Structure of Optimal State Discrimination in Generalized Probabilistic Theories
- Authors
- Bae, Joonwoo; Kim, Dai-Gyoung; Kwek, Leong-Chuan
- Issue Date
- Feb-2016
- Publisher
- Multidisciplinary Digital Publishing Institute (MDPI)
- Keywords
- optimal state discrimination; generalized probabilistic theories; min-entropy
- Citation
- Entropy, v.18, no.2, pp.1 - 11
- Indexed
- SCIE
SCOPUS
- Journal Title
- Entropy
- Volume
- 18
- Number
- 2
- Start Page
- 1
- End Page
- 11
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/14558
- DOI
- 10.3390/e18020039
- ISSN
- 1099-4300
- 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.
- Files in This Item
-
Go to Link
- Appears in
Collections - COLLEGE OF SCIENCE AND CONVERGENCE TECHNOLOGY > ERICA 수리데이터사이언스학과 > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/14558)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.