docs: close ADR-0242 memo fidelity slice + living-summary update + sanctioned-seam note (follow-up batch)
- docs/research/ADR-0242-…md: committed authority copy of the R&D memo (retrieved via Drive connector from the .gdoc pointer's doc_id), with an audit note marking the reference code as memo-sketch (non-executable; landed impl deliberately stronger). - acceptance packet §7 addendum: memo slice CLOSED — no new defects; impl > spec code on 4 counts; carry items (cert-telemetry seam, F5–F7 cross-band gate, budget floor 2 vs 3) recorded for the ruling. - integration plan: ADR-0242 authority-doc row BLOCKED → CLOSED. - living summary §12: supersedes stale §11 (#38/#40/#41 merged, #42 open, T1/T2 ruling, local-first CI, billing lock, memo closure). - holographic_vault.py: comment documenting the sanctioned physics→teaching EpistemicStatus seam (W1 Finding #4); extraction deferred behind a second-consumer trigger; core/epistemic_state.py is a different concept. [Verification]: pre-push smoke gate queued behind current machine load (W2/W3 lanes saturating CPU, load ~195); push held until it reports green.
This commit is contained in:
Shay
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@ -27,6 +27,12 @@ import numpy as np
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from algebra.backend import versor_condition
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from algebra.cl41 import N_COMPONENTS
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from core.physics.wave_manifold import WaveManifold
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# SANCTIONED SEAM (W1 Finding #4): the one physics→teaching import — boundary
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# vocabulary only (SPECULATIVE/COHERENT standing), no teaching logic crosses.
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# Extraction to a shared kernel is deferred until a second physics module
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# needs the vocabulary (32 consumers repo-wide; not a LOW-batch relocation).
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# NOTE: core/epistemic_state.py holds a DIFFERENT concept (turn-level
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# EpistemicState) — do not merge the two.
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from teaching.epistemic import EpistemicStatus
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from vault.store import VaultStore, _parse_entry_status, _status_admits
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@ -50,3 +50,20 @@
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## 6. Requested action
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Rule on §2 deviations (recommendations inline) and, if satisfied, flip **ADR-0241 and ADR-0242 → Accepted**. PR #41 (chiral gate) can be folded into the Accept or ruled separately.
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---
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## 7. Addendum (same day, post-merge) — ADR-0242 memo fidelity slice CLOSED
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§5 item 1 is resolved: the "deterministic-fibonacci-operators-and-evidence-gated-optimization" memo was retrieved in full (Drive connector; committed copy now at `docs/research/ADR-0242-deterministic-fibonacci-operators-and-evidence-gated-optimization.md`). Audit against the implementation: **no new defects — the implementation is stronger than the memo's own reference code** on four counts:
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| Memo | Implementation | Direction |
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|---|---|---|
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| Prose demands a "content-addressed, cryptographic" certificate; the memo's own dataclass **omits** the digest field | `cert_id` sha256 present, dual-run byte-stable | impl > spec code |
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| Reference unimodality check counts extrema (would **pass a pure local maximum**) | shape check (decrease-to-min-then-increase) fails it | impl > spec code |
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| No nonfinite / bounds-violation guards; code non-executable as written (`np.argsort` without numpy import) | fail-closed on nonfinite, bounds, budget, eval error | impl > spec code |
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| `minimizer` = bracket midpoint always | best sampled point when inside the final bracket (deviation documented at the code comment) | impl > spec, noise-robust |
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Sovereignty invariant (§6 of the memo) verified: Fibonacci operators never touch truth status / safety / identity / promotion (T2 quarantine + proposal-only κ). The five-vector staging matches the memo's phase gating exactly, including anyons (Phase 5 pre-research, not built — consistent with the corrected ledger row).
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**Carry items (staged, non-blocking):** (a) §5-P1 "certificate written to execution telemetry" seam not verified; (b) §5-P2 cross-band (F₅–F₇) DiscoveryCandidate persistence gate not built; (c) impl accepts `evaluation_budget ≥ 2` where the memo floor is 3 — kept deliberately (n=2 is mathematically valid and the impl validates harder elsewhere), noted for the ruling.
