论文标题
NISQ搜索算法的细分相位甲骨文
Subdivided Phase Oracle for NISQ Search Algorithms
论文作者
论文摘要
由于嘈杂的中间量子量子（NISQ）机器迅速累积了错误，因此我们需要新的方法来设计NISQ感知算法并评估其性能。在理想情况下（例如较低的成功概率），具有不太理想的特征的算法实际上可能优于其在现有硬件上的理想对应物。我们提出了对Grover算法的改编，将相位翻转成段以取代数字计数器和复杂的相位翻转决策逻辑。我们应用了这种方法在稀疏图中获得最佳切割问题的最佳解决方案，利用具有残留相移的多控制，类似Toffoli的门。我们在IBM Q处理器上实现了该算法，并成功地解决了一个5节点最大切割问题，并证明了四个量子位上的振幅扩增。这种方法对于一系列问题将很有用，并且可能会缩短达到量子优势的时间。
Because noisy, intermediate-scale quantum (NISQ) machines accumulate errors quickly, we need new approaches to designing NISQ-aware algorithms and assessing their performance. Algorithms with characteristics that appear less desirable under ideal circumstances, such as lower success probability, may in fact outperform their ideal counterparts on existing hardware. We propose an adaptation of Grover's algorithm, subdividing the phase flip into segments to replace a digital counter and complex phase flip decision logic. We applied this approach to obtaining the best solution of the MAX-CUT problem in sparse graphs, utilizing multi-control, Toffoli-like gates with residual phase shifts. We implemented this algorithm on IBM Q processors and succeeded in solving a 5-node MAX-CUT problem, demonstrating amplitude amplification on four qubits. This approach will be useful for a range of problems, and may shorten the time to reaching quantum advantage.
