Title :
Identifying the Information Gain of a Quantum Measurement
Author :
Berta, Mario ; Renes, Joseph M. ; Wilde, Mark M.
Author_Institution :
Inst. for Theor. Phys., ETH Zurich, Zurich, Switzerland
Abstract :
We show that quantum-to-classical channels, i.e., quantum measurements, can be asymptotically simulated by an amount of classical communication equal to the quantum mutual information of the measurement, if sufficient shared randomness is available. This result generalizes Winter´s measurement compression theorem for fixed independent and identically distributed inputs to arbitrary inputs, and more importantly, it identifies the quantum mutual information of a measurement as the information gained by performing it, independent of the input state on which it is performed. Our result is a generalization of the classical reverse Shannon theorem to quantum-to-classical channels. In this sense, it can be seen as a quantum reverse Shannon theorem for quantum-to-classical channels, but with the entanglement assistance and quantum communication replaced by shared randomness and classical communication, respectively. The proof is based on a novel one-shot state merging protocol for classically coherent states as well as the postselection technique for quantum channels, and it uses techniques developed for the quantum reverse Shannon theorem.
Keywords :
information theory; quantum communication; quantum theory; Winter measurement compression theorem; classical communication; classical reverse Shannon theorem; entanglement assistance; information gain; one-shot state merging protocol; postselection technique; quantum channel; quantum communication; quantum measurement; quantum mutual information; quantum reverse Shannon theorem; quantum-to-classical channel; sufficient shared randomness; Entropy; Extraterrestrial measurements; Gain measurement; Hilbert space; Merging; Protocols; Quantum mechanics; Channel Simulation; Measurement Compression; Quantum Measurement; Quantum Shannon Theory; Quantum measurement; Reverse Shannon Theorem; channel simulation; measurement compression; quantum Shannon theory; reverse Shannon theorem;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2014.2365207