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@ -280,4 +280,15 @@ You are resuming CORE ADR-0241/0242 work. Plan A (cohesion P0–P12) and Plan B
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---
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*Archived from session work on 2026-07-15. Plans A/B copied from session plan artifacts; status tables updated to match branch tip and CI reality at archive time.*
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## 12. LIVING UPDATE — 2026-07-15 evening (supersedes §11)
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The §11 brief is stale. Current truth:
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- **#38 MERGED** (`9e1455b9`, lane-shas green at `26abdbe7`; debug env-dump reverted at `4853a55c`).
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- **#40 MERGED** (`54228d45`): W1 adversarial pass (executed) — chiral P8 + Fibonacci V1 confirmed solid; **live A-04 transitive serve breach found & fixed** (core/physics barrel → lazy Tier-2 exports + process-level guard test); **T1/T2 serve-boundary reconciliation ruled** (wave_manifold = sanctioned serve substrate; 7 research modules stay off-serving); 4-blueprint integration plan; these plan archives (W2); CLI smoke↔CI parity (175 tests); **local-first CI protocol in AGENTS.md** (GitHub Actions billing-locked — do not chase).
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- **#41 MERGED** (`717aca9b`): chiral orientation sign-gate (sgn(Q)=const fail-closed, ADR-0241 §2.4C / core_ha §5.2 — the audit's one missing safeguard) + **D10 acceptance packet** (`docs/audit/adr-0241-0242-acceptance-packet-2026-07-15.md`) + anyon ledger honesty fix.
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- **#42 OPEN**: CRDT-vs-bit-exact determinism decision dossier (Gemini) — recommends bit-exact single-writer now, CRDT behind a multi-writer gate; found real Delta-CRDT machinery in `core-rs/src/vault.rs`.
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- **ADR-0242 R&D memo slice CLOSED**: read via the Drive connector; no new defects — implementation is stronger than the memo's own reference code. Carry items: cert-telemetry seam (§5-P1) and F₅–F₇ cross-band DiscoveryCandidate gate (§5-P2) unbuilt (staged, non-blocking); impl allows budget≥2 vs memo's ≥3 (kept — stronger validation elsewhere).
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- **Remaining**: Joshua Accept ruling (packet ready); W5 backlog (D9 Rust parity, sensorium compilers, V2 energy benchmark, progressive field); parallel lanes W2 (full-suite reds) / W3 (xdist polluters) briefed in `tmp/`.
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*Archived from session work on 2026-07-15. Plans A/B copied from session plan artifacts; §12 added post-merge; earlier status tables reflect archive-time reality.*
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@ -0,0 +1,323 @@
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# ADR-0242: Deterministic Fibonacci Operators and Evidence-Gated Optimization
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> Committed authority copy. Retrieved verbatim 2026-07-15 from the R&D Google Doc
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> (`doc_id 15_NECCPy-tEWGfYi_BNqawm8GytUTMkz1DsOqGVMXhI`, pointer:
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> `docs/research/ADR-0242-deterministic-fibonacci-operators-and-evidence-gated-optimization.md.gdoc`),
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> formatting normalized from the Docs export. The Drive document remains the
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> editable source; this copy exists so fidelity audits can cite in-repo text.
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> Fidelity audit: `docs/audit/adr-0241-0242-acceptance-packet-2026-07-15.md` §7.
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**Status**: Proposed (acceptance path: benchmark evidence + Joshua review)
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**Date**: 2026-07-13
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**Deciders**: Joshua Shay + multi-model R&D
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**Traceability**: Notion R&D (Fibonacci and Golden Ratio Dynamics)
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**Related**: ADR-0238, ADR-0239, ADR-0240, ADR-0241, core/physics/goldtether.py, core/physics/surprise.py, core/physics/energy.py
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**Canonical path**: docs/adr/
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## 1. Context and Problem Statement
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The introduction of continuous wave-field representations (ADR-0241) in the Continuous Orthogonal Resonance Engine (CORE) establishes a unified, coordinate-free geometric substrate. As we refine the physical layers of CORE, we encounter several optimization, scheduling, and multi-scale allocation challenges:
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- **Optimization of Unimodal Scalars**: Bounded parameters such as the GoldTether valence-scaling factor (κ) or the Conformal Procrustes alignment angle (θ) require fast, exact, and reproducible bracketing.
