PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 2, 20260 citationsOpen Access

Effective Geometry, Coarse-Graining, and the Non-Fundamental Quantization of Gravity in a Recursive Geometric Framework

View Full Paper
JSJean Santillana

Key Points

  • The research aims to connect cosmology and gravity through a framework that emphasizes emergent properties rather than fundamental quantization.
  • Develop a framework based on Recursive Geometric Field and Unified Model of Creation and Reality.
  • Interpret gravitational dynamics through emergent, coarse-grained spacetime descriptions.
  • Analyze consistency with observational cosmology and structure growth.
  • Clarified the role of coarse-graining scales in gravity.
  • Identified conditions under which quantum gravitational phenomena manifest.
  • Established a coherent pathway linking cosmology, effective geometry, and semiclassical gravity.

Abstract

We develop a balanced effective framework connecting late--time cosmology, emergent gravity, and the conceptual foundations of quantum gravity. Building upon the Recursive Geometric Field (RGF) and the Unified Model of Creation and Reality (UMCR), we interpret gravitational dynamics as an emergent, coarse--grained description of a pre--dynamical geometric organization of spacetime. Within this perspective, gravity need not be fundamentally quantized, while quantum field theory in curved spacetime and the effective field theory of General Relativity remain fully valid within their domains of applicability. We clarify the role of coarse--graining scales, establish consistency with observational cosmology, and identify the regime in which quantum gravitational phenomena are expected to arise. The framework does not provide a microscopic theory of quantum gravity, but delineates a coherent and falsifiable pathway—through late--time cosmological observables and structure growth—linking cosmology, effective geometry, and semiclassical gravity.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Jean Santillana (2026) studied this question.

synapsesocial.com/papers/6980ff08c1c9540dea811afbhttps://doi.org/10.5281/zenodo.18436171
Ask AI
Helpful
Bookmark
Share
View Full Paper