在量子计算硬件上运行复杂算法将需要使用逻辑量子比特，即以允许检测和纠正错误的方式将多个硬件量子比特链接在一起。一般来说，为每个逻辑量子比特分配的硬件量子比特越多，识别错误的几率就越大。但鉴于硬件量子比特容易出错，增加更多硬件量子比特也会增加发生错误的概率。如果硬件错误率过高，扩大逻辑量子比特只会让情况变得更糟。
Running complicated algorithms on quantum computing hardware is going to require the use of logical qubits, where collections of hardware qubits are linked together in ways that allow errors to be detected and corrected. In general, the more hardware qubits you dedicate to each logical qubit, the better the chances are of identifying errors. But, given that the hardware qubits are prone to errors, adding more of them also increases the probability that errors will occur. If the hardware error rate is too high, then growing the logical qubit will only make matters worse.
幸运的是，多家公司已展示出错误率不太高的硬件。多项演示表明，逻辑量子比特已超越盈亏平衡点，即增加量子比特能提升性能。问题在于这种改善并不显著。要将错误率降低到运行复杂算法所需的水平，必须为每个逻辑量子比特增加完全不切实际数量的量子比特。
Fortunately, several companies have demonstrated hardware where the error rate is not too high. Several demonstrations show logical qubits are beyond the breakeven point, where adding more qubits improves performance. The problem is that the improvement isn't very dramatic. To lower error rates to levels we'll need to run complex algorithms, we'd have to add a completely impractical number of qubits to each logical qubit.
周一，Quantinuum 宣布其当前一代硬件能够远超盈亏平衡点进行扩展。逻辑量子比特规模每提升一级，其某些性能指标就提高 10 倍以上。
On Monday, Quantinuum announced that its current generation of hardware is capable of scaling well beyond the breakeven point. Each step up in the size of logical qubits improved some measures of their performance by a factor of over 10.