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- **Hierarchical Temporal Horizons**: Modeling decay, salience, and consolidation requires a deterministic temporal basis to segregate transient noise from long-horizon semantic structures.
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- **Mode Centroid Allocation**: Registering new standing-wave modes in WaveManifold requires a low-discrepancy, incrementally extensible spacing algorithm to prevent spectral mode collision without global repacking.
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- **Observability Scheduling**: Periodic background checks risk phase-locking with external batching cycles, requiring quasi-periodic, non-harmonic scheduling.
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In natural and mathematical systems, Fibonacci recurrences (F_n = F_{n-1} + F_{n-2}) and Golden Ratio (φ) limits govern optimal packings, anyon fusion, and optimal search. However, CORE's **Third Door** philosophy explicitly rejects the dogmatic adoption of "sacred geometry" or aesthetic doctrines. Any mathematical operator must "earn its place" through a measurable, isolated, and falsifiable advantage, and its results must be bound by strict evidence-gated promotion.
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## 2. Decision and Reframed Thesis
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We establish the **CORE Fibonacci Evidence Discipline**:
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**Fibonacci structure is implemented only where CORE requires a deterministic, reconstructible, multi-scale allocation, search, or selection mechanism — not because φ is inherently privileged, but because a Fibonacci recurrence can be evaluated empirically against competing schedules, packings, or optimizers under CORE's rigorous evidence gating.**
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We define **five targeted vectors** of Fibonacci integration, structured from near-term engineering deliverables to long-horizon theoretical research, each isolated behind clean programmatic boundaries and cryptographic validation gates:
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```
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[CORE Evidence Discipline]
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+-----------------+------------+------------+-----------------+
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| | | |
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v v v v
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[Vector 1] [Vector 2] [Vector 3] [Vector 4/5]
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Fibonacci Search Temporal Basis Anchor Alloc Word Choreography
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(Optimization) (Decay Study) (Mode Packing) (Quasi-Periodic)
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Certificate E_n(t) = E_n*exp(-t/tau) Low-discrep W_n+1 = W_n · W_n-1
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```
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## 3. The Five Fibonacci Vectors
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### 3.1 Vector 1: Bounded Fibonacci-Section Search (Immediate Opportunity)
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We implement Fibonacci-section search as a highly constrained, pure, and deterministic scalar optimizer.
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For a known, fixed evaluation budget N, Fibonacci search provides the mathematically optimal final bracket width among comparison-based methods under unimodality assumptions. It is superior to golden-section search because it leverages a precomputed Fibonacci schedule to minimize interval length exactly at step N, reusing one function evaluation per step.
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#### CORE-Native Certificate Gating
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To prevent unreviewed parameters from altering cognitive behavior, the optimizer does *not* return a raw scalar. It outputs a content-addressed, cryptographic **FibonacciSearchCertificate** (or a typed **OptimizationFailure**). This certificate serves as an immutable audit trail of the search trajectory and must be verified before the minimizer can be promoted to drive any active parameter (e.g., GoldTether valence-scaling κ).
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### 3.2 Vector 2: Multi-Scale Temporal Basis (Most Native Research Path)
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The Field Energy Operator (ADR-0006) simulates thermodynamic cooling of active states. Rather than hard-coding decay constants, we treat the Fibonacci sequence as a candidate **temporal basis family**.
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Each active field component carries a deterministic vector of decayed energies across a finite, reconstructible spectrum of horizons:
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E_n(t) = E_n(t_0) · exp(−(t − t_0) / (F_n · τ_0))
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where F_n ∈ {1, 2, 3, 5, 8, 13, 21, …} provides the temporal scales.
