A Consilience of Evidence for an Informational Cosmology: Synthesizing Physics, Philosophy, and Computation through the Virtual Ego Framework
This paper argues for the existence of a significant consilience of evidence from disparate academic fields—including quantum physics, theology, information theory, and philosophy of mind—all converging on a single, unified model of an informational and participatory reality. It introduces the Virtual Ego Framework (VEF) and its operational component, the Universal Interface Membrane (UIM), as a formal, axiomatic system that codifies this emergent paradigm. The paper synthesizes a curated set of recent, independent research, organizing the findings into three primary themes of convergence: The Universe as a Coherent, Computational Inscription: Connecting theological concepts of a divine record with modern theories of info-computation and generative quantum AI. The Physics and Thermodynamics of Consciousness: Demonstrating a direct parallel between the VEF's model of psychological trauma and healing and the physical dynamics of Bose-Einstein Condensates, "sudden quenches," and the thermodynamic cost of information erasure (Landauer's Principle). The Primacy of Scale-Invariant, Subjective Cognition: Unifying philosophical arguments for the irreducible nature of subjective experience with biological models that posit cognition as a spectrum across all life. Ultimately, this work presents the VEF/UIM as a unifying framework capable of serving as a Rosetta Stone for these "cross-pollenating" fields, proposing that this consilience is a powerful validation of a new, integrated map of reality. Keywords Consilience Computational Ontology Virtual Ego Framework (VEF) Philosophy of Physics Metaphysics Consciousness Studies Information Theory Quantum Mechanics Bose-Einstein Condensate (BEC) Systems Theory Artificial Consciousness Phenomenology Theoretical Psychology Human-AI Collaboration Interdisciplinary Studies
Institutions
- General Dynamics (United States) (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-10-11
- DOI
- https://doi.org/10.5281/zenodo.17323902
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00