Master equation — The information gain minimum approximation
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Abstract
Approximate time-dependent solutions of a master equation having unique stationary solution can be obtained by minimizing the information gain functional subject to constraints for mean values of a number of chosen observables. We study mathematical properties of such an approximation. We find the region of applicability, prove that the approximate solutions are globally asymptotically stable, and show how the approximation is related to some exact integrodifferential equation governing the time evolution of the mean values of the chosen observables.
Keywords
Spectroscopy Neural Network State Physics Complex System Time Evolution
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© Springer-Verlag 1987