We present the Unified Informational Theory of Emergent Spacetime (IVES), a self-consistent theoretical framework in which spacetime, gravity, and cosmological dynamics arise as macroscopic manifestations of an underlying irreversible informational substrate. In this formulation, the fundamental degrees of freedom are an informational density field and a causal flow vector, governed by conservation, covariance, and intrinsic entropy production.The framework extends relativistic hydrodynamics by incorporating causal bulk viscosity (Israel–Stewart dynamics) and a constrained torsional sector, both emerging as effective descriptions of non-equilibrium informational flow. Within this structure, Einstein’s field equations are recovered as a thermodynamic limit of horizon entropy balance, while cosmological acceleration emerges naturally from late-time viscous relaxation of the informational medium.The model predicts a two-phase cosmological evolution, transitioning from a dust-like regime at high redshift to an effective dark-energy phase at low redshift, without introducing a fundamental cosmological constant. Linear perturbation analysis yields a scale-dependent effective gravitational coupling, leading to suppressed structure growth (S₈ reduction) and potential alleviation of current cosmological tensions. Additionally, the framework provides nonsingular black hole interiors via viscous defocusing and predicts a matter–information conversion mechanism in extreme curvature regimes, ensuring global conservation of information.The theory is formulated as a closed effective field theory with a variational principle, causal dissipative dynamics, and a well-defined quantum extension characterized by positive spectral density and analytic retarded propagators. These properties ensure stability, unitarity, and consistency at both classical and semiclassical levels.IVES thus offers a unified description in which spacetime geometry, gravitational dynamics, and cosmological phenomena are emergent consequences of irreversible information flow.
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Mikheil Rusishvili
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Mikheil Rusishvili (Sun,) studied this question.
www.synapsesocial.com/papers/69eb0bfa553a5433e34b5761 — DOI: https://doi.org/10.5281/zenodo.19700538