Quantum machine learning for electronic structure calculations
With the rapid development of quantum computers, quantum machine learning approaches are emerging as powerful tools to perform electronic structure calculations. Here, the authors develop a quantum machine learning algorithm, which demonstrates significant improvements in solving quantum many-body p...
Guardado en:
Autores principales: | Rongxin Xia, Sabre Kais |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2018
|
Materias: | |
Acceso en línea: | https://doaj.org/article/2c2ac00115c04322a31d84ce4aae2fb4 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
A quantum algorithm for evolving open quantum dynamics on quantum computing devices
por: Zixuan Hu, et al.
Publicado: (2020) -
Magnetic flux noise in superconducting qubits and the gap states continuum
por: Dominik Szczęśniak, et al.
Publicado: (2021) -
Power of data in quantum machine learning
por: Hsin-Yuan Huang, et al.
Publicado: (2021) -
Demonstration of quantum advantage in machine learning
por: Diego Ristè, et al.
Publicado: (2017) -
To address surface reaction network complexity using scaling relations machine learning and DFT calculations
por: Zachary W. Ulissi, et al.
Publicado: (2017)