scholarly journals Heterogeneous multipartite entanglement purification for size-constrained quantum devices

2021 ◽  
Vol 3 (3) ◽  
Author(s):  
Stefan Krastanov ◽  
Alexander Sanchez de la Cerda ◽  
Prineha Narang
2009 ◽  
Vol 55 (1) ◽  
pp. 235-242 ◽  
Author(s):  
Y. B. Sheng ◽  
F. G. Deng ◽  
B. K. Zhao ◽  
T. J. Wang ◽  
H. Y. Zhou

2021 ◽  
Author(s):  
Yong-Ting Liu ◽  
Yi-Ming Wu ◽  
Fang-Fang Du

Abstract We present a self-error-rejecting multipartite entanglement purification protocol (MEPP) for N-electron-spin entangled states, resorting to the single-side cavity-spin-coupling system. Our MEPP has a high efficiency containing two steps. One is to obtain high-fidelity N-electron-spin entangled systems with error-heralded parity-check devices (PCDs) in the same parity-mode outcome of three electron-spin pairs, as well as M-electron-spin entangled subsystems (2 ≤ M < N) in the different parity-mode outcomes of those. The other is to regain the N-electron-spin entangled systems from M-electron-spin entangled states utilizing entanglement link. Moreover, the quantum circuits of PCDs make our MEPP works faithfully, due to the practical photon-scattering deviations from the finite side leakage of the microcavity, and the limited coupling between a quantum dot and a cavity mode, converted into a failed detection in a heralded way.


2021 ◽  
Vol 18 (6) ◽  
pp. 065205
Author(s):  
Cheng-Chen Luo ◽  
Lan Zhou ◽  
Wei Zhong ◽  
Yu-Bo Sheng

1999 ◽  
Author(s):  
Konstantin K. Likharev ◽  
P. Bunyk ◽  
W. Chao ◽  
T. Filippov ◽  
Y. Kameda
Keyword(s):  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Israel F. Araujo ◽  
Daniel K. Park ◽  
Francesco Petruccione ◽  
Adenilton J. da Silva

AbstractAdvantages in several fields of research and industry are expected with the rise of quantum computers. However, the computational cost to load classical data in quantum computers can impose restrictions on possible quantum speedups. Known algorithms to create arbitrary quantum states require quantum circuits with depth O(N) to load an N-dimensional vector. Here, we show that it is possible to load an N-dimensional vector with exponential time advantage using a quantum circuit with polylogarithmic depth and entangled information in ancillary qubits. Results show that we can efficiently load data in quantum devices using a divide-and-conquer strategy to exchange computational time for space. We demonstrate a proof of concept on a real quantum device and present two applications for quantum machine learning. We expect that this new loading strategy allows the quantum speedup of tasks that require to load a significant volume of information to quantum devices.


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