Quantum image processing?

Quantum image processing? This paper presents a number of problems concerning the practical (real) implementation of the techniques known as quantum image processing. The most serious problem is the recovery of the outcomes after the quantum measurement, which will be demonstrated in this work that is equivalent to a noise measurement, and it is not considered in the literature on the subject. It is noteworthy that this is due to several factors: (1) a classical algorithm that uses Dirac’s notation and then it is coded in MATLAB does not constitute a quantum algorithm, (2) the literature emphasizes the internal representation of the image but says nothing about the classical-to-quantum and quantum-to-classical interfaces and how these are affected by decoherence, (3) the literature does not mention how to implement in a practical way (at the laboratory) these proposals internal representations, (4) given that quantum image processing works with generic qubits, this requires measurements in all axes of the Bloch sphere, logically, and (5) among others. In return, the technique known as quantum Boolean image processing is mentioned, which works with computational basis states (CBS), exclusively. This methodology allows us to avoid the problem of quantum measurement, which alters the results of the measured except in the case of CBS. Said so far is extended to quantum algorithms outside image processing too. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quantum Information Processing Springer Journals

Quantum image processing?

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Publisher
Springer Journals
Copyright
Copyright © 2016 by Springer Science+Business Media New York
Subject
Physics; Quantum Information Technology, Spintronics; Quantum Computing; Data Structures, Cryptology and Information Theory; Quantum Physics; Mathematical Physics
ISSN
1570-0755
eISSN
1573-1332
D.O.I.
10.1007/s11128-016-1457-y
Publisher site
See Article on Publisher Site

Abstract

This paper presents a number of problems concerning the practical (real) implementation of the techniques known as quantum image processing. The most serious problem is the recovery of the outcomes after the quantum measurement, which will be demonstrated in this work that is equivalent to a noise measurement, and it is not considered in the literature on the subject. It is noteworthy that this is due to several factors: (1) a classical algorithm that uses Dirac’s notation and then it is coded in MATLAB does not constitute a quantum algorithm, (2) the literature emphasizes the internal representation of the image but says nothing about the classical-to-quantum and quantum-to-classical interfaces and how these are affected by decoherence, (3) the literature does not mention how to implement in a practical way (at the laboratory) these proposals internal representations, (4) given that quantum image processing works with generic qubits, this requires measurements in all axes of the Bloch sphere, logically, and (5) among others. In return, the technique known as quantum Boolean image processing is mentioned, which works with computational basis states (CBS), exclusively. This methodology allows us to avoid the problem of quantum measurement, which alters the results of the measured except in the case of CBS. Said so far is extended to quantum algorithms outside image processing too.

Journal

Quantum Information ProcessingSpringer Journals

Published: Dec 20, 2016

References

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