scholarly journals Simulation of Gaussian channels via teleportation and error correction of Gaussian states

2018 ◽  
Vol 98 (5) ◽  
Author(s):  
Spyros Tserkis ◽  
Josephine Dias ◽  
Timothy C. Ralph
2017 ◽  
Vol 118 (16) ◽  
Author(s):  
Giacomo De Palma ◽  
Dario Trevisan ◽  
Vittorio Giovannetti

2016 ◽  
Vol 15 (6) ◽  
pp. 2441-2453 ◽  
Author(s):  
Zhong-Xiao Wang ◽  
Shuhao Wang ◽  
Qiting Li ◽  
Tie-Jun Wang ◽  
Chuan Wang

Entropy ◽  
2021 ◽  
Vol 23 (9) ◽  
pp. 1190
Author(s):  
Liang Liu ◽  
Jinchuan Hou ◽  
Xiaofei Qi

Generally speaking, it is difficult to compute the values of the Gaussian quantum discord and Gaussian geometric discord for Gaussian states, which limits their application. In the present paper, for any (n+m)-mode continuous-variable system, a computable Gaussian quantum correlation M is proposed. For any state ρAB of the system, M(ρAB) depends only on the covariant matrix of ρAB without any measurements performed on a subsystem or any optimization procedures, and thus is easily computed. Furthermore, M has the following attractive properties: (1) M is independent of the mean of states, is symmetric about the subsystems and has no ancilla problem; (2) M is locally Gaussian unitary invariant; (3) for a Gaussian state ρAB, M(ρAB)=0 if and only if ρAB is a product state; and (4) 0≤M((ΦA⊗ΦB)ρAB)≤M(ρAB) holds for any Gaussian state ρAB and any Gaussian channels ΦA and ΦB performed on the subsystem A and B, respectively. Therefore, M is a nice Gaussian correlation which describes the same Gaussian correlation as Gaussian quantum discord and Gaussian geometric discord when restricted on Gaussian states. As an application of M, a noninvasive quantum method for detecting intracellular temperature is proposed.


Author(s):  
Elmostafa ATIFY ◽  
Cherki DAOUI ◽  
Ahmed BOUMEZZOUGH

As part of a detailed study on blind identification of Gaussian channels, the main  purpose was  to propose an algorithm based on cumulants and  fuzzy number approach  involved throughout the whole process of identification. Our objective was to compare the new design of the algorithm to the old one using the  higher order cumulants, namely  Alg1, Algat  and the Giannakis  algorithm. We were  able to demonstrate that the proposed method -fuzzy number error correction- increases the performance of the algorithm by calculating the ratio of squared errors of ALGaT and  AlgatF. The method can be applied to any algorithm for more improvement and effinciency.


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