PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
May 10, 20260 citationsOpen Access

Emergent Relational Geometrodynamics: Dynamical Self-Organization of Newtonian Scaling in Adaptive Networks with Curvature Constraints

View Full Paper
JTJuan Carlos Alves Tabernero

Key Points

  • This research aims to explore how adaptive networks can self-organize under curvature constraints, reflecting mechanisms in scalar-tensor gravity.
  • Introduced a dynamical extension of the Emergent Relational Geometrodynamics program.
  • Used numerical simulations to analyze the network evolution with local rewiring moves.
  • Examined the effects of the curvature penalty and connectivity on network structure.
  • The effective decay exponent of the scalar field converges to approximately γ=1.
  • The mean ratio L/⟨λ⟩ stabilizes at the critical value of 44 as found in static models.
  • Curvature constraints successfully prevent dimensional collapse and support a three-dimensional effective geometry.

Abstract

We introduce a dynamical extension of the Emergent Relational Geometrodynamics program in which the interaction range of each node depends adaptively on its local connectivity, thereby mimicking the chameleon screening mechanism of scalar‑tensor gravity. The network evolves through local rewiring moves that minimise a structural energy functional combining field‑induced tension with a curvature penalty that penalises low clustering. Numerical simulations demonstrate that the system spontaneously self‑organises into a configuration where the effective decay exponent of the scalar field approaches the Newtonian value γ≈1γ≈1 without any externally imposed interaction scale. The mean ratio L/⟨λ⟩L/⟨λ⟩ stabilises precisely at the critical value 44 identified in earlier static network models, while the curvature term successfully prevents dimensional collapse and preserves a three‑dimensional effective geometry. These findings indicate that Newtonian gravity can arise as a dynamical attractor in discrete relational systems and provide a direct conceptual link with the chameleon mechanism in the continuum.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Juan Carlos Alves Tabernero (2026) studied this question.

synapsesocial.com/papers/6a002222c8f74e3340f9d0f3https://doi.org/10.5281/zenodo.20088534
Ask AI
Helpful
Bookmark
Share
View Full Paper