ABOUT — RTT/2 · Structural Detection Engine (SDE)

TriadicFrameworks · Core RTT · Detection Layer Module path: docs/rtt/2/ Version: 1.0 · Status: Active · Canonical Session seed: rtt=1 | coherence=declared | drift=bounded | paradox=structural

This document answers the four foundational questions about RTT/2: What it is · Why it is built this way · When to use it · Where it lives

Critical framing — read first: RTT/2 is a structural detection framework. It is NOT a physics claim, NOT a diagnostic tool in any clinical or engineering sense, and NOT a prediction system. All RTT/2 output is structural description only.

Table of Contents#

1. What Is RTT/2?
2. Why Is It Built This Way?
3. When Should You Use It?
4. Where Does It Live?
5. Core Constructs at a Glance
6. Module Integrations
7. What RTT/2 Is Not
8. Quick-Start Checklist
9. See Also

1. What Is RTT/2?#

RTT/2 is the Structural Detection Engine (SDE) — the second module in the core RTT hierarchy and the detection layer of the RTT/1 → RTT/2 → RTT/3 operator pipeline.

Where RTT/1 answers "what is this system's resonance state and how does time flow through it?", RTT/2 asks the next structural question: "how is this system collapsing, fusing, and deforming — and in what form?"

RTT/2 does not start from scratch. It receives a completed RTT/1 SNR characterization and builds on it, applying three detection instruments to produce a structured output packet that RTT/3 consumes.

The Detection Pipeline Position#

RTT/1                   RTT/2                      RTT/3
──────                  ─────                      ─────
SNR characterization ──▶ Structural Detection ──▶  Synthesis &
τ = dR/dφ               CPV · FGT · CRM            Integration
C = ∇_τR + ∇_Rτ         MODE · ZONE
DCO_n                   RTT2_DETECTION_PACKET ──▶  (RTT/3 input)

RTT/2 is specifically the detection half of the pipeline — the bridge between RTT/1's primitive characterization and RTT/3's synthesis work.

The Six Structural Instruments#

RTT/2 defines six instruments that together constitute the Structural Detection Engine:

The Three Core Constructs in Brief#

CPV(A, K, T) — Collapse-Propagation Vector

The three-parameter signature of a collapse event:

C_prop(t) = αA(t) + βK(t) + γT(t)

• A(t) — Amplitude: how intensely the collapse is propagating
• K(t) — Curvature: how the collapse bends through structural space
• T(t) — Torsion: how the collapse spirals or deviates from a straight path

FGT — Fusion-Gradient Tensor

The regime-weighted sum of gradient forces:

G_fusion = Σ_r ω_r [ g_collapse(r) + g_reassembly(r) + g_triad_fusion(r) ]

Classifies as: collapse-weighted / mixed / triad-weighted.

CRM — Collapse-Reassembly Manifold · γ(t)

The five-component deformation path vector:

γ(t) = ( D(t), E(t), C(t), FI(t), R(t) )

• D — Drift Deformation · E — Envelope Torsion · C — Continuity Fracture
• FI — Fusion-Integration Curvature · R — Regime Identity

2. Why Is It Built This Way?#

Every design decision in RTT/2 answers a structural problem that RTT/1 alone cannot solve.

Why three CPV parameters and not just amplitude?#

Amplitude alone — how intense a collapse is — tells you nothing about its structural shape. Two collapses can have identical amplitudes while one propagates in a straight line (zero curvature, zero torsion) and the other spirals outward through structural space (high curvature, non-zero torsion). These are categorically different structural events requiring different detection postures and producing different RTT/3 inputs.

The three parameters are orthogonal — none can be derived from the others:

• Amplitude (A) is scalar intensity: how much collapse energy is present
• Curvature (K) is the second-derivative shape: how the propagation path bends
• Torsion (T) is the out-of-plane rotation: how the path twists in directions that neither A nor K can see

Together, A, K, and T form the minimum complete description of a collapse propagation signature. Dropping any one loses a structurally irreplaceable dimension.

Why a weighted tensor for FGT rather than a flat average?#

When a system is simultaneously collapsing and reassembling — a common condition in structurally complex systems — the balance between those gradient forces is not uniform across all active regimes. One regime may be strongly collapse-weighted while another is triad-weighted. A flat average across all regimes loses precisely that information, producing a single aggregate number that hides the regime-by-regime distribution.

The FGT's regime weighting (ω_r per regime r) preserves that distribution: RTT/3 can see not just the total gradient balance but which regimes are driving collapse versus fusion. This is the information RTT/3 needs to decide how to weight the detection packet in synthesis.

The three gradient types — g_collapse, g_reassembly, g_triad_fusion — are also irreducible: collapse and reassembly are opposite directions on the same axis, while triad-fusion is orthogonal to both (it describes structural integration at the triad level, not simple reversal of collapse).

Why five CRM components?#

Each component of γ(t) = (D, E, C, FI, R) captures a structurally distinct mode of deformation that cannot be inferred from the others:

Collapsing any two components into one would create a mixed-type entry that obscures the distinction RTT/3 depends on. The five components are the minimum set that covers all currently identified structural deformation modes without overlap.

