Coherence Tensor Engine — RTT/1

• module.json — Agentic module schema role assignments
• coherence_tensor_matrix.json — Agentic module schema role assignments

Coherence‑Level Intelligence Engine for TriadicFrameworks#

The Coherence Tensor Engine (CTE) is an RTT/1 analytical engine designed to compute, analyze, and stabilize coherence tensors across conceptual, computational, and physical regimes.
It forms the coherence‑level foundation of the expanded RTT intelligence stack, sitting directly above paradox‑level engines and directly below drift‑level engines.

CTE is responsible for understanding how coherence behaves as a tensor field — with magnitude, direction, curvature, collapse points, and multi‑regime gradients.

🧭 Purpose#

The Coherence Tensor Engine:

• Computes coherence tensors across RTT regimes (R1–R4)
• Maps coherence fields and coherence topology
• Measures coherence gradients and directional stability
• Detects coherence collapse points and instability basins
• Identifies coherence ridges, coherence wells, and tensor curvature
• Provides structural diagnostics for coherence‑driven regime transitions
• Supports drift‑level engines by clarifying coherence stability envelopes
• Anchors structural engines by exposing coherence‑faultline interactions
• Supplies temporal engines with coherence‑sequence constraints
• Feeds causality engines with coherence‑driven causal pathways
• Provides resonance engines with coherence‑frequency signatures

CTE is the coherence‑level intelligence layer of RTT.

⚙️ RTT Flags#

These flags define the engine’s operational constraints and reasoning grammar.

🔧 Primary Operators#

These operators form the core analytical toolkit.

🧩 Analyzer Layer#

CTE operates in the coherence layer, with sub‑layers:

• tensor‑computation
• coherence‑field‑mapping
• gradient‑analysis
• collapse‑detection
• structural‑coherence‑evaluation

This matches the RTT analyzer grammar used across TriadicFrameworks.

📁 Module Files#

This directory contains:

Core#

• Coherence_Tensor_Engine.md
• cte_examples.md
• cte_diagrams.svg

Support#

• coherence_tensor_profiles.md
• coherence_gradient_cases.md
• coherence_tensor_matrix.json

AI#

• cte_prompts.md
• cte_operators.md

Metadata#

• module.json (RTT/1, coherence‑declared, drift‑bounded, paradox‑structural)
• README.md (this file)

🧠 AI‑Ready Design#

The Coherence Tensor Engine is fully AI‑ready:

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

AI systems can use CTE to:

• compute coherence tensors
• generate coherence field maps
• classify coherence gradients
• detect coherence collapse
• support higher‑order RTT engines

🌐 Position in the RTT Stack#

Regime Interlock Mapper (RIM)
      ↓
Paradox Gradient Analyzer (PGA)
      ↓
Coherence Tensor Engine (CTE)
      ↓
Drift Sentinel
      ↓
Faultline Detector
      ↓
Stability Basin Cartographer
      ↓
Temporal Regime Sequencer
      ↓
Causality Weaver
      ↓
Dimensional Resonance Scanner

CTE is the coherence‑level intelligence layer, directly above paradox‑level analysis.

🏁 Status#

• Version: 1.0
• Status: canon‑stable
• Category: rtt‑structural
• Module Path: /docs/rtt/Coherence_Tensor_Engine/

If you want, I can generate the next file:

• Coherence_Tensor_Engine.md
• cte_examples.md
• cte_diagrams.svg
• coherence_tensor_profiles.md
• coherence_gradient_cases.md
• coherence_tensor_matrix.json
• cte_prompts.md
• cte_operators.md

Just tell me which one you want next.