An Improvement in Quantum Fourier Transform
Abstract
Singular Value Decomposition (SVD) is one of the most useful techniques for analyzing data in linear algebra. SVD decomposes a rectangular real or complex matrix into two orthogonal matrices and one diagonal matrix. In this work we introduce a new approach to improve the preciseness of the standard Quantum Fourier Transform. The presented Quantum-SVD algorithm is based on the singular value decomposition mechanism. While the complexity of the proposed scheme is the same as the standard Quantum Fourier Transform, the precision of the Quantum-SVD approach is some orders higher. The Quantum-SVD approach also exploits the benefits of quantum searching.
Keywords
Cite
@article{arxiv.1207.4464,
title = {An Improvement in Quantum Fourier Transform},
author = {Laszlo Gyongyosi and Sandor Imre},
journal= {arXiv preprint arXiv:1207.4464},
year = {2012}
}
Comments
30 pages, 10 figures, Journal-ref: Journal of Circuits, Systems, and Computers (JCSC), World Scientific, Print ISSN: 0218-1266, Online ISSN: 1793-6454; 2010