2021/05/31 by Yizhou Liu, John B. DeBrota
Computer Science · Mathematics · Physics and Astronomy · #Computer science #Data mining #Disturbance (geology) #Hilbert space #Mathematics #Measure (data warehouse) #Open quantum system #Operator (biology) #Orthogonality #Orthonormal basis #POVM #Pairwise comparison #Physics #Pure mathematics #Quantum #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #Quantum Mechanics and Applications #Quantum mechanics #Quantum operation #Quantum state #SIC-POVM #Statistics #quant-ph
paper · pdf · doi:10.1103/physreva.104.052216
8 pages, 0 figure
arxiv created 2021/11/18 · openalex publication_date 2021/11/22 · arxiv updated 2021/11/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
In the general theory of quantum measurement, one associates a positive-semidefinite operator on a d-dimensional Hilbert space to each of the n possible outcomes of an arbitrary measurement. In the special case of a projective measurement, these operators are pairwise Hilbert-Schmidt orthogonal, but when n>d, orthogonality is restricted by positivity. This restriction allows us to more precisely state the quantum adage: information gain of a system is always accompanied by unavoidable disturbance. Specifically, we investigate three properties of a measurement with L"uders rule updating: its disturbance, a measure of how the expected postmeasurement state deviates from the input; its measurement strength, a measure of the intrinsic information producing capacity of the measurement; and its orthogonality, a measure of the degree to which the measurement operators differ from an orthonormal set. These quantities satisfy an information-disturbance tradeoff relation that highlights the additional role played by orthogonality. Finally, we assess several classes of measurements on these grounds and identify symmetric informationally complete quantum measurements as the unique quantum analogs of a perfectly informative and nondisturbing classical ideal measurement.