Layer 1 complete: E3-E6 + E2 analysis add-ons

Finishes the Layer 1 analytical core. All six experiments run with honest,
publication-quality figures; 71 tests green.

- E3 region-matched grounding: `grounding.exercised` knob + per-region tail
  survival. Matched holds the exercised region's tail (0.49) where uniform
  spreads thin and lets it collapse (0.07).
- E4 multi-teacher recombination: `run_coverage` runner. Union coverage matches
  U(K_T,rho,q) exactly. Finding: mean-mixture distillation shows NO surviving
  benefit (a conservation law — 1/K_T dilution cancels the union gain); a
  union-preserving max-merge (M2N2-style) does. E4 reports both operators.
- E5 QD vs greedy: greedy drives fixation (H~0.01); QD holds H at 0.48-0.88,
  rising with the novelty exponent.
- E6 re-mint gate: `arm` multi-override sweep. Re-minting a collapsed lineage
  locks in divergence of KL-to-original; gating on diversity prevents it.
- E2 analysis add-ons (from the companion work order, numbers verified): new
  analysis.py (reduce_to_stationary, critical_grounding with bootstrap CI ->
  g*=0.048, 95% CI [0.047,0.050]); tail_band_metrics + per-band logging; the
  E2 figure rebuilt as a 2x2 (defined g*+CI, g=0 flagged as a finite-time
  artifact, tail item-vs-mass, per-rarity-band panel). Uses truth-mass-weighted
  tail coverage rather than the raw (martingale) tail_mass.

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

configs/layer1/E3.yaml

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+experiment: E3_region_matched_grounding
+seed: 20260704
+n_replicates: 100
+generations: 400
+
+# Region-matched grounding (blueprint 2.5-E3). Fixed total budget m; the lineage this
+# passage exercises region 0 (the target, carrying its own rare tail). Compare:
+#   uniform  -> spread m evenly over all R regions (region 0 gets only m/R)
+#   matched  -> allocate m to the exercised region(s) only (region 0 gets all of m)
+# Prediction: under uniform, region 0's tail collapses even though global grounding is
+# nonzero; under matched, it persists. Metric: per-region tail-item survival.
+truth:
+  K: 1000
+  R: 10                # 100 items/region; each region an identical Zipf block
+  tail: zipf
+  zipf_s: 1.1
+  tail_frac: 0.5
+  tail_threshold: 1.0e-3
+  init: truth
+
+dynamics:
+  n: 200
+  teachers: {K_T: 1, rho: 0.0, q: 1.0}
+  grounding:
+    m: 100             # same total for both arms; uniform => 10/region, matched => 100 to region 0
+    policy: uniform    # overwritten by the sweep
+    exercised: [0]     # region 0 is exercised this passage (matched targets it)
+  selection: {mode: none, novelty_alpha: 0.0}
+  remint: {enabled: false, period: null, H_gate: null}
+
+metrics:
+  kl_floor: 1.0e-9
+  support_eps: 1.0e-9
+
+sweep:
+  - param: dynamics.grounding.policy
+    values: [uniform, matched]
+
+output:
+  dir: results/E3

configs/layer1/E4.yaml

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+experiment: E4_multiteacher_decorrelation
+kind: coverage
+seed: 20260704
+n_replicates: 200
+
+# Multi-teacher recombination (blueprint 2.5-E4 / 2.7.1). Build K_T teachers with exact
+# marginal retention q and pairwise retention-correlation rho, form the pupil from their
+# mixture (n draws total = matched budget), and report TWO coverages:
+#   union_coverage    -> construction-level U(K_T,rho,q) (must match the closed form)
+#   surviving_coverage-> tail items that survive the pupil's size-n resampling (+ grounding)
+# Expect: both rise with K_T and (1-rho); at rho=1 many teachers give no benefit over one;
+# the union-surviving gap shrinks as grounding g rises.
+truth:
+  K: 500
+  R: 1
+  tail: zipf
+  zipf_s: 1.1
+  tail_frac: 0.5
+  tail_threshold: 2.0e-3
+
+coverage:
+  n: 300          # pupil sample size (matched budget across teachers)
+  q: 0.5          # per-teacher marginal tail retention
+
+sweep:
+  - param: K_T
+    values: [1, 2, 3, 5]
+  - param: rho
+    values: [0.0, 0.25, 0.5, 0.75, 1.0]
+  - param: g
+    values: [0.0, 0.02, 0.05]
+
+output:
+  dir: results/E4

