DISTINGUISHABILITY MEASURES AND ENTROPIES FOR GENERAL PROBABILISTIC THEORIES

As a part of the construction of an information theory based on general probabilistic theories, we propose and investigate several distinguishability measures and entropies in general probabilistic theories. As their applications, no-cloning theorems, information-disturbance theorems are reformulated, and a bound of the accessible informations is discussed in general probabilistic theories, not resorting to quantum theory. We also propose the principle of equality for pure states which makes general probabilistic theories more realistic, and we discuss the role of entropies as a measure of pureness.