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Quantum neural network for combinatorial optimization and boltzmann sampling
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Journal of Lasers, Optics & Photonics

ISSN: 2469-410X

Open Access

Quantum neural network for combinatorial optimization and boltzmann sampling


Joint Event on 6th International Conference on Photonics & 7th International Conference on Laser Optics

July 31- August 02, 2017 Milan, Italy

Yoshihisa Yamamoto

Japan Science and Technology Agency, Japan

Posters & Accepted Abstracts: J Laser Opt Photonics

Abstract :

Many combinatorial optimization problems can be mapped onto ground-state-search problems of the Ising model or more general neural network. However, physical Ising machines are often based on localized spins, resulting in limited number of spin-spin couplings and severe scalability problems. We report 100ΓΆΒ?Β?2,000 spin networks with all-to-all connections using time-multiplexed optical parametric oscillator pulses and measurement and feedback control. The developed machine can outperform simulated annealing in terms of accuracy and computation time for dense graphs.

Google Scholar citation report
Citations: 279

Journal of Lasers, Optics & Photonics received 279 citations as per Google Scholar report

Journal of Lasers, Optics & Photonics peer review process verified at publons

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