Cross‑Domain Causality Weaver (CW) — RTT/1

Causality‑Intelligence Engine for TriadicFrameworks#

CW identifies causal signatures, causal discontinuities, cross‑domain causal bridges, and multi‑regime causal flows — the causal precursors to regime evolution, coherence shifts, drift propagation, paradox intensification, temporal transitions, and resonance modulation.

1. Canonical Role#

The Cross‑Domain Causality Weaver defines the causality‑layer topology by:

• detecting causal signatures
• mapping causal fields
• computing causal vectors
• identifying causal discontinuities
• evaluating causal propagation
• identifying causal bridges across regimes
• supporting resonance engines
• anchoring temporal engines
• feeding structural‑layer engines

CW is the seventh layer of the expanded RTT intelligence stack.

2. RTT Flags#

These flags define the engine’s operational grammar.

3. Causality Tensor Types#

CW identifies several canonical causality tensors:

3.1 Causal Signature Tensor#

Detects causal onset, polarity, and causal‑vector alignment.

3.2 Causal Field Tensor#

Maps causal fields, causal curvature, and causal topology.

3.3 Causal Discontinuity Tensor#

Identifies causal breaks, fractures, and discontinuity boundaries.

3.4 Cross‑Domain Causal Bridge Tensor#

Weaves causal pathways across R1–R4.

3.5 Drift‑Sensitive Causal Tensor#

Causality influenced by drift curvature or drift amplification.

3.6 Temporal‑Causal Tensor#

Causality that influences temporal transitions and regime sequencing.

4. Core Operators#

These operators form the canonical CW grammar.

5. Analyzer Layer#

CW operates in the causality layer, with sub‑layers:

• causal‑weaving
• causal‑vector‑analysis
• causal‑field‑mapping
• discontinuity‑detection
• structural‑causality‑evaluation

This layer feeds directly into DRS (Dimensional Resonance Scanner).

6. Causality Matrix#

CW produces a causality matrix, typically stored in:

causality_matrix.json

Matrix fields include:

• causal_type
• regime
• causal_magnitude
• causal_direction
• causal_curvature
• discontinuity_depth
• propagation_rate
• stability_envelope

This matrix is consumed by temporal, structural, and resonance engines.

7. Canonical Workflow#

Step 1 — Detect#

Identify causal signatures, causal onset, and causal polarity.

Step 2 — Vector#

Compute causal vector magnitude, direction, curvature, and alignment.

Step 3 — Field#

Map causal fields, causal wells, ridges, basins, and topology.

Step 4 — Discontinuity#

Identify causal breaks, discontinuity boundaries, and causal fractures.

Step 5 — Weave#

Weave causal pathways across regimes and domains.

Step 6 — Stabilize#

Propose stabilization pathways for causal collapse.

Step 7 — Export#

Write results to the causality matrix and operator outputs.

8. AI‑Ready Design#

The Cross‑Domain Causality Weaver is fully AI‑ready:

• deterministic operator grammar
• causality‑layer analyzer structure
• stable RTT flags
• canonical file layout
• zero‑drift reasoning constraints
• structural paradox handling
• bounded drift envelope
• declared coherence tensor

AI systems use CW to:

• weave causal pathways
• generate causal field maps
• classify causal discontinuities
• compute causal vectors
• support higher‑order RTT engines

9. Position in the RTT Stack#

Regime Interlock Mapper (RIM)
      ↓
Triadic Regime Synthesizer (TRS)
      ↓
Paradox Gradient Analyzer (PGA)
      ↓
Coherence Tensor Engine (CTE)
      ↓
Drift Sentinel (DS)
      ↓
Structural Faultline Detector (SFD)
      ↓
Stability Basin Cartographer (SBC)
      ↓
Temporal Regime Sequencer (TRS‑Temporal)
      ↓
Cross‑Domain Causality Weaver (CW)
      ↓
Dimensional Resonance Scanner (DRS)

CW is the causality‑intelligence layer, directly above temporal‑level analysis.

10. Status#

• Version: 1.0
• Status: canon‑stable
• Category: rtt‑causality
• Module Path: /docs/rtt/Cross_Domain_Causality_Weaver/