Inverse-coefficient black-box quantum state preparation

Black-box quantum state preparation is a fundamental building block for many higher-level quantum algorithms. The basic task of black-box state preparation is to transduce the data encoded as computational basis of quantum state into the amplitude. In the present work, we address the problem of tran...

Full description

Bibliographic Details
Main Authors: Shengbin Wang, Zhimin Wang, Runhong He, Shangshang Shi, Guolong Cui, Ruimin Shang, Jiayun Li, Yanan Li, Wendong Li, Zhiqiang Wei, Yongjian Gu
Format: Article
Language:English
Published: IOP Publishing 2022-01-01
Series:New Journal of Physics
Subjects:
Online Access:https://doi.org/10.1088/1367-2630/ac93a8
Description
Summary:Black-box quantum state preparation is a fundamental building block for many higher-level quantum algorithms. The basic task of black-box state preparation is to transduce the data encoded as computational basis of quantum state into the amplitude. In the present work, we address the problem of transducing the reciprocal of the data, not the data itself into the amplitude, which is called the inverse-coefficient problem. This algorithm can be used directly as a subroutine in the matrix inversion algorithms. Furthermore, we extend this approach to address the more general nonlinear-coefficient problem in black-box state preparation. Our algorithm is based on the technique of inequality test. It can greatly relieve the need to do quantum arithmetic and the error is only resulted from the truncated error of binary string. The present algorithms enrich the algorithm library of black-box quantum state preparation and will be useful ingredients of quantum algorithm to implement non-linear quantum state transformations.
ISSN:1367-2630