Quantum mechanics and machine learning may seem theoretically disparate, but their link becomes clear through the density matrix operator which can be readily approximated by neural network models, permitting a formulation of quantum physics in which physical observables can be computed via neural networks.
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Quantum mechanics and machine learning may seem theoretically disparate, but their link becomes clear through the density matrix operator which can be readily approximated by neural network models, permitting a formulation of quantum physics in which physical observables can be computed via neural networks.
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New. Contains: Illustrations, black & white, Illustrations, color. Quantum Science and Technology . XXIII, 378 p. 109 illus., 66 illus. in color. Intended for professional and scholarly audience.
![Quantum Machine Learning: Thinking and Exploration in Neural Network Models for Quantum Science and Quantum Computing (Quantum Science and Technology) [Hardcover] [Jan 03, 2024] Conti, Claudio](https://www.alibris-static.com/isbn/9783031442254_t.gif)
