An extension of FermiNet to discover quantum phase transitions
6 de feb. de 2023 ·
13m
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https://phys.org/news/2023-02-extension-ferminet-quantum-phase-transitions.html Architectures based on artificial neural networks (ANNs) have proved to be very helpful in research settings, as they can quickly analyze vast amounts of data and make accurate predictions....
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https://phys.org/news/2023-02-extension-ferminet-quantum-phase-transitions.html
Architectures based on artificial neural networks (ANNs) have proved to be very helpful in research settings, as they can quickly analyze vast amounts of data and make accurate predictions. In 2020, Google's British AI subsidiary DeepMind used a new ANN architecture dubbed the Fermionic neural network (FermiNet) to solve the Schrodinger equation for electrons in molecules, a central problem in the field of chemistry.
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Architectures based on artificial neural networks (ANNs) have proved to be very helpful in research settings, as they can quickly analyze vast amounts of data and make accurate predictions. In 2020, Google's British AI subsidiary DeepMind used a new ANN architecture dubbed the Fermionic neural network (FermiNet) to solve the Schrodinger equation for electrons in molecules, a central problem in the field of chemistry.
Información
| Autor | UniquilbriuM |
| Organización | Flor and Hakeem |
| Página web | - |
| Etiquetas |
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