The quantum Fourier transform based on quantum vision representation

Hai Sheng Li, Ping Fan, Hai ying Xia, Shuxiang Song, Xiangjian He

Research output: Journal PublicationArticlepeer-review

12 Citations (Scopus)

Abstract

Quantum Fourier transform (QFT) plays a key role in many quantum algorithms, but the existing circuits of QFT are incomplete and lacking the proof of correctness. Furthermore, it is difficult to apply QFT to the concrete field of information processing. Thus, we firstly investigate quantum vision representation (QVR) and develop a model of QVR. Then, we design four complete circuits of QFT and inverse QFT and describe the functions of their components. Meanwhile, we prove the correctness of the four complete circuits using formula derivation. Next, 2D QFT and 3D QFT based on QVR are proposed for the first time. Experimental results with simulation show the proposed QFTs are valid and useful in processing quantum images and videos. In conclusion, this paper develops a complete framework of QFT based on QVR and provides a feasible scheme for QFT to be applied in quantum vision information processing.

Original languageEnglish
Article number333
JournalQuantum Information Processing
Volume17
Issue number12
DOIs
Publication statusPublished - 1 Dec 2018
Externally publishedYes

Keywords

  • Quantum computing
  • Quantum Fourier transformation
  • Quantum image processing
  • Quantum information processing

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Statistical and Nonlinear Physics
  • Theoretical Computer Science
  • Signal Processing
  • Modelling and Simulation
  • Electrical and Electronic Engineering

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