三种高效快速的量子态滤波和估计优化算法

Three Types of Efficient and Fast Optimization Algorithms for Quantum State Filtering and Estimation

针对不同干扰和噪声情况下的量子状态估计和滤波问题,分别提出相应的高效量子状态密度矩阵重构凸优化算法.对于稀疏状态干扰和测量噪声同时存在的情况,提出量子状态滤波算法.对分别存在稀疏状态干扰和测量噪声的情况,提出相应两种不同的量子状态估计算法.在5量子位的状态密度矩阵估计仿真实验中分析不同采样率下的3种算法性能.实验表明,3种算法均具有较低的计算复杂度、较快的收敛速度和较低的估计误差.

The quantum state estimation and filtering problems under different interference and noise conditions are studied, and the corresponding efficient convex algorithms for quantum state density matrix reconstruction are proposed. A quantum state filtering algorithm is proposed for the simultaneous existence of sparse state interference and measurement noise. Two different quantum state estimation algorithms for the existence of sparse state interference and measurement noise are proposed, respectively. In the simulation experiments of the 5-qubit density matrix estimation, the performances of the three proposed algorithms are compared, and the performances of the three algorithms with different measurement rates are analyzed. Experimental results show that the three algorithms have high convergent speeds and low computational complexity, low estimation errors and measurement rates.