Order-of-magnitude extension of qubit lifetimes with a decoherence-free subspace quantum error correction code
Shival Dasu, Ben Criger, Foltz, Cameron, Justin A. Gerber, C. N. Gilbreth, Kevin Gilmore, C. A. Holliman, Nathan Lysne, Alistair R. Milne, Daichi Okuno, Grahame Vittorini, David Hayes
Constructing an efficient and robust quantum memory is central to the challenge of engineering feasible quantum computer architectures. Quantum error correction codes can solve this problem in theory, but without careful design it can introduce daunting requirements that call for machines many orders of magnitude larger than what is available today. Bringing these requirements down can often be achieved by tailoring the codes to mitigate the specific forms of noise known to be present. Using a Quantinuum H1 quantum computer, we report on a robust quantum memory design using a concatenated code, with the low-level code designed to mitigate the dominant source of memory error, and a higher-level error correction scheme to enable robust computation. The resulting encoding scheme, known as a decoherence-free subspace quantum error correction code, is characterized for long probe times, and shown to extend the memory time by over an order of magnitude compared to physical qubits.
Constructing an efficient and robust quantum memory is central to the challenge of engineering feasible quantum computer architectures. Quantum error correction codes can solve this problem in theory, but without careful design it can introduce daunting requirements that call for machines many orders of magnitude larger than what is available today. Bringing these requirements down can often be achieved by tailoring the codes to mitigate the specific forms of noise known to be present. Using a Quantinuum H1 quantum computer, we report on a robust quantum memory design using a concatenated code, with the low-level code designed to mitigate the dominant source of memory error, and a higher-level error correction scheme to enable robust computation. The resulting encoding scheme, known as a decoherence-free subspace quantum error correction code, is characterized for long probe times, and shown to extend the memory time by over an order of magnitude compared to physical qubits.
Quantum error-correcting codes (QECCs) and decoherence-free subspace (DFS) codes provide active and passive means, respectively, to address certain types of errors that arise during quantum computation. The latter technique is suitable to correct correlated errors with certain symmetries and the former to correct independent errors. The concatenation of a QECC and a DFS code results in a degenerate code that splits into actively and passively correcting parts, with the degeneracy impacting either part, leading to degenerate errors as well as degenerate stabilizer operators. The concatenation of the two types of code can aid universal fault-tolerant quantum computation when a mix of correlated and independent errors is encountered. In particular, we show that for sufficiently strongly correlated errors, the concatenation with the DFS as the inner code provides better entanglement fidelity, whereas for sufficiently independent errors, the concatenation with the QECC as the inner code is preferable. As illustrative examples, we examine in detail the concatenation of a two-qubit DFS code and a three-qubit repetition code or five-qubit Knill-Laflamme code, under independent and correlated errors.
This paper presents the design and theoretical framework for a single-bit quantum error correction memory unit based on the principles of quantum error correction. The core claim is to construct a fault-tolerant memory unit for storing quantum information reliably. The proposed unit utilizes a multi-party quantum error correction coding scheme coupled with an error decoding system to mitigate the effects of decoherence and noise on individual qubits. The key innovation lies in the efficient implementation of quantum error correction at the single-qubit level, addressing a critical bottleneck in quantum computing. The theoretical framework details the encoding and decoding processes, emphasizing the real-time feedback mechanism for sustained quantum state preservation. Mathematical formulations are presented to illustrate the operation of the unit, including the error correction codes and the decoding algorithms. The unit's design offers a pathway toward scalable quantum memory solutions, crucial for advanced quantum computation and quantum communication protocols.
It was shown recently [D. A. Lidar et al., Phys. Rev. Lett. 81, 2594 (1998)] that within the framework of the semigroup Markovian master equation, decoherence-free (DF) subspaces exist which are stable to first order in time to a perturbation. Here this result is extended to the non-Markovian regime and generalized. In particular, it is shown that within both the semigroup and the non-Markovian operator sum representation, DF subspaces are stable to all orders in time to a symmetry-breaking perturbation. DF subspaces are thus ideal for quantum memory applications. For quantum computation, however, the stability result does not extend beyond the first order. Thus, to perform robust quantum computation in DF subspaces, they must be supplemented with quantum error correcting codes.
Concatenating quantum error correction codes scales error correction capability by driving logical error rates down double-exponentially across levels. However, the noise structure shifts under concatenation, making it hard to choose an optimal code sequence. We automate this choice by estimating the effective noise channel after each level and selecting the next code accordingly. In particular, we use learning-based methods to tailor small, non-additive encoders when the noise exhibits sufficient structure, then switch to standard codes once the noise is nearly uniform. In simulations, this level-wise adaptation achieves a target logical error rate with far fewer qubits than concatenating stabilizer codes alone--reducing qubit counts by up to two orders of magnitude for strongly structured noise. Therefore, this hybrid, learning-based strategy offers a promising tool for early fault-tolerant quantum computing.
This paper presents a novel design for a quantum storage system based on quantum error-correcting codes. The primary goal is to enhance the storage capacity and reliability of quantum storage devices, which are fundamental to the advancement of quantum computing. The proposed architecture leverages the principles of quantum error correction, specifically utilizing low-density parity-check (LDPC) codes, to mitigate the effects of decoherence and other sources of quantum noise. The design incorporates redundancy through the encoding of multiple logical qubits within a physical qubit ensemble, enabling the detection and correction of errors without compromising the integrity of the stored quantum information. The performance analysis demonstrates the potential for significant improvements in storage fidelity and the ability to store a larger number of quantum bits compared to traditional, uncorrected quantum storage approaches. The design addresses key challenges in quantum storage, including error mitigation and data preservation, contributing to the realization of scalable and reliable quantum computing systems.
Quantum error correction is expected to be essential in large-scale quantum technologies. However, the substantial overhead of qubits it requires is thought to greatly limit its utility in smaller, near-term devices. Here we introduce a new family of special-purpose quantum error-correcting codes that offer an exponential reduction in overhead compared to the usual repetition code. They are tailored for a common and important source of decoherence in current experiments, whereby a register of qubits is subject to phase noise through coupling to a common fluctuator, such as a resonator or a spin defect. The smallest instance encodes one logical qubit into two physical qubits, and corrects decoherence to leading-order using a constant number of one- and two-qubit operations. More generally, while the repetition code on n qubits corrects errors to order t^{O(n)}, with t the time between recoveries, our codes correct to order t^{O(2^{n})}. Moreover, they are robust to model imperfections in small- and intermediate-scale devices, where they already provide substantial gains in error suppression. As a result, these hardware-efficient codes open a potential avenue for useful quantum error correction in near-term, pre-fault tolerant devices.