Abstract
It is shown that a number of optimization problems in quantum information theory: the \(\chi\)-capacity (called the Holevo capacity in literature) of a quantum channel; the classical capacity of quantum observable; entanglement of formation—can be recast as a generalization of a Bayes problem over the set of all quantum states. This allows us to consider it as a convex programming problem for which necessary and sufficient optimality conditions along with the dual problem can be formulated.
Similar content being viewed by others
REFERENCES
A. S. Holevo, Quantum Systems, Channels, Information: A Mathematical Introduction, 2nd ed. (De Gruyter, Berlin, 2019).
A. S. Holevo and M. E. Shirokov, ‘‘Continuous ensembles and the capacity of infinite-dimensional quantum channels,’’ Theory Probab. Appl. 50, 86–98 (2005).
A. S. Holevo, ‘‘Statistical decision theory for quantum systems,’’ J. Multivariate Anal. 3, 337–394 (1973).
A. S. Holevo, ‘‘On a vector-valued integral in the noncommutative statistical decision theory,’’ J. Multivariate Anal. 5, 462–465 (1975).
A. S. Holevo, ‘‘Studies in general theory of statistical decisions,’’ Proc. Steklov Math. Inst. 124 (1978).
D. G. Luenberger, Optimization by Vector Space Methods (Wiley, New York, 1969).
M. E. Shirokov, ‘‘On properties of the space of quantum states and their application to construction of entanglement monotones,’’ Izv.: Math. 74, 849–882 (2010).
Funding
This work is supported by Russian Science Foundation under the grant no. 19-11-00086, https://rscf.ru/project/19-11-00086/. The author is grateful to M. E. Shirokov for useful remarks.
Author information
Authors and Affiliations
Corresponding author
Additional information
(Submitted by A. M. Elizarov)
Rights and permissions
About this article
Cite this article
Holevo, A.S. On Optimization Problem for Positive Operator-Valued Measures. Lobachevskii J Math 43, 1646–1650 (2022). https://doi.org/10.1134/S1995080222100158
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1134/S1995080222100158