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arXiv:2504.21845 · IEEE International Symposium on Information Theory (ISIT)

On the Efficacy of the Peeling Decoder for the Quantum Expander Code

Jefrin Sharmitha Prabhu, Abhinav Vaishya, Shobhit Bhatnagar, Aryaman Manish Kolhe, V. Lalitha, P. Vijay Kumar

Published Jun 22, 2025• 2 citations
arXivHTMLPDF

Abstract

The problem of recovering from qubit erasures has recently gained attention as erasures occur in many physical systems such as photonic systems, trapped ions, superconducting qubits and circuit quantum electrodynamics. While several linear-time decoders for error correction are known, their errorcorrecting capability is limited to half the minimum distance of the code, whereas erasure correction allows one to go beyond this limit. As in the classical case, stopping sets pose a major challenge in designing efficient erasure decoders for quantum LDPC codes. In this paper, we show through simulation, that an attractive alternative here, is the use of quantum expander codes in conjunction with the peeling decoder that has linear complexity. We also discuss additional techniques including small-set-flip decoding, that can be applied following the peeling operation, to improve decoding performance and their associated complexity.

DOI
10.1109/isit63088.2025.11195550

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The problem of recovering from qubit erasures has recently gained attention as erasures occur in many physical systems such as photonic systems, trapped ions, superconducting qubits and circuit quantum electrodynamics. While several linear-time decoders for error correction are known, their errorcorrecting capability is limited to half the minimum distance of the code, whereas erasure correction allows one to go beyond this limit. As in the classical case, stopping sets pose a major challenge in designing efficient erasure decoders for quantum LDPC codes. In this paper, we show through simulation, that an attractive alternative here, is the use of quantum expander codes in conjunction with the peeling decoder that has linear complexity. We also discuss additional techniques including small-set-flip decoding, that can be applied following the peeling operation, to improve decoding performance and their associated complexity.
Quantum low-density parity-check (qLDPC) codes are an important component in the quest for quantum fault tolerance. Dramatic recent progress on qLDPC codes has led to constructions which are asymptotically good, and which admit linear-time decoders to correct errors affecting a constant fraction of codeword qubits. These constructions, while theoretically explicit, rely on inner codes with strong properties only shown to exist by probabilistic arguments, resulting in lengths that are too large to be practically relevant. In practice, the surface/toric codes, which are the product of two repetition codes, are still often the qLDPC codes of choice. A previous construction of qLDPC codes based on the lifted product of an expander-based classical LDPC code with a repetition code (Panteleev and Kalachev, 2020) achieved a near-linear distance, and avoids the need for such intractable inner codes. Our main result is an efficient decoding algorithm for these codes that corrects a near-linear number of adversarial errors. En route, we give a similar algorithm for the hypergraph product version these codes, which are simpler but have distance growing only as the square root of the block length. Our decoding algorithms leverage the fact that the codes we consider are quasi-cyclic, meaning that they respect a cyclic group symmetry. Since the repetition code is not based on expanders, previous approaches to decoding expander-based qLDPC codes, which typically worked by greedily flipping code bits to reduce some potential function, do not apply in our setting. Instead, we reduce our decoding problem (in a black-box manner) to that of decoding classical expander-based LDPC codes under noisy parity-check syndromes. For completeness, we also include a treatment of such classical noisy-syndrome decoding that is sufficient for our application to the quantum setting.
We introduce a new erasure decoder that applies to arbitrary quantum LDPC codes. Dubbed the cluster decoder, it generalizes the decomposition idea of Vertical-Horizontal (VH) decoding introduced by Connolly et al. in 2022. Like the VH decoder, the idea is to first run the peeling decoder and then post-process the resulting stopping set. The cluster decoder breaks the stopping set into a tree of clusters, which can be solved sequentially via Gaussian Elimination. By allowing clusters of unconstrained size, this decoder achieves maximum-likelihood (ML) performance with reduced complexity compared with full Gaussian Elimination. When Gaussian Elimination is applied only to clusters whose sizes are less than a constant, the performance is degraded, but the complexity becomes linear in the block length. Our simulation results show that, for hypergraph product codes, the cluster decoder with constant cluster size achieves near-ML performance similar to VH decoding in the low-erasure-rate regime. For the general quantum LDPC codes we studied, the cluster decoder can be used to estimate the ML performance curve with reduced complexity over a wide range of erasure rates.
In order to build a large scale quantum computer, one must be able to correct errors extremely fast. We design a fast decoding algorithm for topological codes to correct for Pauli errors and erasure and combination of both errors and erasure. Our algorithm has a worst case complexity of O ( n α ( n ) ) , where n is the number of physical qubits and α is the inverse of Ackermann's function, which is very slowly growing. For all practical purposes, α ( n ) ≤ 3 . We prove that our algorithm performs optimally for errors of weight up to ( d − 1 ) / 2 and for loss of up to d − 1 qubits, where d is the minimum distance of the code. Numerically, we obtain a threshold of 9.9 % for the 2d-toric code with perfect syndrome measurements and 2.6 % with faulty measurements.
Fault tolerant quantum computation is a technique to perform reliable quantum computation using noisy components. In this context, quantum error correcting codes are used to keep the amount of errors under a sustainable threshold. One of the main problems of this field is to determine the minimum cost, in terms of memory and time, which is needed in order to transform an ideal quantum computation into a fault-tolerant one. In this PhD thesis, we show that the family of quantum expander codes and the small-set-flip decoder can be used in the construction of ref. [arXiv:1310.2984] to produce a fault-tolerant quantum circuit with constant space overhead. The error correcting code family and the decoder that we study has been introduced in ref. [arXiv:1504.00822] where an adversarial error model was examined. Based on the results of this article, we analyze quantum expander codes subjected to a stochastic error model which is relevant for fault-tolerant quantum computation [arXiv:1711.08351], [arXiv:1808.03821]. In addition, we show that the decoding algorithm can be parallelized to run in constant time. This is very relevant to prevent errors from accumulating while the decoding algorithm is running. Beyond the theoretical results described above, we perform a numerical analysis of quantum expander codes to measure their performance in practice [arXiv:1810.03681]. The error model used during these simulations generates X and Z type errors on the qubits with an independent and identically distributed probability distribution. Our results are promising because they reveal that these constant rate codes have a decent threshold and good finite length performance.
The overhead of quantum error correction (QEC) poses a major bottleneck for realizing fault-tolerant computation. To reduce this overhead, we exploit the idea of erasure qubits, relying on an efficient conversion of the dominant noise into erasures at known locations. We start by introducing a formalism for QEC schemes with erasure qubits and express the corresponding decoding problem as a matching problem. Then, we propose and optimize QEC schemes based on erasure qubits and the recently introduced Floquet codes. Our schemes are well suited for superconducting circuits, being compatible with planar layouts. We numerically estimate the memory thresholds for the circuit noise model that includes spreading (via entangling operations) and imperfect detection of erasures. Our results demonstrate that, despite being slightly more complex, QEC schemes based on erasure qubits can significantly outperform standard approaches.