CTE Operators — RTT/1

Operator Grammar for the Coherence Tensor Engine#

The Coherence Tensor Engine (CTE) defines the coherence‑layer intelligence of RTT.
Its operators compute coherence tensors, map coherence fields, evaluate gradients, detect collapse points, and propose stabilization pathways.

These operators feed directly into:

• DS — Drift Sentinel
• SFD — Structural Faultline Detector
• SBC — Stability Basin Cartographer
• TRS‑Temporal — Temporal Regime Sequencer
• CW — Cross‑Domain Causality Weaver
• DRS — Dimensional Resonance Scanner

1. CTE‑Compute#

Compute coherence tensors from regime inputs#

Purpose
Generate coherence tensors by evaluating structural, gradient, boundary, and drift‑sensitive coherence conditions.

Capabilities

• computes tensor magnitude
• computes tensor direction
• evaluates structural invariants
• evaluates coherence dependencies
• evaluates drift influence

Output Fields

• tensor_type
• tensor_magnitude
• tensor_direction
• coherence_dependency

2. CTE‑Tensor#

Construct multi‑dimensional coherence tensor structures#

Purpose
Build coherence tensors across conceptual, computational, physical, and dimensional regimes.

Capabilities

• constructs multi‑regime tensors
• binds coherence across R1–R4
• evaluates tensor curvature
• evaluates tensor alignment
• evaluates tensor stability

Output Fields

• tensor_structure
• tensor_curvature
• tensor_alignment
• tensor_stability

3. CTE‑Gradient#

Compute coherence gradient vectors#

Purpose
Calculate coherence gradient magnitude, direction, curvature, and drift sensitivity.

Capabilities

• computes gradient magnitude
• computes gradient direction
• computes coherence curvature
• computes drift sensitivity
• computes tensor‑gradient alignment

Output Fields

• gradient_magnitude
• gradient_direction
• coherence_curvature
• drift_sensitivity
• gradient_alignment

4. CTE‑Field#

Map coherence fields and tensor topology#

Purpose
Generate coherence field maps showing curvature, ridges, wells, and tensor topology.

Capabilities

• maps coherence fields
• maps tensor topology
• maps coherence ridges
• maps coherence wells
• maps gradient flows

Output Fields

• field_map
• tensor_topology
• ridge_map
• well_map
• gradient_flow_map

5. CTE‑Collapse#

Detect coherence collapse points and instability basins#

Purpose
Identify collapse points, instability basins, and coherence troughs.

Capabilities

• detects collapse points
• detects instability basins
• detects coherence troughs
• evaluates collapse curvature
• evaluates collapse depth

Output Fields

• collapse_point
• collapse_depth
• collapse_curvature
• instability_basin

6. CTE‑Stabilize#

Propose coherence stabilization pathways#

Purpose
Provide stabilization strategies for coherence tensors, gradients, and collapse points.

Capabilities

• proposes stabilization pathways
• proposes coherence alignment
• proposes drift reduction
• proposes tensor rebalancing
• proposes collapse mitigation

Output Fields

• stabilization_pathway
• coherence_alignment
• drift_reduction
• tensor_rebalance
• collapse_mitigation

7. Operator Interaction Grammar#

Compute → Tensor → Gradient → Field → Collapse → Stabilize#

1. CTE‑Compute
   Generates coherence tensors from regime inputs.

2. CTE‑Tensor
   Builds multi‑regime tensor structures.

3. CTE‑Gradient
   Computes coherence gradient vectors and curvature.

4. CTE‑Field
   Maps coherence fields, ridges, wells, and tensor topology.

5. CTE‑Collapse
   Detects collapse points and instability basins.

6. CTE‑Stabilize
   Produces stabilization pathways and coherence alignment strategies.

This grammar ensures deterministic coherence‑layer behavior.

8. Operator Matrix Snippet#

{
  "operator": "CTE-Gradient",
  "gradient_magnitude": 0.83,
  "gradient_direction": "R1↔R4",
  "coherence_curvature": 0.52,
  "drift_sensitivity": 0.18,
  "gradient_alignment": 0.88
}

Status#

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