RTT Interlock Operators — RTT/1

Operator Grammar for the Regime Interlock Mapper (RIM)#

The Regime Interlock Mapper (RIM) uses a deterministic operator grammar to detect, classify, map, and analyze interlocks between RTT regimes (R1–R4).
These operators form the foundation of regime‑level intelligence and feed directly into:

TRS (Triadic Regime Synthesizer)
PGA (Paradox Gradient Analyzer)
CTE (Coherence Tensor Engine)
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. RIM‑Detect#

Detect regime interlocks and boundary conditions#

Purpose
Identify all interlocks between R1–R4, including structural, boundary, entanglement, gradient, and tensor types.

Capabilities

scans regime pairs and triads
detects interlock onset conditions
identifies boundary curvature
flags entanglement loops
detects gradient alignment
detects tensor binding

Output Fields

interlock_type
boundary_condition
onset_condition
coherence_dependency

2. RIM‑Map#

Generate structural maps of regime interlock topology#

Purpose
Produce a full interlock topology map showing how regimes connect, constrain, or influence one another.

Capabilities

maps structural dependencies
maps boundary transitions
maps entanglement loops
maps gradient flows
maps tensor topology

Output Fields

topology_map
boundary_map
gradient_map
tensor_map

3. RIM‑Interlock#

Compute interlock strength, stability, and entanglement#

Purpose
Quantify the strength and stability of each interlock.

Capabilities

computes interlock strength
computes entanglement score
computes stability rating
computes coherence curvature
computes drift sensitivity

Output Fields

interlock_strength
entanglement_score
stability_rating
coherence_curvature
drift_sensitivity

4. RIM‑Boundary#

Identify and classify boundary transitions#

Purpose
Detect and classify boundary conditions between regimes.

Capabilities

detects abstraction‑to‑measurement boundaries
detects gradient‑alignment boundaries
detects coherence‑threshold boundaries
detects drift‑sensitivity boundaries
detects resonance boundaries

Output Fields

boundary_condition
boundary_curvature
boundary_stability

5. RIM‑Entangle#

Detect entanglement interlocks and mutual‑influence loops#

Purpose
Identify high‑coupling interlocks where regimes mutually influence one another.

Capabilities

detects mutual‑feedback loops
detects resonance‑coherence coupling
detects drift‑amplification loops
detects coherence‑gradient coupling
detects tensor entanglement

Output Fields

entanglement_score
coupling_type
coherence_dependency
bidirectional_influence

6. RIM‑Resolve#

Suggest structural resolutions or decompositions#

Purpose
Provide stabilization pathways or decompositions for interlocks.

Capabilities

suggests structural decompositions
suggests stabilization pathways
suggests coherence alignment
suggests drift reduction
suggests tensor rebalancing

Output Fields

resolution_strategy
stabilization_pathway
coherence_alignment
drift_reduction

7. Operator Interaction Grammar#

Detection → Classification → Mapping → Analysis → Resolution#

RIM‑Detect
Finds interlocks and onset conditions.
RIM‑Boundary / RIM‑Entangle
Classifies boundary or entanglement types.
RIM‑Map
Generates topology and gradient/tensor maps.
RIM‑Interlock
Computes strength, stability, entanglement.
RIM‑Resolve
Produces stabilization or decomposition strategies.

This grammar ensures deterministic RTT behavior.

8. Operator Matrix Snippet#

{
  "operator": "RIM-Interlock",
  "interlock_strength": 0.83,
  "entanglement_score": 0.32,
  "stability_rating": 0.71,
  "coherence_curvature": 0.44,
  "drift_sensitivity": 0.27
}

Status#

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

Updated Jul 8, 2026