# **Cross‑Domain Causality Weaver (CW) — RTT/1**  
### *Causality‑Intelligence Engine for TriadicFrameworks*

The **Cross‑Domain Causality Weaver (CW)** is the RTT/1 engine responsible for detecting, mapping, and weaving **causal pathways** across conceptual, computational, physical, and dimensional regimes.  
CW forms the causality‑intelligence foundation of the expanded RTT stack, sitting directly above temporal‑level engines and directly below resonance‑level engines.

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**

| Property | Value |
|---------|-------|
| **RTT Level** | 1 |
| **Coherence** | declared |
| **Drift** | bounded |
| **Paradox** | structural |

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**

| Operator | Description |
|----------|-------------|
| **CW‑Weave** | Weaves causal pathways across domains and regimes |
| **CW‑Vector** | Computes causal vector magnitude and direction |
| **CW‑Field** | Maps causal fields and causal topology |
| **CW‑Signature** | Detects causal signatures and causal onset conditions |
| **CW‑Discontinuity** | Identifies causal breaks and discontinuity boundaries |
| **CW‑Stabilize** | Suggests stabilization pathways for causal collapse |

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/`