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Hybrid quantum physics-informed neural networks for simulating computational fluid dynamics in complex shapes
Finding the distribution of the velocities and pressures of a fluid (by solving the Navier-Stokes equations) is a principal task in the chemical, energy, and pharmaceutical industries, as well as in mechanical engineering and the design of pipeline systems.
Quantum machine learning for image classification
This model demonstrated a record-breaking classification accuracy of 99. 21% on the full MNIST dataset, surpassing the performance of known quantum-classical models, while having eight times fewer parameters than its classical counterpart.
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