DocumentCode :
1474127
Title :
Methods for Estimating Capacities and Rates of Gaussian Quantum Channels
Author :
Pilyavets, Oleg V. ; Lupo, Cosmo ; Mancini, Stefano
Author_Institution :
School of Science and Technology, Physics Division, University of Camerino, Camerino, Italy
Volume :
58
Issue :
9
fYear :
2012
Firstpage :
6126
Lastpage :
6164
Abstract :
Optimization methods aimed at estimating the capacities of a general Gaussian channel are developed. Specifically evaluation of classical capacity as maximum of the Holevo information is pursued over all possible Gaussian encodings for the lossy bosonic channel, but extension to other capacities and other Gaussian channels seems feasible. Solutions for both memoryless and memory channels are presented. It is first dealt with single-use (single-mode) channel where the capacity dependence on channel´s parameters is analyzed providing the full classification of possible cases. Then, it is dealt with multiple uses (multimode) channel where the capacity dependence on the (multimode) environment state is analyzed when both total environment energy and environment purity are fixed. This allows a fair comparison among different environments, thus understanding the role of memory (intermode correlations) and phenomenon like superadditivity of the capacity. The developed methods are also used for deriving transmission rates with heterodyne and homodyne measurements at the channel output. Classical capacity and transmission rates are presented within a unique framework where the rates can be treated as logarithmic approximations of the capacity.
Keywords :
Additives; Approximation methods; Channel capacity; Covariance matrix; Eigenvalues and eigenfunctions; Quantum mechanics; Vectors; Classical capacity of quantum channels; Gaussian quantum channels; classical transmission rates of quantum channels; quantum information;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.2012.2191475
Filename :
6172235
Link To Document :
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