universal property. We present numerical evidence that the threshold even exceeds this hashing bound for an experimentally relevant range of noise parameters. Focusing on the common situation where qubit dephasing is the dominant noise, we show that this code has a practical, high-performance decoder and surpasses all previously known thresholds in the realistic setting where syndrome measurements are unreliable. We go on to demonstrate the favourable sub-threshold resource scaling that can be obtained by specialising a code to exploit structure in the noise. We show that it is possible to maintain all of these advantages when we perform fault-tolerant quantum computation.
Abstract Performing large calculations with a quantum computer will likely require a fault-tolerant architecture based on quantum error-correcting codes. The challenge is to design practical quantum error-correcting codes that perform well against realistic noise using modest resources. Here we show that a variant of the surface code—the XZZX code—offers remarkable performance for fault-tolerant quantum computation. The error threshold of this code matches what can be achieved with random codes (hashing) for every single-qubit Pauli noise channel; it is the first explicit code shown to have this universal property. We present numerical evidence that the threshold even exceeds this hashing bound for an experimentally relevant range of noise parameters. Focusing on the common situation where qubit dephasing is the dominant noise, we show that this code has a practical, high-performance decoder and surpasses all previously known thresholds in the realistic setting where syndrome measurements are unreliable. We go on to demonstrate the favourable sub-threshold resource scaling that can be obtained by specialising a code to exploit structure in the noise. We show that it is possible to maintain all of these advantages when we perform fault-tolerant quantum computation.
The necessity for quantum error correction arises from the need to safeguard quantum information from errors induced by decoherence and other noise forms. However, the optimal decoding of quantum error-correcting codes is a computationally challenging task. In our research, we introduce an ensemble decoder that amalgamates the advantages of various decoders to attain lower logical error rates and the capability to decode multiple errors. We employed statistical methodologies to allocate a specific error syndrome to the decoder with the highest likelihood of accurate decoding. We applied diverse variants of the Noise model to simulate the impact of noise on transmitted quantum states accurately. The efficacy of the ensemble decoder was assessed in both Symmetric and Asymmetric Noise Models. In the Symmetric Noise Model, bit-flip and phase-flip errors are presumed to have equal probabilities, while in the Asymmetric Noise Model, these probabilities can vary. The comparison aimed to evaluate the ensemble decoder's proficiency in rectifying these error types compared to traditional decoding techniques. Our results indicate that the ensemble decoder surpasses conventional decoders in the Symmetric Noise model, particularly for higher code distances. It is also apparent that augmenting the lattice size diminishes the logical error rate and that threshold and pseudo-threshold values escalate with incremental changes in noise asymmetry. The study's findings underscore the substantial potential of the ensemble decoder in quantum error correction and communication realms.
We introduce surface ZZZY codes, a novel family of quantum error-correcting codes designed for asymmetric channels. Derived from standard surface codes through tailored modification of generators, ZZZY codes can be decoded by the minimum weight perfect matching (MWPM) algorithm with a suitable pre-processing phase. The resulting decoder exploits the information provided by the modified generators without introducing additional complexity. ZZZY codes demonstrate a significant performance advantage over surface codes when increasing the channel asymmetry, while maintaining the same correction capability over depolarizing channel.