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- W4285293325 endingPage "73177" @default.
- W4285293325 startingPage "73156" @default.
- W4285293325 abstract "Quantum annealing is a quantum computing approach widely used for optimization and probabilistic sampling problems. It is an alternative approach designed due to the limitations of gate-based quantum computing models. The method is observed to have a significant impact on different fields such as machine learning, graphics, routing, scheduling, computational chemistry, computational biology, security, portfolio, and others despite the fact that it is relatively new. This research provides a systematic review of research development trends in the field of quantum annealing and analyzes how it has been implemented in different problem domains. The results are expected to serve as the basis to identify the opportunities and challenges of research related to its implementation. The main contribution of this systematic review is to summarize different implementations of quantum annealing. It is also to analyze the prospect and opportunities in one of the problem domains with the greatest interest which is machine learning." @default.
- W4285293325 created "2022-07-14" @default.
- W4285293325 creator A5041115880 @default.
- W4285293325 creator A5071778708 @default.
- W4285293325 date "2022-01-01" @default.
- W4285293325 modified "2023-10-17" @default.
- W4285293325 title "Implementation of Quantum Annealing: A Systematic Review" @default.
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