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April 5, 20260 citationsOpen Access

Stabilizer Quantum Gravity V: Open-System Cosmology, Stabilization Flow, and Effective Large-Scale Response

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GMGeorge Mallis

Key Points

  • This research explores the effective cosmological framework within the Stabilizer Quantum Gravity program and its implications for large-scale observations.
  • Introduced a global stabilization variable for cosmology
  • Defined the large-scale unsaturated sector in SQG
  • Outlined the effective flow law governing the stabilization
  • Identified how incomplete stabilization leads to a deficit-controlled cosmological correction tensor
  • Proposed modified response kernels for large-scale structure and lensing
  • Established conditions for meaningful deviation from General Relativity in observations

Abstract

This paper forms Part V of the Stabilizer Quantum Gravity (SQG) program, introducing its effective cosmological framework. In SQG, effective geometry arises from the stabilization of an underlying recoverable operator-algebraic substrate. We hypothesize that while local spatial sectors may approach the strongly saturated (Einsteinian) limit, the large-scale cosmological universe may remain in a partially unsaturated regime. Consequently, SQG cosmology is modeled not as a perfectly closed geometric phase, but as an open-system effective regime governed by a global stabilization flow. We introduce a global stabilization variable, define the large-scale unsaturated sector, and outline the corresponding effective flow law. This incomplete large-scale stabilization naturally generates a deficit-controlled cosmological correction tensor, phenomenologically manifesting as modified response kernels for large-scale structure (clustering) and lensing (). The paper does not claim a fully fitted cosmological data model, but rather establishes the rigorous theoretical conditions under which large-scale deviations from General Relativity become observationally meaningful within the SQG architecture, while preserving local recovery of the Einstein limit.

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Cite This Study

George Mallis (2026) studied this question.

synapsesocial.com/papers/69d1fd9ca79560c99a0a3bf1https://doi.org/10.5281/zenodo.19400337
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