configs/layer1/E5.yaml

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+experiment: E5_qd_vs_greedy
+seed: 20260704
+n_replicates: 100
+generations: 400
+
+# Quality-diversity vs greedy selection (blueprint 2.5-E5). Modest grounding gives a true
+# stationary state (so items can be re-introduced); selection then shapes it. Greedy
+# (directional, fitness-proportional) drives toward the fittest items -> low H; qd (adds a
+# novelty bonus w_i ∝ f_i·p_i^{-alpha}) resists fixation -> higher stationary H. Sweep the
+# novelty exponent alpha. Prediction: qd holds higher stationary H (and tail survival)
+# than greedy at matched grounding.
+truth:
+  K: 500
+  R: 1
+  tail: zipf
+  zipf_s: 1.1
+  tail_frac: 0.5
+  tail_threshold: 1.0e-3
+  init: truth
+
+dynamics:
+  n: 200
+  teachers: {K_T: 1, rho: 0.0, q: 1.0}
+  grounding: {m: 10, policy: proportional}   # g ~ 0.048, same for all arms
+  selection: {mode: none, novelty_alpha: 0.0}
+  remint: {enabled: false, period: null, H_gate: null}
+
+metrics:
+  kl_floor: 1.0e-9
+  support_eps: 1.0e-9
+
+sweep:
+  - param: dynamics.selection.mode
+    values: [none, greedy, qd]
+  - param: dynamics.selection.novelty_alpha
+    values: [0.5, 1.0, 2.0]
+
+output:
+  dir: results/E5

configs/layer1/E6.yaml

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+experiment: E6_remint_gate
+seed: 20260704
+n_replicates: 100
+generations: 400
+
+# Re-minting gate / irreversibility (blueprint 2.5-E6). Re-minting freezes the current
+# distribution as the new grounding reference and DISCARDS the original truth. Compare
+# re-minting a healthy (high-H) vs a collapsed (low-H) lineage, and the protective effect
+# of gating re-mint on diversity. Metric: forward KL to the ORIGINAL truth. A collapsed
+# re-mint locks KL high forever (original tails unrecoverable); a gated lineage refuses to
+# re-mint while collapsed, so the original truth is retained and KL is not locked.
+truth:
+  K: 500
+  R: 1
+  tail: zipf
+  zipf_s: 1.1
+  tail_frac: 0.5
+  tail_threshold: 1.0e-3
+  init: truth
+
+dynamics:
+  n: 200
+  teachers: {K_T: 1, rho: 0.0, q: 1.0}
+  grounding: {m: 3, policy: proportional}
+  selection: {mode: none, novelty_alpha: 0.0}
+  remint: {enabled: false, period: 150, H_gate: null}
+
+metrics:
+  kl_floor: 1.0e-9
+  support_eps: 1.0e-9
+
+# Arms vary grounding strength (healthy vs collapsing) and remint policy together.
+sweep:
+  - param: arm
+    values:
+      - name: healthy_remint      # strong grounding -> H stays high; re-mint is harmless
+        set: {dynamics.grounding.m: 60, dynamics.remint.enabled: true, dynamics.remint.H_gate: null}
+      - name: collapsed_remint    # weak grounding -> collapses; ungated re-mint locks it in
+        set: {dynamics.grounding.m: 1, dynamics.remint.enabled: true, dynamics.remint.H_gate: null}
+      - name: collapsed_gated     # weak grounding; gate (0.75) blocks re-mint while H is low
+        set: {dynamics.grounding.m: 1, dynamics.remint.enabled: true, dynamics.remint.H_gate: 0.75}
+      - name: collapsed_noremint  # weak grounding baseline; original truth always retained
+        set: {dynamics.grounding.m: 1, dynamics.remint.enabled: false}
+
+output:
+  dir: results/E6