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Combinatorial Optimization by Quantum Neural Networks and Its Applications
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- HASEGAWA Mikio
- Faculty of Engineering, Tokyo University of Science
Bibliographic Information
- Other Title
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- 量子ニューラルネットワークを用いた組合せ最適化及びその応用
Description
An optimization method based on energy minimization of the Ising Hamiltonian has been proposed in recent research (S. Utsunomiya et al., Optics Express 19, 2011). Large-scale implementation of such a high-speed optimization method has also been proposed. (T. Inagaki et al., Science, 234, 2016). This paper introduces the quantum neural networks, that can be realized by high-speed devices and applies them to combinatorial ptimization problems. In such schemes using quantum neural networks, an objective function for target optimization problems has to be implemented on mutual connections. In this paper, a mutually connected neural network has been implemented on quantum neural networks to solve combinatorial optimization problems. The simulation results show that quantum neural networks can solve combinatorial optimization problems.
Journal
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- IEICE ESS Fundamentals Review
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IEICE ESS Fundamentals Review 11 (2), 113-117, 2017
The Institute of Electronics, Information and Communication Engineers
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Keywords
Details 詳細情報について
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- CRID
- 1390001205343474304
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- NII Article ID
- 130006110803
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- ISSN
- 18820875
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- Text Lang
- ja
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
- OpenAIRE
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- Abstract License Flag
- Disallowed