The information hidden in Markov diffusion. Este artículo no está disponible.The information hidden in Markov diffusion

We study emergence of quantum, dynamic information, and arising an information observer under impulse interactive actions in Markov diffusion process modeling random environment. The interactive delta-impulse of Markov diffusion process cuts the process correlation revealing hidden information connecting the process inner states. Information appears as phenomenon of interactions. The impulse probing probabilities, observing random process under Kolmogorov’s 1-0 law, link Bayesian probabilities that increases each posterior correlation and reduces conditional entropy measures up to cutting this entropy by high probable impulse. Cutting random process correlation, covering the interactive internal events, reveals underneath both hidden quantum and classical information. The cutting entropy sequentially converts to information and memorizes the impulse probabilistic logic in bits, which participates in next conversions and encoding. The impulse step-down action cuts a maximum of impulse’ minimal uncertainty-entropy, and the impulse’ step-up action transforms the cutting portion to ending impulse state, where it kills the uncertainty, delivering the equal minimax information.

We study emergence of quantum, dynamic information, and arising an information observer under impulse interactive actions in Markov diffusion process modeling random environment. The interactive delta-impulse of Markov diffusion process cuts the process correlation revealing hidden information connecting the process inner states. Information appears as phenomenon of interactions. The impulse probing probabilities, observing random process under Kolmogorov’s 1-0 law, link Bayesian probabilities that increases each posterior correlation and reduces conditional entropy measures up to cutting this entropy by high probable impulse. Cutting random process correlation, covering the interactive internal events, reveals underneath both hidden quantum and classical information. The cutting entropy sequentially converts to information and memorizes the impulse probabilistic logic in bits, which participates in next conversions and encoding. The impulse step-down action cuts a maximum of impulse’ minimal uncertainty-entropy, and the impulse’ step-up action transforms the cutting portion to ending impulse state, where it kills the uncertainty, delivering the equal minimax information.