2017/07/15 by Kenji Nakahira, Kentaro Kato, Tsuyoshi Sasaki Usuda · 5 citations
Computer Science · Mathematics · Physics and Astronomy · #Algorithm #Bipartite graph #Computer science #Convex optimization #Discrete mathematics #Expression (computer science) #Mathematical optimization #Mathematics #Minimax #Optimization problem #Quantum #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #Quantum Mechanics and Applications #Regular polygon #State (computer science) #quant-ph
paper · pdf · doi:10.1103/physreva.97.022340
published in Physical Review A 97(2) (American Physical Society)
arxiv created 2017/07/15 · openalex publication_date 2018/02/27 · arxiv updated 2018/03/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
We investigate an optimization problem of finding quantum sequential measurements, which forms a wide class of state discrimination problems with the restriction that only local operations and one-way classical communication are allowed. Sequential measurements from Alice to Bob on a bipartite system are considered. Using the fact that the optimization problem can be formulated as a problem with only Alice's measurement and is convex programming, we derive its dual problem and necessary and sufficient conditions for an optimal solution. Our results are applicable to various practical optimization criteria, including the Bayes criterion, the Neyman-Pearson criterion, and the minimax criterion. In the setting of the problem of finding an optimal global measurement, its dual problem and necessary and sufficient conditions for an optimal solution have been widely used to obtain analytical and numerical expressions for optimal solutions. Similarly, our results are useful to obtain analytical and numerical expressions for optimal sequential measurements. Examples in which our results can be used to obtain an analytical expression for an optimal sequential measurement are provided.