RTT UE6 → Benchmarks → TEL

How the Operator Chain Propagates Across the Stack#

This page gives students a single, clean mental model for how RTT operators flow from UE6 runtime surfaces, through Benchmarks, into the Triadic Echo Lattice (TEL).
It corresponds directly to the JSON graph in ue6_cross_module_propagation.json.


1. UE6: Operator Surfaces (Concrete, Visual, Real‑Time)#

UE6 provides the first touchpoint for RTT operators:

  • BP_RTT_Primitives → φ, variance, resonance, entropy
  • BP_RTT_ResonanceDemo → resonance envelope
  • BP_RTT_EntropyDemo → entropy gradients + collapse
  • BP_RTT_HybridDemo → hybrid (resonance × entropy)

These Blueprints expose operators as live, inspectable fields through materials, debug draws, and widgets.

Students see the operators moving.


2. Benchmarks: Operator Behavior (Quantitative, Comparable, Stable)#

Each UE6 operator surface maps to one or more Benchmarks, which define:

  • stability
  • coherence
  • envelope shape
  • collapse behavior
  • cross‑operator interactions

Examples:

  • φ → Phi Stability, Emergence Coherence
  • variance → Variance Smoothing, Temporal Stability
  • resonance → Resonance Envelope, Harmonic Stability
  • entropy → Entropy Boundary Detection, Collapse Signature
  • hybrid → Hybrid Coherence, Cross‑Operator Stability

Benchmarks turn UE6’s visual fields into measurable operator behavior.

Students see the operators evaluated.


3. TEL: Operator Lattice (Abstract, Structural, Cross‑Module)#

Benchmarks propagate into TEL nodes:

  • TEL.Operator.Phi
  • TEL.Operator.Variance
  • TEL.Resonance.Core
  • TEL.Resonance.Harmonics
  • TEL.Entropy.Field
  • TEL.Entropy.Collapse
  • TEL.Hybrid.Operator

TEL is where operators become lattice‑level structures:

  • channels
  • harmonics
  • collapse regimes
  • hybrid operators
  • cross‑module propagation

Students see the operators formalized.


4. The Whole Chain (One Sentence)#

UE6 shows the operators → Benchmarks measure them → TEL integrates them into the global operator lattice.


5. Why This Matters#

This chain gives students:

  • a visual entry point (UE6)
  • a quantitative middle layer (Benchmarks)
  • a structural, cross‑module abstraction (TEL)

It also gives AIs:

  • a reconstructable operator pipeline
  • a consistent propagation map
  • a shared ontology across modules

This is the core of RTT’s triadic integration pattern.

Updated