论文标题
基于粒子群优化算法的量子门的近似分离和CNOT的分离实验
Approximate separation of quantum gates and separation experiments of CNOT based on Particle Swarm Optimization algorithm
论文作者
论文摘要
Ying想象使用两个或多个小容量量子计算机通过量子并行编程生成大容量量子计算系统（[M. S. Ying，Morgan-Kaufmann，2016]）。这样一来，主要障碍是将整个电路中的量子门分开，以产生当地大门的张量。已经表明，很少有可分离的多部分量子门，因此近似分离问题涉及找到近似给定不可分割的门的局部量子门。我们提出并研究了一个问题，涉及基于量子闸的忠诚度多片门的近似分离。对于给定的多片和局部门，我们得出结论，较小的是任意特征值的乘积之间的最大距离，它们的栅极保真度就越大。这为近似分离提供了标准。最后，我们讨论了CNOT门的最佳近似分离。
Ying conceived of using two or more small-capacity quantum computers to produce a larger-capacity quantum computing system by quantum parallel programming ([M. S. Ying, Morgan-Kaufmann, 2016]). In doing so, the main obstacle is separating the quantum gates in the whole circuit to produce a tensor product of the local gates. It has been showed that there are few separable multipartite quantum gates, so the approximate separation problem involves finding local quantum gates that approximate a given inseparable gate. We propose and study a problem involving the approximate separation of multipartite gates based on quantum-gate fidelity. For given multipartite and local gates, we conclude that the smaller is the maximal distance between the products of an arbitrary pair of eigenvalues, the greater is their gate fidelity. This provides a criterion for approximate separation. Lastly, we discuss the optimal approximate separation of the CNOT gate.
