IDEAS home Printed from https://ideas.repec.org/p/osf/osfxxx/ucavd_v1.html
   My bibliography  Save this paper

The Persistence Equation as a Unified Predictive Framework: From Molecular Systems to Cosmology

Author

Listed:
  • Giannakopoulos, Bill Doctor

    (University of New South Wales)

Abstract

The Persistence Equation was originally developed to model structural resilience in biological and cognitive systems under entropic stress. However, its applicability extends far beyond. In this paper, we argue that the Persistence Equation — built from core principles of reversibility, entropy, adaptability, and fragility — represents a minimal and scalable formalism that can model phenomena from molecular redox biology to gravitational singularities, dark matter, and cosmic acceleration. We present its trajectory of application, demonstrate how it resolves core cosmological features without invoking new physics, and propose that, with further refinement, it may offer the most parsimonious and epistemically justified predictive framework available across disciplines.

Suggested Citation

  • Giannakopoulos, Bill Doctor, 2025. "The Persistence Equation as a Unified Predictive Framework: From Molecular Systems to Cosmology," OSF Preprints ucavd_v1, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:ucavd_v1
    DOI: 10.31219/osf.io/ucavd_v1
    as

    Download full text from publisher

    File URL: https://osf.io/download/67ecbbabe630351c766ddc7f/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/ucavd_v1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:osf:osfxxx:ucavd_v1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: OSF (email available below). General contact details of provider: https://osf.io/preprints/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.