Nearest centroid classification on a trapped ion quantum computer
Abstract Quantum machine learning has seen considerable theoretical and practical developments in recent years and has become a promising area for finding real world applications of quantum computers. In pursuit of this goal, here we combine state-of-the-art algorithms and quantum hardware to provid...
Guardado en:
Autores principales: | Sonika Johri, Shantanu Debnath, Avinash Mocherla, Alexandros SINGK, Anupam Prakash, Jungsang Kim, Iordanis Kerenidis |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/7ac446645ae74a218aaee8d6c4706aec |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Improved trilateration for indoor localization: Neural network and centroid-based approach
por: Satish R Jondhale, et al.
Publicado: (2021) -
Quality-related fault diagnosis based on -nearest neighbor rule for non-linear industrial processes
por: Zelin Ren, et al.
Publicado: (2021) -
Riemann zeros from Floquet engineering a trapped-ion qubit
por: Ran He, et al.
Publicado: (2021) -
Power-optimal, stabilized entangling gate between trapped-ion qubits
por: Reinhold Blümel, et al.
Publicado: (2021) -
Reprogrammable and high-precision holographic optical addressing of trapped ions for scalable quantum control
por: Chung-You Shih, et al.
Publicado: (2021)