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Board hygiene for merged #932/#933 + storm-geography refinement of the two-regime rule #934
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@@ -187,6 +187,80 @@ final validation of the two-regime table already committed in | |
| head-to-head arithmetic that entry asserted but did not yet run as a | ||
| standalone, swept comparison. | ||
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| ### Refinement — the storm's own geography sorts the two regimes (operator, 2026-08-12) | ||
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| Operator observation (paraphrased): the analytic/tempered register belongs at | ||
| the **storm's eye**, the golden/sunflower register in the **collision zone** | ||
| (the arc's Nahkampf terrain) — and specifically, the tempered register gives | ||
| the more exact storm **centering**, because a golden spiral's own center is | ||
| where its data quality is worst. | ||
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| All three halves of that are mechanically grounded in measurements this arc | ||
| has already made — the mapping is not an aesthetic assignment: | ||
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| 1. **The spiral's center is structurally sub-floor at ANY N.** Local | ||
| parastichy index at radius `r` is `√(r²·N)` → 0 as `r` → 0 — the exact | ||
| arithmetic behind the W5 fix (`weather-w-probes-v1` §1), where raising N | ||
| could never rescue the inner bands and the only correct move was | ||
| excluding them from judgment. A Vogel lattice's innermost points are | ||
| degenerate by construction: resonant stride families, uneven first-few-k | ||
| spacing, no floor-qualifying neighbourhood. **Center work on a golden | ||
| lattice is garbage-register work, at any budget.** | ||
| 2. **The shipped center-finder is already on the correct register.** | ||
| `find_center` (`comet_tail_f5_n10.py` / `comet_tail_f16.py`) is an | ||
| exact-enumeration argmin over the regular lat/lon grid plus a quadratic | ||
| sub-grid fit — bounded, exhaustive, zero-variance: the tempered/head | ||
| register, never a spiral sample. What was implicit practice is now | ||
| stated doctrine: **centering = exact enumeration; never sample the | ||
| center from the spiral whose center is its own worst data.** | ||
| 3. **The sunflower is the territory-gain model, and its advantage is that | ||
| its addresses speak for themselves outward.** Prefix-extensibility | ||
| (report §10.5 property 3) means position is *implied* by index `k` — | ||
| place deterministic, residue stored, nothing re-meshed — and each added | ||
| point lands in the largest current gap (`O(log N/N)` discrepancy). In | ||
| the Go framing the arc already measured (`go_territory_probe`): golden | ||
| is the **opening** — optimal incremental territory claim in open, | ||
| growing space; tempered is the **endgame count** — exact, closed, | ||
| bounded. Same two regimes as the T1 table, now with the game-phase | ||
| reading attached. **And the self-description is unbounded** (operator, | ||
| same session, paraphrased: self-explanatory without end) — which is the | ||
| sharpest way to state the asymmetry. A tempered walk is self-describing | ||
| exactly up to `q`: beyond one cycle the index carries no new | ||
| information, the address vocabulary is exhausted, the walk repeats. The | ||
| golden index is self-describing for **every** `k`, indefinitely — no | ||
| re-meshing, no re-indexing, no schema change at any scale, with quality | ||
| still *improving* as it grows (`O(log m/m)`, T2's measured 68–106× | ||
| advantage at `m=200q` IS this property in number form). Bounded | ||
| self-description that closes exactly, versus unbounded self-description | ||
| that never stops refining: that is the entire duel in one sentence. | ||
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| 4. **Overlaying the collision lattices is controlled chaos at near-zero | ||
| storage cost** (operator observation, same session, paraphrased: the | ||
| superposition is pleasingly chaotic AND cheap). Both halves are | ||
| measurable, not vibes. *Chaotic:* two golden lattices over different | ||
| centers are incommensurate — the overlay pattern is aperiodic (never | ||
| repeats, no moiré, no systematic ties; §10.5 property 2, and exactly | ||
| what W2s-a's G1/G3 bars measure) — yet fully **deterministic**: the | ||
| entire pattern regenerates from two center coordinates and nothing | ||
| else. Low-discrepancy chaos, not randomness — reproducible, seedless, | ||
| audit-friendly. *Cheap:* the overlay stores **no geometry at all**. | ||
| Every point's position is implied by its index (place deterministic), | ||
| so a collision node costs exactly its 12-byte V3 facet — rails 0–1 the | ||
| `(k_H:k_T)` pair address, rails 2–5 the 8 state bytes — with radii, | ||
| azimuths, and positions all *derived*, never persisted. Densifying the | ||
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When the collision annulus is densified at a fixed radius, the point position is not determined by Useful? React with 👍 / 👎. |
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| overlay adds nodes, not meshes: cost grows with the number of | ||
| collisions you choose to materialize, not with the resolution of the | ||
| space they live in. | ||
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| **The demarcation that keeps this honest:** the geography does not *cause* | ||
| the regime — the **task** does. The eye is tempered territory because the | ||
| task there (resolve one address, fixed budget, exact closure) is a bounded | ||
| task; the collision annulus is golden territory because the task there | ||
| (pair two growing lattices ever more densely) is an unbounded one. It | ||
| happens — and this is the elegant part, not the load-bearing part — that | ||
| the storm's geography sorts its tasks into exactly the two regimes the T1 | ||
| crossover table measures. | ||
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| ## Execution | ||
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| Zero fetch, pure `numpy`/`scipy.spatial` (only T3's KD-tree-adjacent bucket | ||
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In the context where this refinement is presented as grounded in existing measurements, W2s-a cannot support the aperiodicity/no-moiré claim: this commit's inventory explicitly says no W2s-a bar has run (
PR_ARC_INVENTORY.md:113-121), and its planned G1 measures per-source nearest-neighbor ties while G3 is only a descriptive midpoint-density statistic (weather-w-probes-v1.md:305-329), neither of which tests whether the overlay repeats or forms moiré structure. Treat this as a hypothesis or add and run a metric that actually measures the stated property.Useful? React with 👍 / 👎.