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This directory contains simulation frameworks designed to test, validate, and explore predictions of Recurgent Field Theory (RFT) across multiple domains. The simulation architectures translate RFT’s mathematical formalism into computational models that generate testable predictions and empirical results.

Simulation Philosophy

The simulation architectures here value:

  1. Theoretical Fidelity: Models maintain rigorous correspondence to underlying RFT mathematics and mechanics.
  2. Empirical Testability: Simulations produce clear, measurable predictions that can be compared against observational data.
  3. Reproducibility: All architectures are documented and designed for transparency.
  4. Progressive Refinement: Simulations evolve through systematic exploration, parameter optimization, and model extension.

Current Architectures

001: RFT Galactic Dynamics

A simulation modeling galactic rotation curves using RFT’s semantic mass formalism rather than conventional particle dark matter. Demonstrates how emergent semantic structures can account for gravitational anomalies at galactic scales.

Key features:

  • Parametric models for recursive depth (D), constraint density (ρ), and attractor stability (A)
  • Direct comparison with standard dark matter halo models
  • Systematic parameter space exploration
  • Quantitative error metrics against observational targets

Results show RFT can reproduce observed galactic rotation curves with high precision, outperforming conventional dark matter models in fitting accuracy.

Note: All simulation results should be interpreted in the context of the broader Recurgent Field Theory framework as a whole, detailed in the Mathematics section.