Measurement incompatibility in Bayesian multiparameter quantum estimation
This paper presents a comprehensive Bayesian framework for multiparameter quantum estimation, demonstrating that measurement incompatibility can at most double the minimum precision loss compared to idealized scenarios, thereby validating individually optimal measurements as efficient benchmarks for practical applications.