Quantum Algorithm for the Toeplitz Systems
Lin‐Chun Wan, Chao‐Hua Yu, Shi‐Jie Pan, Fei Gao, Qiaoyan Wen · arXiv (Cornell University) · 2016
Solving the Toeplitz systems, which is to find the vector $x$ such that $T_nx = b$ given a $n\times n$ Toeplitz matrix $T_n$ and a vector $b$, has a variety of applications in mathematics and engineering. In this paper, we present a quantum algorithm for solving the Toeplitz systems, in which a quantum state encoding the solution with error $\epsilon$ is generated. It is shown that our algorithm's complexity is nearly linear in the condition number, and polylog in the dimensions $n$ and in the inverse error $\epsilon^{-1}$. This implies our algorithm is exponentially faster than the best classical algorithm for the same problem if the condition number of $T_n$ is $O(\textrm{poly}(\textrm{log}\,n))$. Since no assumption on the sparseness of $T_n$ is demanded in our algorithm, the algorithm can serve as an example of quantum algorithms for solving non-sparse linear systems.