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- F_1·τ_0: Immediate sensory perturbations.
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- F_3·τ_0: Working reasoning context.
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- F_5·τ_0: Active session structures.
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- F_8·τ_0: Long-horizon biography holonomies.
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**The Comparative Hypothesis**: We will benchmark this Fibonacci basis against standard dyadic (τ_n = 2^n·τ_0), logarithmic, and hand-tuned bases. The Fibonacci basis is promoted to the production pipeline (e.g., inside core/physics/energy.py) if and only if it separates transient sensory noise from persistent semantic signals with measurably higher fidelity under identical replay workloads.
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### 3.3 Vector 3: Golden-Angle Mode Allocator (Anchor Allocation)
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When registering a new standing-wave mode ψ_k in the Hyperbolic Atlas, the manifold must assign a spatial centroid anchor X_k that minimizes phase overlap and collision.
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We define a pure **AnchorAllocator** strategy interface. One candidate strategy is a **Golden-Angle Hyperbolic Spiral** over the Poincaré disk model, which generates a low-discrepancy, incrementally extensible spatial distribution without requiring global repacking.
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The final anchor layout is never stored as a mutable, opaque coordinate table. It is dynamically regenerated from the allocator's identity and the ordinal sequence, preserving the **reconstruction-over-storage** doctrine:
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Layout(n) = AnchorAllocator(n, version="golden_angle_v1")
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The golden-angle allocator will be benchmarked against deterministic low-discrepancy sequences, measuring minimum pairwise geodesic separation, recall ambiguity, and insertion cost before adoption.
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### 3.4 Vector 4: Fibonacci-Word Operator Choreography (Observability Scheduling)
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To reduce phase-locking and harmonic resonance between periodic background checks and input batching cycles, we introduce a quasi-periodic, non-harmonic scheduling operator.
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We recursively generate **Fibonacci words** from two safe, existing action classes:
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- **Action A**: Low-cost local measurements (e.g., local energy/surprise updates).
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- **Action B**: High-cost cross-band evaluations (e.g., biography holonomy or sealed-holdout checks).
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W_0 = B, W_1 = A, W_{n+1} = W_n W_{n−1}
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For n=4, this yields: A → B → A → A → B → A → B → A → A → B …
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This non-periodic, deterministic sequence belongs strictly outside the cognitive truth path. It is used to schedule background measurements, telemetry traces, and sealed-holdout sampling. This prevents cyclic artifacts of the scheduler from corrupting the continuous field dynamics.
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### 3.5 Vector 5: Topological Compositional Holonomy (Long-Horizon anyon Theory)
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We open an isolated research branch (algebra/topological_reasoning/) to study whether non-commuting semantic composition paths produce stable, topologically protected holonomies under bounded perturbation.
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This track will explore if the category data of **Fibonacci anyons** (including its fusion spaces, F-symbols, and R-symbols) can be represented within Cl(4,1) CGA. This remains a pre-research theory program. It must never enter the production pipeline or affect active reasoning until its mathematical representation and stability under floating-point perturbations are fully proven.
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## 4. Implementation Specification (Vector 1: Fibonacci Search)
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> Note (audit, 2026-07-15): the memo's reference implementation below is
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> preserved as-written for the record. The landed implementation
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> (`core/physics/fibonacci_search.py`) deliberately deviates in the
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> impl-stronger direction — see the acceptance-packet §7 table (cert_id
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> digest added; shape-based unimodality check; nonfinite/bounds fail-closed;
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> best-sample minimizer). The reference code below is non-executable as
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> written (uses `np.argsort` without importing numpy).
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To guarantee exactness and absolute reproducibility, we define the strict, frozen Python interface for the unimodal objective, the search certificate, and the deterministic Fibonacci-section search algorithm.
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```python
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# core/physics/fibonacci_search.py (memo reference sketch — see note above)
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from __future__ import annotations
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from dataclasses import dataclass
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from typing import Callable, Union
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@dataclass(frozen=True, slots=True)
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class BoundedUnimodalObjective:
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"""Represents a bounded, unimodal scalar objective to be optimized."""
