Quantum Entropies of Non-Probabilistic Square Matrices

Guy Jumarie

Naohumi Muraki, Masanori Ohya, Dėnes Petz

Guy Jumarie

The quantum mechanical entropy of density matrices defined by Von Neumann in quantum physics has been generalized in the form of quantum entropy of non-probabilistic matrices, and it is shown that the latter can be of some use in automatic control. This quantum entropy can be thought of as a measure of structure complexity and its application is quite relevant and meaningful in the following topics: stability of linear and non-linear systems, robustness and order reduction. Quantum entropy appears to be a new weighted combination of eigenvalues which would allow us to re-examine some problems with new points of view relating to information theory without probability.

Guy Jumarie

Von Neumann defined the informational entropy of a density matrix ρ by the expression S(ρ)=−tr(ρ ln ρ). [J. Von Neumann, Die Mathematischen Grundlagen der Quantummechanik (Springer-Verlag, Berlin, 1932)]. Here, starting from the definitions of Shannon entropy and of Renyi entropy of random variables, and using some (reasonable) rules of inference, two expressions are obtained for the quantum entropy of a given square (deterministic) matrix, irrespective of any probabilistic framework and/or any randomization technique. These definitions apply directly to linear operators on Hilbert spaces even when they are not of positive trace class, and they contain Von Neumann entropy as a special case. These new measures of uncertainty could provide new approaches to some problems related to structure complexity.

Masanori Ohya

Adriana Paula Batista dos Santos, R. Silva, J. S. Alcaniz +1 more