论文标题
矩阵稀疏性和量子噪声对量子随机步行线性求解器的影响
Effect of matrix sparsity and quantum noise on quantum random walk linear solvers
论文作者
论文摘要
我们研究量子噪声在杂交量子式求解器中使用量子随机步行对线性方程式稀疏系统的影响，该系统应用于静态的哈密顿矩阵。在理想的无噪声量子计算机中，稀疏矩阵实现了相对误差低于密集矩阵的溶液向量。但是，我们发现量子噪声会逆转这种效果，随着稀疏性的增加，总体误差增加。我们确定无效的量子随机步行是这种误差增加的原因，并提出了修订后的线性求解器算法，该算法通过减轻这些无效的步行来提高准确性。
We study the effects of quantum noise in hybrid quantum-classical solver for sparse systems of linear equations using quantum random walks, applied to stoquastic Hamiltonian matrices. In an ideal noiseless quantum computer, sparse matrices achieve solution vectors with lower relative error than dense matrices. However, we find quantum noise reverses this effect, with overall error increasing as sparsity increases. We identify invalid quantum random walks as the cause of this increased error and propose a revised linear solver algorithm which improves accuracy by mitigating these invalid walks.
