论文标题
补充Grover的搜索算法：振幅抑制实现
Complement Grover's Search Algorithm: An Amplitude Suppression Implementation
论文作者
论文摘要
Grover的搜索算法是量子算法的开创性进步，显示了对项目查询的二次加速。自从创建该算法以来，它已以各种方式使用，包括为通用电路准备特定状态。但是，随着所需项目数量的增加，进行查询的子过程的栅极复杂性也会增加。为了应对这种复杂性，得出了Grover搜索算法的扩展，其中查询的焦点是在不良项目上以抑制查询项目的幅度。为了显示功效，该算法是作为QAOA的子过程实现的，并应用于旅行推销员问题。为了进行比较，将结果与QAOA进行比较。
Grover's search algorithm was a groundbreaking advancement in quantum algorithms, displaying a quadratic speed-up of querying for items. Since the creation of this algorithm it has been utilized in various ways, including in preparing specific states for the general circuit. However, as the number of desired items increases so does the gate complexity of the sub-process that conducts the query. To counter this complexity, an extension of Grover's search algorithm is derived where the focus of the query is on the undesirable items in order to suppress the amplitude of the queried items. To display the efficacy the algorithm is implemented as a sub-process into QAOA and applied to a traveling salesman problem. For a basis of comparison, the results are compared against QAOA.
