Quantum error correction can constantly recalibrate a processor
摘要
量子计算面临诸多挑战，除了制造足够多高质量硬件量子比特等宏观问题外，校准也是一个关键难题。由于超导量子比特等硬件存在个体差异，需要通过校准测试微波脉冲的最佳频率和振幅以降低错误率。但常规校准无法在计算过程中进行，导致长时间复杂算法中出现漂移问题。谷歌发现可以利用纠错数据同时进行校准，为量子处理器的持续优化提供了新思路。
There are some obvious big picture issues that stand between us and useful quantum computing. Issues like whether we can make enough high-quality hardware qubits to connect into the error-corrected logical qubits we need, and how we generate the states needed to perform universal computation on those logical qubits. But there are also many less prominent challenges that will need to be solved before we can perform calculations.
One of those challenges, which only affects some types of hardware, is calibration. For devices we manufacture, like superconducting qubits, there are always subtle variations among individual qubits. (This is not true when we use something like an atom to hold the qubit, but the lasers that control them can drift.) As a result, this hardware is put through a process called calibration, where we test different frequencies and amplitudes of the microwave pulses that control them to find the combination that produces the lowest error rates, and then save those settings for use in calculations.
However, you can't perform the typical calibration process while e you're doing calculations, which means drift becomes an issue for long and complicated algorithms. Google, though, has figured out that it's possible to do calibration using the same data that's used for error correction.
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