Quantum computers promise computational advantages for many important problems across various application domains. Unfortunately, physical quantum devices are highly susceptible to errors that limit us from running most of these quantum applications. Quantum Error Correction (QEC) codes are required to implement Fault-Tolerant Quantum Computers (FTQC) on which computations can be performed without encountering errors. Error decoding is a critical component of quantum error correction and is responsible for transforming a set of qubit measurements generated by the QEC code, called the syndrome, into error locations and error types. For the feasibility of implementation, error decoders must not only identify errors with high accuracy, but also be fast and scalable to a large number of qubits. Unfortunately, most of the prior works on error decoding have focused primarily only on the accuracy and have relied on software implementations that are too slow to be of practical use. Furthermore, these studies only look at designing a single decoder and do not analyze the challenges involved in scaling the storage and bandwidth requirements when performing error correction in large systems with thousands of qubits.In this paper, we present AFS, an accurate, fast, and scalable decoder architecture that is designed to operate in the context of systems with hundreds of logical qubits. We present the hardware implementation of AFS, which is based on the Union Find decoding algorithm and employs a three-stage pipelined design. AFS provides orders of magnitude higher accuracy compared to recent SFQ-based hardware decoders (logical error rate of 6×10−10for physical error rate of 10−3) and low decoding latency (42ns on average), while being robust to measurement errors introduced while extracting syndromes during the QEC cycles. We also reduce the amount of decoding hardware required to perform QEC simultaneously on all the logical qubits by co-designing the micro-architecture across multiple decoding units. Our proposed Conjoined-Decoder Architecture (CDA) reduces the storage overhead by 70% (10MB to 2.8MB). Finally, we reduce the bandwidth overheads required to transmit syndromes from the qubits to the decoders by exploiting the sparsity in the syndromes and compressing the data. Our proposed Syndrome Compression reduces the bandwidth requirement by 30x, on an average.

Quantum LDPC codes are a promising direction for low overhead quantum computing. In this paper, we propose a generalization of the Union-Find decoder as a decoder for quantum LDPC codes. We prove that this decoder corrects all errors with weight up to$An^\alpha $for some$A, \alpha > 0$, where$n$is the code length, for different classes of quantum LDPC codes such as toric codes and hyperbolic codes in any dimension$D \geq 3$and quantum expander codes. To prove this result, we introduce a notion of covering radius which measures the spread of an error from its syndrome. We believe this notion could find application beyond the decoding problem. We also perform numerical simulations, which show that our Union-Find decoder outperforms the belief propagation decoder in the low error rate regime in the case of a quantum LDPC code with length 3600.

Extensive quantum error correction is necessary in order to perform a useful computation on a noisy quantum computer. Moreover, quantum error correction must be implemented based on imperfect parity check measurements that may return incorrect outcomes or inject additional faults into the qubits. To achieve fault-tolerant error correction, Shor proposed to repeat the sequence of parity check measurements until the same outcome is observed sufficiently many times. Then, one can use this information to perform error correction. A basic implementation of this fault tolerance strategy requires$\Omega (r d^{2})$parity check measurements for a distance-$d$code defined by$r$parity checks. For some specific highly structured quantum codes, Bombin has shown that single-shot fault-tolerant quantum error correction is possible using only$r$measurements. In this work, we consider a phenomenological noise model for parity check measurements assuming that each bit of a codeword and the measurement outcome suffer from independent bit flips with some error rate$p$. For this model, we demonstrate that fault-tolerant quantum error correction can be achieved using$O(d \log (d))$measurements for any code with distance$d \geq \Omega (n^\alpha)$for some constant$\alpha > 0$. Moreover, we prove the existence of a sub-single-shot fault-tolerant quantum error correction scheme using fewer than$r$measurements. In some cases, the number of parity check measurements required for fault-tolerant quantum error correction is exponentially smaller than the number of parity checks defining the code. The short measurement sequences constructed generally have high weight and our phenomenological noise model is not realistic in this regime. Our error correction strategy could find applications to small codes and LDPC codes if one can manage to keep the weight of the measured parity checks low.

We propose a simple decoding algorithm for CSS codes taking into account the correlations between the X part and the Z part of the error. Applying this idea to surface codes, we derive an improved version of the perfect matching decoding algorithm which uses these X/Z correlations.

The family of hyperbolic surface codes is one of the rare families of quantum LDPC codes with non-zero rate and unbounded minimum distance. First, we introduce a family of hyperbolic color codes. This produces a new family of quantum LDPC codes with non-zero rate and with minimum distance logarithmic in the blocklength. Second, we show that the parameters [[n, k, d]] of surface codes and color codes satisfy kd2≤ C(log k)2n, where C is a constant that depends only on the row weight of the parity-check matrix. Our results prove that the best asymptotic minimum distance of LDPC surface codes and color codes with non-zero rate is logarithmic in the length.

We study a construction of quantum LDPC codes proposed by MacKay, Mitchison, and Shokrollahi. It is based on the Cayley graph of \BBF2ntogether with a set of generators regarded as the columns of the parity-check matrix of a classical code. We give a general lower bound on the minimum distance of the quantum code in O(dn2) where d is the minimum distance of the classical code. This bound is logarithmic in the blocklength 2nof the quantum code. When the classical code is the [n,1,n] repetition code, we are able to compute the exact parameters of the associated quantum code which are [[2n, 2[(n+1)/2], 2[(n-1)/2]]].

We study a construction of Quantum LDPC codes proposed by MacKay, Mitchison and Shokrollahi in the draft [6]. It is based on the Cayley graph of F2ntogether with a set of generators regarded as the columns of the parity-check matrix of a classical code. We give a general lower bound on the minimum distance of the quantum code in O(dn2) where d is the minimum distance of the classical code. When the classical code is the [n, 1, n] repetition code, we are able to compute the exact parameters of the associated quantum code which are [[2n-1, 2 n/2, 2 n/2-1]].

We are interested in percolation for a family of self-dual tilings of the hyperbolic plane. We achieve an upper bound on the critical probability for these tilings by taking appropriate finite quotients and associating them with a family of quantum CSS codes. We then relate the probability of percolation to the probability of a decoding error for these codes on the quantum erasure channel.