Asymptotic Quantum Algorithm for the Toeplitz Systems

TL;DR

This paper introduces a quantum algorithm for solving Toeplitz linear systems with nearly logarithmic complexity, offering exponential speedup over classical methods under certain condition number constraints.

Contribution

The paper presents a novel quantum algorithm for Toeplitz systems that does not require sparsity and achieves near-logarithmic complexity, advancing quantum linear system solutions.

Findings

Algorithm complexity is nearly $O( ext{log}^2 n)$

Exponential speedup over classical algorithms for certain condition numbers

Applicable to non-sparse Toeplitz matrices

Abstract

Solving the Toeplitz systems, which is to find the vector $x$ such that $T_nx = b$ given an $n\times n$ 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 linear equations of Toeplitz matrices, in which the Toeplitz matrices are generated by discretizing a continuous function. It is shown that our algorithm's complexity is nearly $O(\kappa\textrm{log}^2 n)$, where $\kappa$ and $n$ are the condition number and the dimension of $T_n$ respectively. This implies our algorithm is exponentially faster than the best classical algorithm for the same problem if $\kappa=O(\textrm{poly}(\textrm{log}\,n))$. Since no assumption on the sparseness of $T_n$ is demanded in our algorithm, it can serve as an example of quantum algorithms for solving non-sparse linear systems.