Emergence time, curvature, space, causality, and complexity in encoding a discrete impulse information process

Abstract

Interacting random field of probabilities links Kolmogorov law 0-1 and Bayesian probabilities observing Markov diffusion process under Yes-No actions of random impulse. These objective probabilities measure virtual probing impulses processing the interactions in observable process. The impulse observation increases each posteriori correlation reducing conditional entropy measures from finite uncertainty up to certainty of real impulse. The reduced entropy conveys probabilistic causality with time course and temporal memory in collecting correlations, which interactive impulse innately cuts exposing hidden process entropy. The natural cut of this entropy reveals information hidden in the correlation connections. Inside the merging probing impulse emerges reversible microprocess with yes-no conjugated entangled entropy, curvature and logical complexity. Within the impulse time interval, entanglement starts before its space is formed and ends with beginning the space during reversible relative time interval being small part of impulse time interval. Merging impulse curves and rotates the impulse interactive actions in microprocess whose space interval measures this transitive movement.The cutting entropy sequentially converting to information memorizes the probes logic in Bit, participating in next probe conversions and encoding which memorizes information causality. The complexity and mass appears after the space emerges from the entanglement.The cognition assembles common units through the multiple attraction and resonances at forming network (IN) of triplet hierarchy, which accept only units that concentrates and recognizes each triplet IN node. The ended triplet of hierarchical INs measures level of the observer intelligence. The synthesized optimal process minimizes the observations time in Artificial designed information Observer with intellectual searching logic.