Decision-Making in Quantum State Discrimination

Quantum state discrimination involves finding the best measurement to distinguish between quantum states in a given set. Typically, one wants the POVM which produces the minimal amount of error, or the maximal amount of confidence. We show that this task can easily be cast as an example of Bayesian experimental design, which makes explicit the decision process involved when discriminating between states. This highlights the common implicit assumption that the agent simply decides on the state indicated by the measurement outcome. This naive decision leads to anomalous results, which are resolved when using the optimal decision strategy. Further we generalise state discrimination to POVMs with an arbitrary number of elements, and generalise some well-known results.