Quantum error correction below the surface code threshold

TL;DR

This paper demonstrates quantum surface code memories operating below the error threshold, achieving significant error suppression, real-time decoding, and surpassing physical qubit lifetimes, advancing towards scalable fault-tolerant quantum computing.

Contribution

The work presents the first implementation of surface code memories below the threshold with real-time decoding and detailed performance analysis, including error suppression and lifetime improvements.

Findings

Logical error rate suppressed by a factor of 2.14 with increased code distance

Achieved a 0.143% error per cycle in a 101-qubit distance-7 code

Logical memory exceeds physical qubit lifetime by a factor of 2.4

Abstract

Quantum error correction provides a path to reach practical quantum computing by combining multiple physical qubits into a logical qubit, where the logical error rate is suppressed exponentially as more qubits are added. However, this exponential suppression only occurs if the physical error rate is below a critical threshold. In this work, we present two surface code memories operating below this threshold: a distance-7 code and a distance-5 code integrated with a real-time decoder. The logical error rate of our larger quantum memory is suppressed by a factor of $\Lambda$ = 2.14 $\pm$ 0.02 when increasing the code distance by two, culminating in a 101-qubit distance-7 code with 0.143% $\pm$ 0.003% error per cycle of error correction. This logical memory is also beyond break-even, exceeding its best physical qubit's lifetime by a factor of 2.4 $\pm$ 0.3. We maintain below-threshold performance when decoding in real time, achieving an average decoder latency of 63 $\mu$s at distance-5 up to a million cycles, with a cycle time of 1.1 $\mu$s. To probe the limits of our error-correction performance, we run repetition codes up to distance-29 and find that logical performance is limited by rare correlated error events occurring approximately once every hour, or 3 $\times$ 10$^9$ cycles. Our results present device performance that, if scaled, could realize the operational requirements of large scale fault-tolerant quantum algorithms.