Quantum Neural Networks Achieving Quantum Algorithms

Delphine Nicolay; Timoteo Carletti

doi:10.1007/978-3-319-78658-2_1

Quantum Neural Networks Achieving Quantum Algorithms

Delphine Nicolay, Timoteo Carletti

Research output: Contribution in Book/Catalog/Report/Conference proceeding › Conference contribution

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Abstract

This paper explores the possibility to construct quantum algorithms by means of neural networks endowed with quantum gates evolved to achieve prescribed goals. First tentatives are performed on the well known Deutsch and Deutsch-Jozsa problems. Results are promising as solutions are detected for different sizes and initializations of the problems using a standard evolutionary learning process. This approach is then used to design quantum operators by combining simple quantum operators belonging to a predefined set.

Original language	English
Title of host publication	Artificial Life and Evolutionary Computation - 12th Italian Workshop, WIVACE 2017, Revised Selected Papers
Editors	Marcello Pelillo, Irene Poli, Debora Slanzi, Roberto Serra, Marco Villani, Andrea Roli
Publisher	Springer
Pages	3-15
Number of pages	13
Volume	830
ISBN (Electronic)	978-3-319-78658-2
ISBN (Print)	978-3-319-78657-5
DOIs	https://doi.org/10.1007/978-3-319-78658-2_1
Publication status	Published - 2 May 2018

Publication series

Name	Communications in Computer and Information Science
Volume	830
ISSN (Print)	1865-0929

Keywords

Quantum Neural Networks
Quantum Algorithms
Genetic Algorithm
heuristic method

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10.1007/978-3-319-78658-2_1

AdvArtifLifeEvolutComput_830_2018pp3Final published version, 680 KB

https://www.springer.com/gp/book/9783319786575

Cite this

Nicolay, D., & Carletti, T. (2018). Quantum Neural Networks Achieving Quantum Algorithms. In M. Pelillo, I. Poli, D. Slanzi, R. Serra, M. Villani, & A. Roli (Eds.), Artificial Life and Evolutionary Computation - 12th Italian Workshop, WIVACE 2017, Revised Selected Papers (Vol. 830, pp. 3-15). (Communications in Computer and Information Science; Vol. 830). Springer. https://doi.org/10.1007/978-3-319-78658-2_1

Nicolay, Delphine ; Carletti, Timoteo. / Quantum Neural Networks Achieving Quantum Algorithms. Artificial Life and Evolutionary Computation - 12th Italian Workshop, WIVACE 2017, Revised Selected Papers. editor / Marcello Pelillo ; Irene Poli ; Debora Slanzi ; Roberto Serra ; Marco Villani ; Andrea Roli. Vol. 830 Springer, 2018. pp. 3-15 (Communications in Computer and Information Science).

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title = "Quantum Neural Networks Achieving Quantum Algorithms",

abstract = "This paper explores the possibility to construct quantum algorithms by means of neural networks endowed with quantum gates evolved to achieve prescribed goals. First tentatives are performed on the well known Deutsch and Deutsch-Jozsa problems. Results are promising as solutions are detected for different sizes and initializations of the problems using a standard evolutionary learning process. This approach is then used to design quantum operators by combining simple quantum operators belonging to a predefined set.",

keywords = "Quantum Neural Networks, Quantum Algorithms, Genetic Algorithm, heuristic method",

author = "Delphine Nicolay and Timoteo Carletti",

note = "Funding Information: We thank Andrea Roli for his critical reading of a preliminary version of the paper. This research used computational resources of the “Plateforme Technologique de Calcul Intensif (PTCI)” located at the University of Namur, Belgium, which is supported by the F.R.S.-FNRS. This paper presents research results of the Belgian Network DYSCO (Dynamical Systems, Control, and Optimisation), funded by the Interuniversity Attraction Poles Programme, initiated by the Belgian State, Science Policy Office. The scientific responsibility rests with its authors. Funding Information: This paper presents research results of the Belgian Network DYSCO (Dynamical Systems, Control, and Optimisation), funded by the Interuniversity Attraction Poles Programme, initiated by the Belgian State, Science Policy Office. The scientific responsibility rests with its authors. Funding Information: This research used computational resources of the “Plateforme Technologique de Calcul Intensif (PTCI)” located at the University of Namur, Belgium, which is supported by the F.R.S.-FNRS. Publisher Copyright: {\textcopyright} 2018, Springer International Publishing AG, part of Springer Nature.",

