Please use this identifier to cite or link to this item: http://hdl.handle.net/10497/18166
Title: 
Structure of optimal state discrimination in generalized probabilistic theories
Authors: 
Keywords: 
Optimal state discrimination
Generalized probabilistic theories
Min-entropy
Issue Date: 
2016
Citation: 
Bae, J., Kim, D. G., & Kwek, L. C. (2016). Structure of optimal state discrimination in generalized probabilistic theories. Entropy, 18(2): 39. http://dx.doi.org/10.3390/e18020039
Abstract: 
We consider optimal state discrimination in a general convex operational framework,
so-called generalized probabilistic theories (GPTs), and present a general method of optimal
discrimination by applying the complementarity problem from convex optimization. The method
exploits the convex geometry of states but not other detailed conditions or relations of states and
effects. We also show that properties in optimal quantum state discrimination are shared in GPTs in
general: (i) no measurement sometimes gives optimal discrimination, and (ii) optimal measurement
is not unique.
URI: 
ISSN: 
1099-4300
Other Identifiers: 
10.3390/e18020039
Appears in Collections:Journal Articles

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