I.M.E. Theory – Transformation of Information into Energy through Conscious Observation

The I.M.E. Theory (Information–Mass–Energy), introduced by Anastasios Tsikriteas, proposes a unifying mathematical equation that links the dynamic change of information entropy to energy activation—specifically under conditions of observation. Inspired by Landauer’s thermodynamic principle and quantum collapse, the theory introduces a transformation function C(t), which modulates energy expression based on the rate of change in observed information (−dSᵢ/dt). The core equation:dE/dt = γ × (−dSᵢ/dt) × C(t)is experimentally supported through simulations showing that the same informational stimulus leads to different energy responses depending on whether it is observed or not.This updated version (v2) integrates:computational modeling of entropy-driven energy activation,synthetic EEG-based variables such as Alpha power and P300 triggers,and statistical correlations with conscious perception moments.The theory enables new methods in:BCI signal interpretation,AI observation triggers,and the quantification of consciousness.The preprint includes full Python-based implementations and visual diagrams that demonstrate the transformation from informational entropy collapse to measurable energy activation.