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lower: float
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upper: float
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evaluation_budget: int
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objective_id: str
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objective_version: str
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@dataclass(frozen=True, slots=True)
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class FibonacciSearchCertificate:
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"""The cryptographically verifiable, replayable optimization result."""
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minimizer: float
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final_interval: tuple[float, float]
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evaluations: int
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ordered_points: tuple[float, ...]
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ordered_values: tuple[float, ...]
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objective_id: str
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objective_version: str
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@dataclass(frozen=True, slots=True)
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class OptimizationFailure:
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"""Typed failure response indicating why the optimization could not converge."""
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reason: str
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final_interval: tuple[float, float]
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evaluations: int
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objective_id: str
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objective_version: str
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def _precompute_fibonacci(n: int) -> list[int]:
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"""Generates the first n Fibonacci numbers."""
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fib = [1, 1]
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for i in range(2, n + 2):
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fib.append(fib[-1] + fib[-2])
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return fib
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def fibonacci_section_search(
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objective: BoundedUnimodalObjective,
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func: Callable[[float], float]
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) -> Union[FibonacciSearchCertificate, OptimizationFailure]:
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"""
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Executes a metric-orthogonal Fibonacci search on a unimodal objective.
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Admit only a typed OptimizationFailure or FibonacciSearchCertificate;
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never silently accept a candidate minimizer.
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"""
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a = float(objective.lower)
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b = float(objective.upper)
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n = objective.evaluation_budget
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if n < 3:
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return OptimizationFailure(
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reason="budget_too_low_for_unimodal_search",
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final_interval=(a, b),
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evaluations=0,
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objective_id=objective.objective_id,
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objective_version=objective.objective_version,
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)
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fib = _precompute_fibonacci(n)
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L = b - a
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# Pre-calculated evaluation points
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x1 = a + (fib[n] / fib[n + 2]) * L
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x2 = b - (fib[n] / fib[n + 2]) * L
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points: list[float] = [x1, x2]
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try:
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f1 = float(func(x1))
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f2 = float(func(x2))
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except Exception as e:
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return OptimizationFailure(
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reason=f"evaluation_error_at_initial_points: {str(e)}",
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final_interval=(a, b),
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evaluations=0,
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objective_id=objective.objective_id,
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objective_version=objective.objective_version,
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)
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values: list[float] = [f1, f2]
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evals_count = 2
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for k in range(1, n - 1):
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L_next = b - a
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if f1 < f2:
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b = x2
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x2 = x1
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f2 = f1
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x1 = a + (fib[n - k + 1] / fib[n - k + 2]) * L_next
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try:
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f1 = float(func(x1))
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except Exception as e:
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return OptimizationFailure(
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reason=f"evaluation_error_at_step_{k}: {str(e)}",
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final_interval=(a, b),
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evaluations=evals_count,
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objective_id=objective.objective_id,
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objective_version=objective.objective_version,
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)
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points.append(x1)
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values.append(f1)
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else:
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a = x1
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x1 = x2
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f1 = f2
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x2 = b - (fib[n - k + 1] / fib[n - k + 2]) * L_next
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try:
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f2 = float(func(x2))
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except Exception as e:
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return OptimizationFailure(
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reason=f"evaluation_error_at_step_{k}: {str(e)}",
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final_interval=(a, b),
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evaluations=evals_count,
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objective_id=objective.objective_id,
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objective_version=objective.objective_version,
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)
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points.append(x2)
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values.append(f2)
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evals_count += 1
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minimizer = (a + b) / 2.0
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# Strictly verify the unimodality assumption on the gathered trace.
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# To be unimodal, values must decrease to a minimum and then increase.
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# If the empirical trace contains multiple local extrema, the certificate
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# fails validation.
