Integrating hidden information which is observed and the observer information regularities

TL;DR

This paper introduces a novel framework combining Bayesian entropy measures, impulse controls, and information units to model and compute quantum and classical information processes within an integrated information network.

Contribution

It presents a new model that integrates entropy-uncertainty measures with impulse controls to form stable information structures and networks capable of quantum and classical computation.

Findings

Entropy is reduced through impulse-controlled cuts forming stable information units.

Information path functional (IPF) effectively integrates hidden information contributions.

Information network (IN) performs logical computing, uniting quantum and classical processes.

Abstract

Bayesian integral functional measure of entropy-uncertainty (EF) on trajectories of Markov multi-dimensional diffusion process is cutting off by interactive impulses (controls). Each cutoff minimax of EF superimposes and entangles conjugated fractions in microprocess, enclosing the captured entropy fractions as source of an information unit. The impulse step-up action launches the unit formation and step-down action finishes it and brings energy from the interactive jump. This finite jump transfers the entangled entropy from uncertain Yes-logic to the certain-information No-logic information unit whose measuring at end of the cut kills final entropy-uncertainty and limits unit. The Yes-No logic holds Bit Participator creating elementary information observer without physical pre-law. Cooperating two units in doublet and an opposite directional information unit in triplet forms minimal stable structure. Information path functional (IPF) integrates multiple hidden information contributions along the cutting process correlations in information units of cooperating doublets-triplets, bound by free information, and enfolds the sequence of enclosing triplet structures in the information network (IN) that sequentially decreases the entropy and maximizes information. The IN bound triplets release free information rising information forces enable attracting new information unit and ordering it. While IPF collects the information units, the IN performs logical computing using doublet-triplet code. The IN different levels unite logic of quantum micro- and macro- information processes, composing quantum and/or classical computation.