ψ-FATA MORGANA v2.1: A Retentive Optical Structure at the Threshold of Form
Year: 2025
Type: article
Abstract: ψ-FATA MORGANA v2.1 presents the first structured analysis of a rare atmospheric inversion event interpreted through the ψ-Architecture framework. The captured frame represents a transitional optical state occurring at the boundary of a temperature inversion, prior to the formation of a classical superior mirage. Instead of following deterministic refractive geometry, the observed structure displays loss of geometric identity, suppression of turbulence deformation, and persistence of form consistent with a Δψ-retentive equilibrium. The event is reconstructed through refractive-gradient stability, stratified inversion analysis, ψ-time (τψ) delay, correlation plateaus, and the ψ-retentive potential. The rarity of the captured moment is characterized by a phenomenologically narrow probability window on the order of 10⁻⁶–10⁻⁷, arising from the combined constraints of inversion flatness (~10⁻²), ultralow turbulence (~10⁻³), geometric alignment (~10⁻¹), and Δψ-minimization timing (~10⁻¹–10⁻²). The manuscript provides a full tri-layer analysis—crest, transitional ψ-band, and collapsing geometry—and establishes testable predictions for future atmospheric ψ-events, including correlation plateau duration, ψ-band flatness, and Δψ-minimum conditions. A structural bridge is outlined between atmospheric ψ-retention and late-universe retentive cosmology, highlighting the scale-independent nature of ψ-equilibrium. Two figures accompany the analysis: • a raw, unprocessed capture of the transitional event, and • an annotated ψ-layer decomposition showing the characteristic three-region retentive profile. This work extends ψ-Architecture into atmospheric optics and establishes ψ-retentive transitions as observable, analyzable, and phenomenologically consistent across physical scales.
Author: Yulia, Logacheva
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7108991052
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