2010/07/31 by Gael Sentís, G. Sentís, E. Bagan +5
Computer Science · Engineering · Physics and Astronomy · #A priori and a posteriori #Algorithm #Computer science #Engineering #Limiting #Physics #Quantum #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #Quantum Mechanics and Applications #Quantum mechanics #Quantum state #Qubit #State (computer science) #Task (project management) #quant-ph
paper · pdf · doi:10.1103/physreva.82.042312
published as Phys. Rev. A 82, 042312 (2010) · Based on version published in Physical Review A, some errors in appendix A corrected. 13 pages, 4 figures
openalex publication_date 2010/10/15 · arxiv created 2011/03/15 · arxiv updated 2015/05/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Quantum state discrimination is a fundamental primitive in quantum statistics where one has to correctly identify the state of a system that is in one of two possible known states. A programmable discrimination machine performs this task when the pair of possible states is not a priori known but instead the two possible states are provided through two respective program ports. We study optimal programmable discrimination machines for general qubit states when several copies of states are available in the data or program ports. Two scenarios are considered: One in which the purity of the possible states is a priori known, and the fully universal one where the machine operates over generic mixed states of unknown purity. We find analytical results for both the unambiguous and minimum error discrimination strategies. This allows us to calculate the asymptotic performance of programmable discrimination machines when a large number of copies are provided and to recover the standard state discrimination and state comparison values as different limiting cases.