Gaussian states of continuous-variable quantum systems provide universal and versatile reservoir computing
Most attempts to delineate quantum machine-learning-related computing capabilities of continuous variables states have relied on non-Gaussian resources. Here, the authors show that linear systems with continuous-variable Gaussian states are a promising platform for the implementation of quantum rese...
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| Autores principales: | , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/6d99dbbbdff343148f879fffd11fbb76 |
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| Sumario: | Most attempts to delineate quantum machine-learning-related computing capabilities of continuous variables states have relied on non-Gaussian resources. Here, the authors show that linear systems with continuous-variable Gaussian states are a promising platform for the implementation of quantum reservoir computers with universal approximation capabilities |
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