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sorted_indices = np.argsort(points)
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sorted_vals = [values[i] for i in sorted_indices]
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extrema_count = 0
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for i in range(1, len(sorted_vals) - 1):
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prev_diff = sorted_vals[i] - sorted_vals[i - 1]
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next_diff = sorted_vals[i + 1] - sorted_vals[i]
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if prev_diff < 0 and next_diff > 0:
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extrema_count += 1 # Local minimum
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elif prev_diff > 0 and next_diff < 0:
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extrema_count += 1 # Local maximum
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if extrema_count > 1:
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return OptimizationFailure(
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reason="unimodality_violation_multiple_extrema_detected",
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final_interval=(a, b),
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evaluations=evals_count,
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objective_id=objective.objective_id,
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objective_version=objective.objective_version,
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)
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return FibonacciSearchCertificate(
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minimizer=float(minimizer),
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final_interval=(float(a), float(b)),
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evaluations=evals_count,
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ordered_points=tuple(points),
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ordered_values=tuple(values),
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||||
objective_id=objective.objective_id,
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objective_version=objective.objective_version,
|
||||
)
|
||||
```
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|
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## 5. R&D Integration and Priority Order
|
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|
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To enforce strict, non-doctrinal evidence gating, the five vectors will be integrated sequentially based on their readiness and safety risk:
|
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|
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1. **Phase 1: Isolated Fibonacci-Section Search (Production-Ready)**
|
||||
- **Integration Seam**: Bounded valence-scaling factor (κ) in core/physics/goldtether.py.
|
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- **Gating**: The returned FibonacciSearchCertificate is written to the execution telemetry. If the certificate fails (e.g. unimodality_violation), the system defaults to the safe, pre-calculated baseline kappa = 1.0 and logs an OptimizationFailure warning.
|
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|
||||
2. **Phase 2: Multi-Scale Temporal Basis Study (Research Prototype)**
|
||||
- **Integration Seam**: The Field Energy Operator (core/physics/energy.py) and the non-resonant surprise accumulator (core/physics/surprise.py).
|
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- **Gating**: Emits a DiscoveryCandidate in the contemplation loop *only* when the surprise signal persists across multiple Fibonacci-scaled temporal bands (F_5 to F_7), preventing transient noise from triggering ungrounded updates.
|
||||
|
||||
3. **Phase 3: Golden-Angle Mode Allocator (Sandbox Scaffold)**
|
||||
- **Integration Seam**: Centroid placement inside the WaveManifold memory registry (core/physics/wave_manifold.py).
|
||||
- **Gating**: Active only when the standing-wave registry's coordinate and interference operators are fully verified in the main Rust branch.
|
||||
|
||||
4. **Phase 4: Fibonacci-Word Observability Scheduler (Telemetry Seam)**
|
||||
- **Integration Seam**: Background telemetry traces and sealed-holdout sampling.
|
||||
- **Gating**: Operates strictly outside the cognitive truth path; cannot modify any state variables.
|
||||
|
||||
5. **Phase 5: Topological Braid Category Study (Pre-Research)**
|
||||
- **Integration Seam**: Isolated algebra/topological_reasoning/ branch.
|
||||
- **Gating**: Blocked from any FFI or CPython compilation path until algebraic and numerical stability proofs under floating-point perturbations are finalized.
|
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|
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## 6. Architectural Sovereignty Invariant
|
||||
|
||||
This ADR establishes the absolute sovereignty of CORE's core logical layers over any mathematical scheduling or optimization:
|
||||
|
||||
**Fibonacci operators may optimize the parameters of search, determine the scale of observation, or schedule background checks; they must NEVER dictate the truth status of a proposition, alter safety policies, change CORE's identity, or authorize autonomous promotion.**
|
||||
|
||||
Active reasoning, memory vaulting, and supervised transition gating remain strictly governed by CORE's even versor closure invariants, sharded CRDT-delta exactness, and human-gated review boundaries.
|
||||
|
||||
## 7. References
|
||||
|
||||
1. docs/adr/ADR-0238-GoldTether-Modulated-Supervised-Autonomy.md — GoldTether and supervised blend.
