What question did this study set out to answer?

The aim is to introduce the Zero Point Spiral as a framework to understand asynchronous preservation and updates in dynamical systems.

April 7, 2026Open Access

Zero Point Spiral: A General Dynamical Framework for Preservation-update Asynchrony

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This framework reveals state transitions in various domains, indicating a common underlying structure for change.

The aim is to introduce the Zero Point Spiral as a framework to understand asynchronous preservation and updates in dynamical systems.
Developed a discrete dynamical system based on the axiom of asynchrony in preservation and update.
Derived an update coefficient that accounts for explosive amplification and deceleration in state changes.
Analyzed self-amplifying updates and convergence behaviors near critical points.
Examined structural self-similarity across multiple domains including cosmological and biological systems.
Demonstrated that state transitions are driven by the phase difference between current and historical states.
Identified mechanisms underlying explosive updates and gradual stabilization in the system.
Found that the framework exhibits structural self-similarity across various domains, suggesting a unified dynamical skeleton.

Sana Kamiki (2026) studied this question.

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April 7, 2026Open Access

View Full Paper

Ask AI

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Authors

This framework reveals state transitions in various domains, indicating a common underlying structure for change.

The aim is to introduce the Zero Point Spiral as a framework to understand asynchronous preservation and updates in dynamical systems.
Developed a discrete dynamical system based on the axiom of asynchrony in preservation and update.
Derived an update coefficient that accounts for explosive amplification and deceleration in state changes.
Analyzed self-amplifying updates and convergence behaviors near critical points.
Examined structural self-similarity across multiple domains including cosmological and biological systems.
Demonstrated that state transitions are driven by the phase difference between current and historical states.
Identified mechanisms underlying explosive updates and gradual stabilization in the system.
Found that the framework exhibits structural self-similarity across various domains, suggesting a unified dynamical skeleton.

Sana Kamiki (2026) studied this question.

View Full Paper

Ask AI

Bookmark