Quantum computers are inherently noisy, and a crucial challenge for achieving large-scale, fault-tolerant quantum computing is to implement quantum error correction. A promising direction that has made rapid recent progress is to design hardware that has a specific noise profile, leading to a significantly higher threshold for noise with certain quantum error correcting codes. This Perspective focuses on erasure qubits, which enable hardware-efficient quantum error correction, by concatenating an inner code built-in to the hardware with an outer code. We focus on implementations of dual-rail encoded erasure qubits using superconducting qubits, giving an overview of recent developments in theory and simulation, and hardware demonstrators. We also discuss the differences between implementations; near-term applications using quantum error detection; and the open problems for developing this approach towards early fault-tolerant quantum computers.
Quantum computers are inherently noisy, and a crucial challenge for achieving large-scale, fault-tolerant quantum computing is to implement quantum error correction. A promising direction that has made rapid recent progress is to design hardware that has a specific noise profile, leading to a significantly higher threshold for noise with certain quantum error correcting codes. This Perspective focuses on erasure qubits, which enable hardware-efficient quantum error correction, by concatenating an inner code built-in to the hardware with an outer code. We focus on implementations of dual-rail encoded erasure qubits using superconducting qubits, giving an overview of recent developments in theory and simulation, and hardware demonstrators. We also discuss the differences between implementations; near-term applications using quantum error detection; and the open problems for developing this approach towards early fault-tolerant quantum computers.
Quantum error correction using erasure qubits offers higher fault-tolerant thresholds and improved scaling by converting dominant physical errors into detectable erasures. In superconducting circuits, erasure qubits can be constructed using the dual-rail approach, which, however, requires additional qubit-count overhead and tailored coupling elements. Here, we demonstrate a hardware-efficient scheme that operates transmon qutrits as erasure qubits, which is compatible with standard superconducting circuit-QED hardware. The logical states ∣0L⟩ and ∣1L⟩ are represented by the ground and second excited states, while the dominant relaxation errors can be detected via an ancilla qubit using a microwave-activated two-qutrit SWAP gate. We demonstrate a logical qubit T1 lifetime exceeding 500μs, post-selected with repeated mid-circuit erasure detection, which is ten times longer than the T1 time of the transmon physical qubit. Coherence times beyond 300μs are achieved using dynamical decoupling. Single-qubit gate operations reach average Clifford gate infidelity on the order of 10−4. We further demonstrate dual-purposing an ancilla qubit for both erasure detection and parity checking, showing heralded generation of Bell states between erasure qubits. These results suggest that mainstream architectures of transmon qubit arrays may already be capable of implementing erasure-based QEC strategies for hardware-efficient fault-tolerant quantum computing.
Abstract Quantum computers are inherently noisy, and a crucial challenge for achieving large-scale, fault-tolerant quantum computing is to implement quantum error correction (QEC). A promising direction that has made rapid recent progress is to design hardware that has a specific noise profile, leading to a significantly higher threshold for noise with certain quantum error correcting codes. This Perspective focuses on erasure qubits, which enable hardware-efficient QEC, by concatenating an inner code built-in to the hardware with an outer code. We focus on implementations of dual-rail encoded erasure qubits using superconducting qubits, giving an overview of recent developments in theory and simulation, and hardware demonstrators. We also discuss the differences between implementations; near-term applications using quantum error detection; and the open problems for developing this approach towards early fault-tolerant quantum computers.
Erasure qubits are beneficial for quantum error correction due to their relaxed threshold requirements. While dual-rail erasure qubits have been demonstrated with a strong error hierarchy in circuit quantum electrodynamics, biased-erasure qubits -- where erasures originate predominantly from one logical basis state -- offer further advantages. Here, we realize a hardware-efficient biased-erasure qubit encoded in the vacuum and two-photon Fock states of a single microwave cavity. The qubit exhibits an erasure bias ratio of over 265. By using a transmon ancilla for logical measurements and mid-circuit erasure detections, we achieve logical state assignment errors below 1% and convert over 99.3% leakage errors into detected erasures. After postselection against erasures, we achieve effective logical relaxation and dephasing rates of (6.2ms)−1 and (3.1ms)−1, respectively, which exceed the erasure error rate by factors of 31 and 15, establishing a strong error hierarchy within the logical subspace. These postselected error rates indicate a coherence gain of about 6.0 beyond the break-even point set by the best physical qubit encoded in the two lowest Fock states in the cavity. Moreover, randomized benchmarking with interleaved erasure detections reveals a residual logical gate error of 0.29%. This work establishes a compact and hardware-efficient platform for biased-erasure qubits, promising concatenations into outer-level stabilizer codes toward fault-tolerant quantum computation.
Erasure qubits offer a promising avenue toward reducing the overhead of quantum error correction (QEC) protocols. However, they require additional operations, such as erasure checks, that may add extra noise and increase the run-time of QEC protocols. To assess the benefits provided by erasure qubits, we focus on the performance of the surface code as a quantum memory. In particular, we analyze various erasure check schedules, find the correctable regions in the phase space of error parameters, and probe the subthreshold scaling of the logical error rate. We then consider a realization of erasure qubits in the superconducting hardware architectures via dual-rail qubits. We use the standard transmon-based implementation of the surface code as the performance benchmark. Our results indicate that QEC protocols with erasure qubits can outperform the ones with state-of-the-art transmons, even in the absence of precise information about the locations of erasure errors.
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.
Quantum error correction (QEC) represents the cornerstone technology for realizing fault-tolerant quantum computing, addressing the fundamental challenge of quantum state decoherence in noisy intermediate-scale quantum (NISQ) devices. This comprehensive review examines recent advances in QEC implementations from 2020-2024, spanning theoretical foundations to practical hardware demonstrations. We analyze the evolution from pioneering stabilizer codes to modern topological approaches, with particular emphasis on surface codes and low-density parity-check (LDPC) codes that have demonstrated below-threshold error correction in superconducting and trapped-ion systems. The paper provides a comparative analysis of classical and machine learning-based decoder algorithms, evaluating their performance through complexity analysis and threshold comparisons in real-time error correction scenarios. Through examination of breakthrough experiments by Google, IBM, Quantinuum, and emerging platforms, we assess the current state of fault-tolerant quantum computing and identify critical engineering challenges including correlated noise models, cryogenic control systems, and scalable logical gate implementations. Our quantitative analysis reveals that while significant progress has been made toward practical fault-tolerance thresholds, achieving the resource efficiency and reliability required for large-scale quantum computation remains challenging. We provide detailed resource estimates for key applications including Shor's algorithm and optimization problems, along with analysis of industry roadmaps toward thousand-logical-qubit systems. This review serves as a comprehensive guide for researchers and engineers working toward the next generation of fault-tolerant quantum computers, with particular focus on information-theoretic perspectives relevant to quantum information entropy and syndrome processing.