|
||||
2. docs/adr/ADR-0239-Conformal-Procrustes-Surprise-Dual-Operator.md — Conformal Procrustes and surprise.
|
||||
3. docs/adr/ADR-0240-Analogical-Transfer-Validation-Harness-Biography-Holonomy.md — Biography holonomy and validation.
|
||||
4. docs/adr/ADR-0241-wave-field-driven-hyperbolic-atlas-and-resonant-cognition.md — Continuous wave-field framework.
|
||||
|
|
@ -10,7 +10,7 @@
|
|||
| ADR-0241 wave-field hyperbolic atlas + resonant cognition | ✅ full | audited deep |
|
||||
| core_ha unification & deprecation plan | ✅ full | audited |
|
||||
| fibonacci_applications_in_core_substrate | ✅ full | audited |
|
||||
| ADR-0242 deterministic-fibonacci-operators + evidence-gated-optimization | ❌ **no local export** | **BLOCKED — needs export**; cert impl verified against its own contract |
|
||||
| ADR-0242 deterministic-fibonacci-operators + evidence-gated-optimization | ✅ full (read 2026-07-15 via Drive connector; committed copy at `docs/research/ADR-0242-deterministic-fibonacci-operators-and-evidence-gated-optimization.md`) | **slice CLOSED** — no new defects; see acceptance-packet addendum |
|
||||
|
||||
---
|
||||
|
||||
|
|
@ -53,7 +53,7 @@ The recurring pattern across all four docs: the blueprints were written when the
|
|||
| Missing invariant | Current state | Build |
|
||||
|---|---|---|
|
||||
| **Chiral SIGN-preservation gate** (ADR-0241 §2.4C + core_ha §5.2: `sgn(∫⟨ψIψ̃⟩₀)=const`, mirror-inversion protection) | ✅ **BUILT** (`feat/chiral-sign-preservation-gate`, stacked on PR #40): `core/physics/chiral_gate.py` — `ChiralOrientationGate` latches `sgn(Q)` on the first non-vacuous reading, fails closed (`ChiralOrientationError`) on a materially re-emerging flip; wired at the enforcement point (`goldtether_residual` now feeds the *signed* charge to the gate; residual keeps magnitude semantics byte-identical). Even serve fields stay vacuous → inert on today's serve path (no #19 revival). Pins: `tests/test_chiral_orientation_gate.py` (7). | — (was: latch initial sign + fail closed on flip; wire signed charge) |
|
||||
| **CRDT delta-sync semilattice** (core_ha §2/§3 tombstone → "commutative/associative/idempotent Delta-CRDT in `core/sync/`") | `core/sync/` is a journal/object-store (no `merge`/idempotent/semilattice semantics found). Determinism today = bit-exact `array_codec` + single-writer `VaultStore` (Shape B+), **not** multi-writer CRDT merge. | Decide: either build the CRDT (needed for genuine multi-agent/multi-writer "one continuous life") **or** correct the doc to state determinism is single-writer bit-exact. Don't leave the claim floating. |
|
||||
| **CRDT delta-sync semilattice** (core_ha §2/§3 tombstone → "commutative/associative/idempotent Delta-CRDT in `core/sync/`") | ✅ **RESOLVED by decision dossier** (`docs/analysis/crdt-vs-bitexact-determinism-decision-2026-07.md`, PR #42 merged `ccc42c18`): Python `core/sync/` is object-store only, but real Delta-CRDT semilattice machinery exists in `core-rs/src/vault.rs`, and `test_audio_crdt_merge.py` exercises genuine CRDT properties in that sub-domain. Ruling: single-writer bit-exact (`array_codec` + VaultStore) serves the one-continuous-life telos today; **CRDT rollout deferred behind an explicit multi-writer/multi-agent gate**. | — (Joshua ratification rides the acceptance packet) |
|
||||
|
||||
### ⛔ SCRAP / DO-NOT-BUILD — correctly rejected over-claims
|
||||
| Blueprint clause | Disposition |
|
||||
|
|
|
|||
Loading…
Reference in a new issue