Google Quantum AI Proves Fault Tolerant Quantum Computing is Possible
Google Quantum AI has just proven, beyond any reasonable doubt, that Fault-Tolerant Quantum Computing is possible.
For the first time ever, a logical qubit meets all criteria, demonstrating that Quantum Error Correction is effective.
Here is the link to the research paper.
Many challenges remain. Although Google might in principle achieve low logical error rates by scaling up our current processors, it would be resource intensive in practice. Extrapolating the projections in Fig. 1d, achieving a 1 in a million error rate would require a distance-27 logical qubit using 1457 physical qubits. Scaling up will also bring additional challenges in real-time decoding as the syndrome measurements per cycle increase quadratically with code distance. The repetition code experiments also identify a noise floor at an error rate of 1 in ten billion caused by correlated bursts of errors. Identifying and mitigating this error mechanism will be integral to running larger quantum algorithms.
However, quantum error correction also provides us exponential leverage in reducing logical errors with processor improvements. For example, reducing physical error rates by a factor of two would improve the distance-27 logical performance by four orders of magnitude, well into algorithmically-relevant error rates. They expect these overheads will reduce with advances in error
correction protocols and decoding. The purpose of quantum error correction is to enable large scale quantum algorithms. While this work focuses on building a robust memory, additional challenges will arise in logical computation. On the classical side, they must ensure that software elements including our calibration protocols, real-time decoders, and logical compilers can scale to the sizes and complexities needed to run multi-surface-code operations. With below- threshold surface codes, they have demonstrated processor performance that can scale in principle, but which they must now scale in practice.
Arxiv - Quantum error correction below the surface code threshold
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 Λ = 2.14 ± 0.02 when increasing the code distance by two, culminating in a 101-qubit distance-7 code with 0.143% ± 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 ± 0.3. We maintain below-threshold performance when decoding in real time, achieving an average decoder latency of 63 μs at distance-5 up to a million cycles, with a cycle time of 1.1 μs. 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 billion cycles. Our results present device performance that, if scaled, could realize the operational requirements of large scale fault-tolerant quantum algorithms.
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