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Structure of optimal state discrimination in generalized probabilistic theories
Citation
Bae, J., Kim, D.-G., & Kwek, L.-C. (2016). Structure of optimal state discrimination in generalized probabilistic theories. Entropy, 18(2), Article 39. https://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.
Date Issued
2016
Publisher
MDPI
Journal
Entropy