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Trapped Ion Quantum Computing
Quantum Machine Learning
Quantum Simulation
Quantum Chemistry
Quantum Algorithm for a Stochastic Multicloud Model
arXiv
Authors: Kazumasa Ueno, Hiroaki Miura
Year
2024
Paper ID
66451
Status
Preprint
Abstract Read
~2 min
Abstract Words
163
Citations
N/A
Abstract
Quantum computers have attracted much attention in recent years. This is because the development of the actual quantum machine is accelerating. Research on how to use quantum computers is active in the fields such as quantum chemistry and machine learning, where vast amounts of computation are required. However, in weather and climate simulations, less research has been done despite similar computational demands. In this study, a quantum computing algorithm is applied to a problem of the atmospheric science. The effectiveness of the proposed algorithm is evaluated using a quantum simulator. The results show that it can achieve the same simulations as a conventional algorithm designed for classical computers. More specifically, the stochastically fluctuating behavior of a multi-cloud model was obtained using classical Monte Carlo method, and comparable results are also achieved by utilizing probabilistic outputs of computed quantum states. Our results show that quantum computers have a potential to be useful for the atmospheric and oceanic science, in which stochasticity is widely inherent.
Why This Paper Matters
- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
- It adds a 2024 reference point for readers tracking recent quantum research.
- Quantum computers have attracted much attention in recent years.
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