Realising and compressing quantum circuits with quantum reservoir computing
Building quantum computers typically requires substantial engineering efforts to achieve precise control on qubits and quantum gates. Here, the authors introduce an architecture based on reservoir computing and machine learning to realize efficient quantum operations without resorting to full optimi...
Guardado en:
Autores principales: | , , , |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/2feda7b6e87549cea5068c5c9e6f1bed |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
id |
oai:doaj.org-article:2feda7b6e87549cea5068c5c9e6f1bed |
---|---|
record_format |
dspace |
spelling |
oai:doaj.org-article:2feda7b6e87549cea5068c5c9e6f1bed2021-12-02T15:52:53ZRealising and compressing quantum circuits with quantum reservoir computing10.1038/s42005-021-00606-32399-3650https://doaj.org/article/2feda7b6e87549cea5068c5c9e6f1bed2021-05-01T00:00:00Zhttps://doi.org/10.1038/s42005-021-00606-3https://doaj.org/toc/2399-3650Building quantum computers typically requires substantial engineering efforts to achieve precise control on qubits and quantum gates. Here, the authors introduce an architecture based on reservoir computing and machine learning to realize efficient quantum operations without resorting to full optimization of the control parameters.Sanjib GhoshTanjung KrisnandaTomasz PaterekTimothy C. H. LiewNature PortfolioarticleAstrophysicsQB460-466PhysicsQC1-999ENCommunications Physics, Vol 4, Iss 1, Pp 1-7 (2021) |
institution |
DOAJ |
collection |
DOAJ |
language |
EN |
topic |
Astrophysics QB460-466 Physics QC1-999 |
spellingShingle |
Astrophysics QB460-466 Physics QC1-999 Sanjib Ghosh Tanjung Krisnanda Tomasz Paterek Timothy C. H. Liew Realising and compressing quantum circuits with quantum reservoir computing |
description |
Building quantum computers typically requires substantial engineering efforts to achieve precise control on qubits and quantum gates. Here, the authors introduce an architecture based on reservoir computing and machine learning to realize efficient quantum operations without resorting to full optimization of the control parameters. |
format |
article |
author |
Sanjib Ghosh Tanjung Krisnanda Tomasz Paterek Timothy C. H. Liew |
author_facet |
Sanjib Ghosh Tanjung Krisnanda Tomasz Paterek Timothy C. H. Liew |
author_sort |
Sanjib Ghosh |
title |
Realising and compressing quantum circuits with quantum reservoir computing |
title_short |
Realising and compressing quantum circuits with quantum reservoir computing |
title_full |
Realising and compressing quantum circuits with quantum reservoir computing |
title_fullStr |
Realising and compressing quantum circuits with quantum reservoir computing |
title_full_unstemmed |
Realising and compressing quantum circuits with quantum reservoir computing |
title_sort |
realising and compressing quantum circuits with quantum reservoir computing |
publisher |
Nature Portfolio |
publishDate |
2021 |
url |
https://doaj.org/article/2feda7b6e87549cea5068c5c9e6f1bed |
work_keys_str_mv |
AT sanjibghosh realisingandcompressingquantumcircuitswithquantumreservoircomputing AT tanjungkrisnanda realisingandcompressingquantumcircuitswithquantumreservoircomputing AT tomaszpaterek realisingandcompressingquantumcircuitswithquantumreservoircomputing AT timothychliew realisingandcompressingquantumcircuitswithquantumreservoircomputing |
_version_ |
1718385561656360960 |