Layer 1 core: Wright-Fisher knowledge-transmission model with E1-E2

Scaffold plus the Layer 1 analytical core and the first two experiments.

- knowledge/: truth, metrics, teachers (2.7.1 shared-switch construction),
  step, lineage, experiment, config, seeding (imported as `knowledge`).
- Validation spine green: neutral decay (Pred 1), fixation (Pred 2), exact
  mutation-drift equilibrium (Pred 3), union coverage (Pred 5). 68 tests pass.
- E1 reproduces tail-first collapse. E2 delivers the headline: a grounding
  phase boundary g* << 1, with stationary H tracking the exact H_eq closed
  form (g=0.005 -> 68% of truth diversity; g=0.05 -> 96%).
- Reproducibility: uv venv from a hash-pinned uv.lock is the source of truth;
  every run writes results.parquet + resolved_config.yaml + manifest.json
  (lib versions, git commit, sha256). Figures and manifests tracked; the
  large regenerable parquet is gitignored.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

figures/plot_E1.py

@@ -0,0 +1,64 @@
+"""E1 figure: reproduce collapse (null model).
+
+Shows tail-first collapse under pure neutral drift: geometric H decay matching the
+analytic law, tail items dying faster than head items, support -> 1 and forward-KL
+diverging. Usage:  python figures/plot_E1.py [results/E1]
+"""
+
+from __future__ import annotations
+
+import sys
+from pathlib import Path
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+sys.path.insert(0, str(Path(__file__).parent))
+from _figlib import load_bundle, mean_ci, savefig  # noqa: E402
+
+
+def main(results_dir: str = "results/E1") -> None:
+    df, cfg = load_bundle(results_dir)
+    n = cfg["dynamics"]["n"]
+
+    gens, Hmean, Hci = mean_ci(df, "generation", "heterozygosity")
+    H0 = Hmean[0]
+    analytic = H0 * (1.0 - 1.0 / n) ** gens
+
+    m = df.groupby("generation").mean(numeric_only=True)
+
+    fig, axes = plt.subplots(1, 3, figsize=(15, 4.2))
+
+    # Panel 1: heterozygosity decay vs the analytic law
+    ax = axes[0]
+    ax.plot(gens, Hmean, color="#1f77b4", label="simulation (mean)")
+    ax.fill_between(gens, Hmean - Hci, Hmean + Hci, color="#1f77b4", alpha=0.25)
+    ax.plot(gens, analytic, "k--", label=r"$H_0(1-1/n)^t$")
+    ax.set(xlabel="generation", ylabel="heterozygosity $H$",
+           title=f"Geometric decay (n={n})")
+    ax.legend(frameon=False)
+
+    # Panel 2: tail-first — fraction of tail vs head items still alive
+    ax = axes[1]
+    ax.plot(m.index, m["tail_frac_alive"], color="#d62728", label="tail items alive")
+    ax.plot(m.index, m["head_frac_alive"], color="#2ca02c", label="head items alive")
+    ax.set(xlabel="generation", ylabel="fraction of items surviving",
+           title="Tail dies first", yscale="log")
+    ax.legend(frameon=False)
+
+    # Panel 3: support collapse and KL divergence
+    ax = axes[2]
+    ax.plot(m.index, m["support_size"], color="#9467bd", label="support size")
+    ax.set(xlabel="generation", ylabel="support size", yscale="log", title="Collapse")
+    ax2 = ax.twinx()
+    ax2.plot(m.index, m["forward_kl"], color="#ff7f0e", label="forward KL")
+    ax2.set_ylabel(r"forward KL $D_{KL}(p^*\,\|\,p_t)$", color="#ff7f0e")
+    ax.legend(loc="center right", frameon=False)
+
+    fig.suptitle("E1 — distillation without grounding collapses, tail first", y=1.02)
+    fig.tight_layout()
+    savefig(fig, results_dir, "E1")
+
+
+if __name__ == "__main__":
+    main(*sys.argv[1:])