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量子算法在数据拟合中的应用。

Quantum algorithm for data fitting.

机构信息

Institute for Quantum Computing, Waterloo, Ontario, Canada.

出版信息

Phys Rev Lett. 2012 Aug 3;109(5):050505. doi: 10.1103/PhysRevLett.109.050505. Epub 2012 Aug 2.

Abstract

We provide a new quantum algorithm that efficiently determines the quality of a least-squares fit over an exponentially large data set by building upon an algorithm for solving systems of linear equations efficiently [Harrow et al., Phys. Rev. Lett. 103, 150502 (2009)]. In many cases, our algorithm can also efficiently find a concise function that approximates the data to be fitted and bound the approximation error. In cases where the input data are pure quantum states, the algorithm can be used to provide an efficient parametric estimation of the quantum state and therefore can be applied as an alternative to full quantum-state tomography given a fault tolerant quantum computer.

摘要

我们提供了一种新的量子算法,该算法基于高效求解线性方程组的算法[Harrow 等人,Phys. Rev. Lett. 103, 150502 (2009)],可有效地确定在指数级大数据集上的最小二乘拟合的质量。在许多情况下,我们的算法还可以有效地找到一个简洁的函数来近似要拟合的数据,并对逼近误差进行约束。在输入数据是纯量子态的情况下,该算法可用于提供对量子态的高效参数估计,因此在具有容错能力的量子计算机的情况下,可以替代全量子态层析成像。

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