论文标题
分析超导量子处理器上变异量子保理的性能
Analyzing the Performance of Variational Quantum Factoring on a Superconducting Quantum Processor
论文作者
论文摘要
在近期，混合量子古典算法具有胜过经典方法的巨大潜力。了解这两个计算范式在串联中的工作方式对于识别该混合算法可以提供量子优势的领域至关重要。在这项工作中，我们通过实施变分量子保理（VQF）算法来研究一种基于QAOA的量子优化算法。我们使用超导量子处理器进行实验演示，并研究量子资源（量子数和电路深度的数量）之间的权衡，并成功地将给定的两次分配得分。在我们的实验中，使用QAOA ANSATZ分别将整数1099551473989、3127和6557分别使用3、4和5 QUBITS，最多具有8层，我们能够确定给定实例的最佳电路层，以最大程度地提高成功的可能性。此外，我们证明了不同噪声源对QAOA性能的影响，并揭示了由量子位之间的残留ZZ耦合引起的连贯误差，这是超导量子处理器中误差的主要源。
In the near-term, hybrid quantum-classical algorithms hold great potential for outperforming classical approaches. Understanding how these two computing paradigms work in tandem is critical for identifying areas where such hybrid algorithms could provide a quantum advantage. In this work, we study a QAOA-based quantum optimization algorithm by implementing the Variational Quantum Factoring (VQF) algorithm. We execute experimental demonstrations using a superconducting quantum processor and investigate the trade-off between quantum resources (number of qubits and circuit depth) and the probability that a given biprime is successfully factored. In our experiments, the integers 1099551473989, 3127, and 6557 are factored with 3, 4, and 5 qubits, respectively, using a QAOA ansatz with up to 8 layers and we are able to identify the optimal number of circuit layers for a given instance to maximize success probability. Furthermore, we demonstrate the impact of different noise sources on the performance of QAOA and reveal the coherent error caused by the residual ZZ-coupling between qubits as a dominant source of error in the superconducting quantum processor.
