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arXiv:1909.09112 · Physical Review A

Hybrid quantum error correction in qubit architectures

Lasse Bjørn Kristensen, Morten Kjærgaard, Christian Kraglund Andersen, Nikolaj Thomas Zinner

Published Aug 3, 2023• 5 citations
arXivHTMLPDF

Abstract

Noise and errors are inevitable parts of any practical implementation of a quantum computer. As a result, large-scale quantum computation will require ways to detect and correct errors in quantum information. Here we present such a quantum error-correcting scheme for correcting the dominant phase and decay errors in superconducting qubit architectures using a hybrid approach combining autonomous correction based on engineered dissipation with traditional measurement-based quantum error correction. Using numerical simulations with realistic device parameters for superconducting circuits, we show that this scheme can achieve a five- to tenfold increase in storage time while using only six qubits for the encoding and two ancillary qubits for the operation of the autonomous correction, providing a potentially large reduction of qubit overhead compared to typical measurement-based error-correction schemes. Furthermore, the scheme relies on standard interactions and qubit driving available in most major quantum computing platforms, making it implementable in a wide range of architectures.

DOI
10.1103/physreva.108.022403

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Noise and errors are inevitable parts of any practical implementation of a quantum computer. As a result, large-scale quantum computation will require ways to detect and correct errors in quantum information. Here we present such a quantum error-correcting scheme for correcting the dominant phase and decay errors in superconducting qubit architectures using a hybrid approach combining autonomous correction based on engineered dissipation with traditional measurement-based quantum error correction. Using numerical simulations with realistic device parameters for superconducting circuits, we show that this scheme can achieve a five- to tenfold increase in storage time while using only six qubits for the encoding and two ancillary qubits for the operation of the autonomous correction, providing a potentially large reduction of qubit overhead compared to typical measurement-based error-correction schemes. Furthermore, the scheme relies on standard interactions and qubit driving available in most major quantum computing platforms, making it implementable in a wide range of architectures.
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.
Dissipative cat qubits are a promising physical platform for quantum computing, since their large noise bias can enable more hardware-efficient quantum error correction. In this work we theoretically study the long-term prospects of a hybrid cat-transmon quantum computing architecture where dissipative cat qubits play the role of data qubits, and error syndromes are measured using ancillary transmon qubits. The cat qubits’ noise bias enables more hardware-efficient quantum error correction, and the use of transmons allows for practical, high-fidelity syndrome measurement. While correction of the dominant cat Z errors with a repetition code has recently been demonstrated in experiment, here we show how the architecture can be scaled beyond a repetition code. In particular, we propose a cat-transmon entangling gate that enables the correction of residual cat X errors in a thin rectangular surface code, so that logical error can be arbitrarily suppressed by increasing code distance. We numerically estimate logical memory performance, finding significant overhead reductions in comparison to architectures without biased noise. For example, with current state-of-the-art coherence, physical error rates of 10 − 3 and noise biases in the range 10 3 – 10 4 are achievable. With this level of performance, the qubit overhead required to reach algorithmically relevant logical error rates with the cat-transmon architecture matches that of an unbiased-noise architecture with physical error rates in the range 10 − 5 – 10 − 4 .
Abstract We propose an autonomous quantum error correction scheme using squeezed cat (SC) code against excitation loss in continuous-variable systems. Through reservoir engineering, we show that a structured dissipation can stabilize a two-component SC while autonomously correcting the errors. The implementation of such dissipation only requires low-order nonlinear couplings among three bosonic modes or between a bosonic mode and a qutrit. While our proposed scheme is device independent, it is readily implementable with current experimental platforms such as superconducting circuits and trapped-ion systems. Compared to the stabilized cat, the stabilized SC has a much lower dominant error rate and a significantly enhanced noise bias. Furthermore, the bias-preserving operations for the SC have much lower error rates. In combination, the stabilized SC leads to substantially better logical performance when concatenating with an outer discrete-variable code. The surface-SC scheme achieves more than one order of magnitude increase in the threshold ratio between the loss rate κ 1 and the engineered dissipation rate κ 2 . Under a practical noise ratio κ 1 / κ 2 = 10 −3 , the repetition-SC scheme can reach a 10 −15 logical error rate even with a small mean excitation number of 4, which already suffices for practically useful quantum algorithms.
We propose a novel measurement-free scheme for stabilizing a spin-oscillator hybrid qubit via autonomous quantum error correction. The engineered Lindbladian renders the code space into an attractive steady-state subspace, realized by coupling the storage mode to a rapidly cooled bath through a controlled beam-splitter and spin-dependent displacement interactions. The continuous variable-discrete variable hybrid approach to autonomous quantum error correction preserves the hardware efficiency of conventional dissipation engineering while simplifying the required system-bath coupling. The construction is compatible with simple logical gates and leverages primitives already demonstrated in experimental platforms, such as trapped-ion systems, suggesting a practical route to hardware-efficient, noise-biased logical qubits without repeated syndrome measurements and feedforward.
Quantum computers require error correction to achieve universal quantum computing. However, current decoding of quantum error-correcting codes relies on classical computation, which is slower than quantum operations in superconducting qubits. This discrepancy makes the practical implementation of real-time quantum error correction challenging. In this work, we propose a decoding scheme that leverages the operations of the quantum circuit itself. Given a noisy quantum circuit AAA, we train a decoding quantum circuit BBB using syndrome measurements to identify the logical operators needed to correct errors in circuit AAA. The trained quantum circuit BBB can be deployed on quantum devices, such as superconducting qubits, to perform real-time decoding and error correction. Our approach is applicable to general quantum codes with multiple logical qubits and operates efficiently under various noise conditions, and the decoding speed matches the speed of the quantum circuits being corrected. We have conducted numerical experiments using surface codes up to distance 7 under circuit-level noise, demonstrating performance on par with the classical minimum-weight perfect matching algorithm. Interestingly, our method reveals that the traditionally classical task of decoding error-correcting codes can be accomplished without classical devices or measurements. This insight paves the way for the development of self-correcting quantum computers.
We can encode a qubit in the energy levels of a quantum system.Relaxation and other dissipation processes lead to decay of the fidelity of this stored information.Is it possible to preserve the quantum information for a longer time by introducing additional drives and dissipation?The existence of autonomous quantum error correcting codes answers this question in the positive.Nonetheless, discovering these codes for a real physical system, i.e., finding the encoding and the associated driving fields and bath couplings, remains a challenge that has required intuition and inspiration to overcome.In this work, we develop and demonstrate a computational approach based on adjoint optimization for discovering autonomous quantum error correcting codes given a Hamiltonian description of a physical system.We implement an optimizer that searches for a logical subspace and control parameters to better preserve quantum information.We demonstrate our method on a system of a harmonic oscillator coupled to a lossy qubit, and find that varying the Hamiltonian distance in Fock space-a proxy for the control hardware complexity-leads to discovery of different and new error correcting schemes.We discover what we call the √ 3 code, realizable with a Hamiltonian distance d = 2, and propose a hardware-efficient implementation based on superconducting circuits.