Data Set for Kilgore Field Theory: A Dynamic Framework for Consciousness as Information Differentiation

This archive contains all artifacts needed to reproduce the paper’s results across Series A–F. It includes parameterized run cards (governing equations, grids, seeds, and sweeps), CSV metrics for key measures (E(t), S(t), k*, Δk, drift u, ω_meas, v_p, v_g, PSD angle θ_PSD, elongation ρ), figure sources, and environment manifests/lockfiles for exact versions. Minimal scripts are provided to execute the run cards, with a mapping table linking every figure to its originating run and outputs; select logs are included for diagnostics. The data cover baseline behavior, noise-as-signal, the continuity threshold λ*, dispersion validation, drift/anisotropy separation, and convergence/robustness checks across seeds and resolutions. Quantities are dimensionless unless noted; symbol definitions appear in the Methods. Reproduction requires Python with the packages listed in manifests/Executing the provided runner regenerates the metrics and figures.