Zobrazeno 1 - 10
of 79
pro vyhledávání: '"IBM Q"'
Autor:
FENG Yan, WANG Rui-cong
Publikováno v:
Jisuanji kexue, Vol 49, Iss 5, Pp 311-317 (2022)
To solve the problem that the user information is easy to be stolen in the traditional electronic voting,and the existing quantum voting generally has low computational efficiency,a quantum voting protocol based on the combination of quantum Fourier
Externí odkaz:
https://doaj.org/article/95b4923e8d904aca9d00d29c2361e2cc
Publikováno v:
IEEE Transactions on Quantum Engineering, Vol 3, Pp 1-12 (2022)
The classical image segmentation algorithm based on grayscale morphology can effectively segment images with uneven illumination, but with the increase of image data, the real-time problem will emerge. In order to solve this problem, a quantum image
Externí odkaz:
https://doaj.org/article/ae2ede4ac98f445790271564d4b8cd16
Publikováno v:
IEEE Transactions on Quantum Engineering, Vol 3, Pp 1-16 (2022)
We present a divide-and-conquer approach to deterministically prepare Dicke states $|D^{n}_{k}\rangle$ (i.e., equal-weight superpositions of all $n$-qubit states with Hamming weight $k$) on quantum computers. In an experimental evaluation for up to $
Externí odkaz:
https://doaj.org/article/a00d68e11f92491cae5c4cbf79d20050
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Masaya Watabe, Kodai Shiba, Chih-Chieh Chen, Masaru Sogabe, Katsuyoshi Sakamoto, Tomah Sogabe
Publikováno v:
Quantum Reports, Vol 3, Iss 2, Pp 333-349 (2021)
Quantum computing has the potential to outperform classical computers and is expected to play an active role in various fields. In quantum machine learning, a quantum computer has been found useful for enhanced feature representation and high-dimensi
Externí odkaz:
https://doaj.org/article/c7036951e2434c3580593e3e8eb89f09
Publikováno v:
IEEE Transactions on Quantum Engineering, Vol 2, Pp 1-10 (2021)
We determine the resource scaling of machine learning-based quantum state reconstruction methods, in terms of inference and training, for systems of up to four qubits when constrained to pure states. Further, we examine system performance in the low-
Externí odkaz:
https://doaj.org/article/827bb9630b264b56978b15a7a7bb351b
Autor:
Antônio Nunes Oliveira, Estevão V. B. de Oliveira, Alan Costa Santos, Celso Jorge Villas-Boas
Publikováno v:
Revista Brasileira de Ensino de Física, Vol 44 (2021)
Processamento de informação quântica tem sido um dos pilares da nova era da informação. Nessa direção, o controle e processamento de informação quântica desempenha um papel fundamental, e computadores capazes de manipular tais informações
Externí odkaz:
https://doaj.org/article/ad5c1e8fd10d4ecf990277a74bc4daf6
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
IEEE Transactions on Quantum Engineering, Vol 2, Pp 1-10 (2021)
We determine the resource scaling of machine learning-based quantum state reconstruction methods, in terms of inference and training, for systems of up to four qubits when constrained to pure states. Further, we examine system performance in the low-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::139df0b5c8863576319e9ffc52713fcd
https://doi.org/10.1109/tqe.2021.3106958
https://doi.org/10.1109/tqe.2021.3106958