Fundamentals of Quantum Mutual Entropy and Capacity

Nilanjana Datta

Masanori Ohya

The study of mutual entropy (information) and capacity in classica l system was extensively done after Shannon by several authors like Kolmogor ov and Gelfand. In quantum systems, there have been several definitions of t he mutual entropy for classical input and quantum output. In 1983, the autho r defined the fully quantum mechanical mutual entropy by means of the relati ve entropy of Umegaki, and he extended it to general quantum systems by the relative entropy of Araki and Uhlmann. When the author introduced the quantu m mutual entropy, he did not indicate that it contains other definitions of the mutual entropy including classical one, so that there exist several misu nderstandings for the use of the mutual entropy (information) to compute the capacity of quantum channels. Therefore in this note we point out that our quantum mutual entropy generalizes others and where the m isuse occurs.

Makoto Ohya, D�nes Petz

Noborn Watanabe

In communication processes, a channel has an activity to communicate information of input system to output system. The mutual entropy (information) denotes an amount of information transmitted correctly from the input system to the output system through a channel. The (semi‐classical) mutual entropies for classical input and quantum output were defined by several researchers. The fully quantum mutual entropy, which is called Ohya mutual entropy, for quantum input and output by using the relative entropy was defined by Ohya in 1983, and he extended it to general quantum systems by means of the relative entropy of Araki and Uhlmann. The capacity shows the ability of the information transmission of the channel, which is used as a measure for construction of channels. The fully quantum capacity is formulated by taking the supremum of Ohya mutual entropy with respect to a certain subset of the initial state space. One of the most important theorems in quantum communication theory is coding theorem. The quantum coding theorems are discussed by using the mutual entropy — type measures introduced in the studies of quantum information.In this paper, we compare with these mutual entropy‐type measures in order to obtain most suitable one for discussing the quantum coding theorem. We concretely calculate the quantum capacity for quantum channels.

Subhash C. Kak

Noborn Watanabe

Adaptive Dynamics and Its Applications to Chaos and NPC Problem Quantum Algorithm for SAT Problem and Quantum Mutual Entropy New Quantum Algorithm for Studying NP-Complete Problems Entanglement, Quantum Entropy and Mutual Information Fundamentals of Quantum Mutual Entropy and Capacity Compound Channels, Transition Expectations, and Liftings Complexities and Their Applications to Characterization of Chaos Complexity, Fractal Dimension for Quantum States Information Dynamics and Its Applications to Optical Communication Processes Information Theoretical Treatments of Genes Some Aspects of Quantum Information Theory and Their Applications to Irreversible Processes On Compound State and Mutual Information in Quantum Information Theory Note on Quantum Probability Quantum Ergodic Channels in Operator Algebras On Open System Dynamics -- An Operator Algebraic Study Dynamical Process in Linear Response Theory Stability of Weiss Ising Model and other papers.