bd2ac7b7be
Implement the countable uncle model from the Cryptarchia spec's counting-only reference rules, and make it the simulator default. Counting rules (uncles.py, measure.py): - Only the first block of a fork (parent on the producer's chain) is referenceable and countable, which makes every reference verifiable from chain data alone. - The reference window is derived from a window-absorption parameter, w_u = W_abs/f slots (W_abs in expected block-intervals, default 10, bounded W_abs <= 0.6*k), replacing the free-standing uncle_window. - Selection skips slots already occupied on the producer's chain and takes at most one uncle per slot. - The measurement pass re-checks every rule per reference and tallies rejections as deep_ref_share. The pre-redesign model is preserved behind --old on tsi-sweep and tsi-verify. Its RNG key is byte-identical to the pre-uncle_model key, so --old bit-reproduces the historical runs. Supporting changes: uncle_model and window_absorption config surface with validation (config.py, constants.py); accuracy closed form over the effective q_u (theory.py); plumbing through tsi.py, epoch.py, sweep.py, blocktree.py, metrics.py, verify.py, figures_pernode.py. Studies and figures: - configs/countable-vs-old.yaml -- delay x U grid, run under both models on the same grid. - configs/absorption-window.yaml -- accuracy vs W_abs at U=1. - scripts/plot_countable_vs_old.py renders fig30-fig33 into reports/tsi/report-figures/. Tests: tests/test_countable_counting.py (7 cases) covering first-fork eligibility, derived-window bounds, occupied-slot exclusion, and per-reference re-checking; extensions to test_uncles.py, test_config.py, test_slot_counting.py. Full fast suite: 202 passed. Also adds CLAUDE.md (graphify project instructions) and ignores editor/local-agent state plus the vendored Equi-X benchmark clone. The reports/tsi/ prose describing this model is held back for a separate editorial pass. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Total-Stake-Inference parameter selection
Per-node network simulation of Cryptarchia Total Stake Inference (TSI). Simulator: tsi-sim-pernode. All runs at the true security parameter k = 2160 unless noted; latency is in slots and 1 slot = 1 s.
This report selects and justifies the TSI parameters for Cryptarchia from a per-node network simulation. It is split into four cohesive parts; section numbers (§1–§9, A–C) are stable identifiers preserved across the set.
Parts
- Overview and recommendations — the executive summary, the per-knob parameter reference (§7), and the safest selection with residual risks and the recommendation-vs-spec deltas (§8).
- Accuracy and design — the model and counting rule (§2), the seven findings and their evidence (§3), the design equations and selection algorithm (§4), and the caveats and regime of validity (§5).
- Robustness and incentives — jitter, grinding, withholding, selfish mining, the reward design, fork/reorg depth, and organic churn (§6).
- Reproducibility and appendices — how to re-run every study (§9), the residual f-rounding offset (App A), the per-epoch noise floor (App B), and consensus detail (App C).
Headline recommendation
Cryptarchia baseline f = 1/30. Two design choices are foundational: count uncles per occupied slot, not per block — the density-bug fix that lands the estimate at exactly D (§2.1, §8.5) — and make genesis D̂ a single protocol constant, identical at every node, never client-configurable, since a per-node divergence is never self-corrected (§8.1 row 7). The settings: security k = 2160, uncle window W = 300 slots, uncle cap U ≥ ⌈ρ⌉ + 1 (2 at the Blend target; the protocol's MAX_UNCLES = 4 sits safely above it), learning rate β = 1, on-chain f at 10⁻⁶ precision, peering degree ≥ 6 at scale, soft uncle rewards with w_u + w_n < 1, and operate at load ρ = f·D_vis < 1. The full recommended-configuration table and rationale are in Part 1 →.
Figures
Figures are embedded from report-figures/ via relative links and are versioned here alongside the report. They are produced by the simulator's plotting scripts (scripts/*.py and tsi_sim.plotting) in tsi-sim-pernode; that simulation folder does not commit its own generated figures — the copies checked in here are the report's figures of record.
Reproducing the results
The simulation code, configs, and run data live in tools/simulators/tsi/tsi-sim-pernode. Every study's exact command is listed in Part 4 — Reproducibility (§9). In short, from the simulator directory: make install, then make <config> to run a sweep (results land under runs/<timestamp>_<label>/), and the per-figure generators under scripts/ render the figures. Regenerated figures must be copied into report-figures/ to update this report.