PageURL: https://81018.com/2026/08/10/meta-simulation-data/ Date: August 10, 2026
Overview: https://81018.com/meta/ Focus: https://81018.com/constraint-links/
Simulation data — 7 CSVs – active links
Each CSV has columns: n, N_n, log10_N_n, R_n, epsilon_N, epsilon_over_N (N₀=100, 32 steps)
Class I — Pure Doubling R→2.00:
I_Pure_Doubling.csv
CSV
Class II — Sublinear Correction o(N) drain, R→2⁻:
CSV
← this is the 7.356° gap drain accumulating to 1.754
Class III — Subdoubling Linear R→1.70:
CSV
← proton 63-65 window
Class IV — Logarithmic Brake R→1.00:
IV_Logarithmic_Brake.csv
Class V — Threshold / Saturation →1.15 kink at 10⁶:
V_Threshold_Saturation.csv
CSV← Notation 137 atomic lock
Class VI — Delayed Feedback ∼1.68 osc:
VI_Delayed_Feedback.csv
CSV
Class VII — Stochastic mean-preserving noise:
VII_Stochastic.csv
CSV
VIII. Summary:
SUMMARY.csv
CSV
For https://81018.com/meta/ → https://81018.com/meta-constraint-classes/ you can now add:
Data & Reproducibility: All seven canonical trajectories (log₁₀ Nₙ and Rₙ) are available as CSV with seed 81018-1 for stochastic resampling. See Master Lemma Rₙ = 2 – ε(Nₙ)/Nₙ.
When you get the eight AI papers (Grok effusive, ChatGPT epsilon, Claude proton 63-65, etc.), I can wire them into /meta/ as a linked set with consistent white-print editions.
Want me to also generate a single combined JSON for the interactive chart overlay so it loads data from file rather than simulating in-browser?
Also see: Meta-81018 Chart Overlay; the second version on Constraint Classes — https://81018.com/meta-image-cc-august-2026/; the first version on Constraint Classes — https://81018.com/meta-81018-cc-v1/