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Nicolay, D & Carletti, T 2018, Quantum Neural Networks Achieving Quantum Algorithms. in M Pelillo, I Poli, D Slanzi, R Serra, M Villani & A Roli (eds), Artificial Life and Evolutionary Computation - 12th Italian Workshop, WIVACE 2017, Revised Selected Papers. vol. 830, Communications in Computer and Information Science, vol. 830, Springer, pp. 3-15. https://doi.org/10.1007/978-3-319-78658-2_1

Quantum Neural Networks Achieving Quantum Algorithms. / Nicolay, Delphine ; Carletti, Timoteo.
Artificial Life and Evolutionary Computation - 12th Italian Workshop, WIVACE 2017, Revised Selected Papers. ed. / Marcello Pelillo; Irene Poli; Debora Slanzi; Roberto Serra; Marco Villani; Andrea Roli. Vol. 830 Springer, 2018. p. 3-15 (Communications in Computer and Information Science; Vol. 830).

Research output: Contribution in Book/Catalog/Report/Conference proceeding › Conference contribution

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T1 - Quantum Neural Networks Achieving Quantum Algorithms

AU - Nicolay, Delphine

AU - Carletti, Timoteo

N1 - Funding Information: We thank Andrea Roli for his critical reading of a preliminary version of the paper. This research used computational resources of the “Plateforme Technologique de Calcul Intensif (PTCI)” located at the University of Namur, Belgium, which is supported by the F.R.S.-FNRS. This paper presents research results of the Belgian Network DYSCO (Dynamical Systems, Control, and Optimisation), funded by the Interuniversity Attraction Poles Programme, initiated by the Belgian State, Science Policy Office. The scientific responsibility rests with its authors. Funding Information: This paper presents research results of the Belgian Network DYSCO (Dynamical Systems, Control, and Optimisation), funded by the Interuniversity Attraction Poles Programme, initiated by the Belgian State, Science Policy Office. The scientific responsibility rests with its authors. Funding Information: This research used computational resources of the “Plateforme Technologique de Calcul Intensif (PTCI)” located at the University of Namur, Belgium, which is supported by the F.R.S.-FNRS. Publisher Copyright: © 2018, Springer International Publishing AG, part of Springer Nature.

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N2 - This paper explores the possibility to construct quantum algorithms by means of neural networks endowed with quantum gates evolved to achieve prescribed goals. First tentatives are performed on the well known Deutsch and Deutsch-Jozsa problems. Results are promising as solutions are detected for different sizes and initializations of the problems using a standard evolutionary learning process. This approach is then used to design quantum operators by combining simple quantum operators belonging to a predefined set.

AB - This paper explores the possibility to construct quantum algorithms by means of neural networks endowed with quantum gates evolved to achieve prescribed goals. First tentatives are performed on the well known Deutsch and Deutsch-Jozsa problems. Results are promising as solutions are detected for different sizes and initializations of the problems using a standard evolutionary learning process. This approach is then used to design quantum operators by combining simple quantum operators belonging to a predefined set.

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KW - Genetic Algorithm

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A2 - Serra, Roberto

A2 - Villani, Marco

A2 - Roli, Andrea

PB - Springer

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Nicolay D , Carletti T. Quantum Neural Networks Achieving Quantum Algorithms. In Pelillo M, Poli I, Slanzi D, Serra R, Villani M, Roli A, editors, Artificial Life and Evolutionary Computation - 12th Italian Workshop, WIVACE 2017, Revised Selected Papers. Vol. 830. Springer. 2018. p. 3-15. (Communications in Computer and Information Science). doi: 10.1007/978-3-319-78658-2_1

Quantum Neural Networks Achieving Quantum Algorithms

Abstract

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Keywords

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High Performance Computing Technology Platform

Italian Workshop on Artificial Life and Evolutionary Computation (WIVACE 2017)

Cite this

Quantum Neural Networks Achieving Quantum Algorithms

Abstract

Publication series

Keywords

Access to Document

Other files and links

Fingerprint

Equipment

High Performance Computing Technology Platform

Activities

Italian Workshop on Artificial Life and Evolutionary Computation (WIVACE 2017)

Cite this