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March 8, 20260 citationsOpen Access

GRAVITY AS PROCESSING LATENCY Deriving the Equivalence Principle and Spacetime Curvature from Local Information Density

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AYAli Caner Yücel

Key Points

  • This research explores how gravity can be derived from local information processing and its implications on spacetime.
  • Developed a phenomenological theory linking gravity to information capacity.
  • Introduced a scalar quantifying information-load relative to causal-patch capacity.
  • Used a conformal metric to derive equations analogous to Newtonian gravity and PPN parameters.
  • Gravity is linked to local information density and processing capabilities.
  • Derivations produced equations equivalent to the Newtonian potential and Poisson kernel.
  • The study discusses implications for cosmology and the concept of an informational dark sector.

Abstract

We present a covariant, phenomenological theory in which gravity — observed as proper-time slowing and acceleration — emerges from finite local information-processing capacity. A dimensionless information-load scalar quantifies the ratio of relevant local bits to causal-patch capacity. We introduce a conformal metric ansatz and show how (i) Landauer’s principle together with holographic scaling reproduce the Newtonian potential in the weak field; (ii) a covariant scalar-field action for coupled to a matter-information scalar yields field equations equivalent to a Poisson kernel in the static limit; (iii) the linearized metric recovers Parametrized Post-Newtonian (PPN) parameters at displayed order; and (iv) black holes are interpretable as saturation regions — a “Null Pointer Singularity” (NPS). We define an informational energy density via a generalized Yücel–Landauer relation, discuss cosmological embedding (an effective informational dark sector), and provide observational and numerical tests. The framework is explicit about phenomenological choices and delineates a clear program to derive microphysics and confront data.

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Cite This Study

Ali Caner Yücel (2026) studied this question.

synapsesocial.com/papers/69acc57d32b0ef16a404fc29https://doi.org/10.5281/zenodo.18886788
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