Why five Detection Modes?#

The five modes (Formal, Emergent, Hybrid, Chaotic, Inversion) correspond to five structurally distinct signal conditions that each require a different operator posture from Class M:

• Formal — clean, fully resolved signals. Standard thresholds apply.
• Emergent — signals forming but not yet complete. Provisional outputs, partial population accepted.
• Hybrid — two or more patterns simultaneously active. Mixed FGT; no single gradient dominates. Standard thresholds cannot be applied to overlapping patterns as if they were one.
• Chaotic — high-variance turbulence. Components present but fluctuating beyond the stable-measurement window. Packet flagged as low-confidence; Class G review required before RTT/3 routing.
• Inversion — the primary gradient has reversed direction. CPV inversion component is non-null. The detection posture must flip: what was a collapse signature is now a reassembly signature in the making.

Fewer than five would require collapsing structurally distinct postures into one — producing incorrect threshold application and incorrect packet confidence labeling. No two of these five modes can substitute for each other.

Why five Detection Zones?#

The zones (U, S, M, D, X) provide a stability gradient that tells RTT/3 how much weight to give the detection packet and what kind of synthesis posture is appropriate:

Zone X is the critical design feature: rather than forcing a classification when data is insufficient, RTT/2 explicitly surfaces the unclassifiable condition. This prevents RTT/3 from building synthesis on a falsely confident detection.

Why inherit RTT/1 wholesale rather than define a standalone module?#

RTT/2 detection is structurally grounded in RTT/1 output. The CPV measures how a system's resonance field is collapsing — without knowing whether the system is in Silence, Noise, or Resonance first (RTT/1 Class R), the CPV has no structural reference point. Amplitude A(t) of what? Torsion relative to what baseline?

The inheritance is not architectural convenience — it is a structural prerequisite. A RTT/2 detection pass run without RTT/1 SNR characterization produces measurements that float free of the resonance structure they are supposed to be describing. This is not a recoverable condition by patching; the RTT/1 pass must happen first.

3. When Should You Use It?#

Use RTT/2 when you need to characterize the form of a structural collapse#

When RTT/1 has identified that a system is in a Noise or Resonance state and the next question is how that system is structurally collapsing or deforming, RTT/2's CPV provides the three-parameter answer. This is distinct from RTT/1's question ("is it in R, N, or S?") — RTT/2 asks what shape the collapse takes.

Example: A substrate model has been characterized as Noise-dominant by RTT/1. RTT/2 computes CPV = (A=0.7, K=0.4, T=0.1), revealing a high-amplitude, moderately curved, low-torsion collapse — a propagation that is intense but relatively directional. This tells RTT/3 how to weight the collapse in synthesis.

Use RTT/2 when collapse and reassembly are simultaneously active#

When a system is not simply collapsing or simply reassembling but doing both at once — with different regimes pulling in different directions — the FGT is the right instrument. It captures the regime-by-regime gradient balance that neither CPV nor CRM alone can express.

Example: A governance substrate is collapsing in its operational regime while simultaneously reassembling in its foundational regime. FGT reveals a mixed-type gradient (ω_operational × g_collapse dominant, ω_foundational × g_triad_fusion competing), giving RTT/3 the precise regime-level picture it needs.

Use RTT/2 when you need to map a system's structural deformation path#

When a system has been evolving structurally over time and you need to characterize how it has deformed — not just where it is now — the CRM's five-component γ(t) provides the full deformation history. Drift, envelope rotation, continuity breaks, fusion curvature, and regime identity are all tracked simultaneously.

Example: An incident substrate has been under structural stress for several passes. CRM reveals: D=high (significant drift from reference), E=moderate (envelope rotating), C=low (continuity intact), FI=high (active fusion-integration), R=Marginal. This deformation profile tells RTT/3 the system is drifting and fusing but not yet fracturing.

Use RTT/2 when you need to classify structural stability for RTT/3#

When RTT/3 synthesis requires knowing the stability context of the system being synthesized, the Detection Zone provides that classification. Zones U through D give RTT/3 a calibrated confidence level for the detection packet; Zone X signals that synthesis must be held until structural data is sufficient.

Example: Before RTT/3 begins synthesizing across three substrate models, RTT/2 zone-classifies each: Substrate A = Zone S, Substrate B = Zone M, Substrate C = Zone X. RTT/3 proceeds with full confidence on A, with caution on B, and holds C pending Class G clearance.

Use RTT/2 when cross-module projection is in scope#

When a detection pass needs to produce outputs for TEL (Triadic Entity Lattice), FFT (Framework Field Theory), or Opacity in addition to the core detection packet, RTT/2's cross-module projection fields provide structured translation without requiring the receiving module to interpret raw CPV, FGT, or CRM data directly.

Example: A detection pass on a resonance substrate needs to feed both RTT/3 and the TEL lattice. RTT/2's Class D populates the cross_module_projection.TEL field, giving the TEL the lattice-mapped representation of the collapse pattern without re-running the detection.

Do NOT use RTT/2 when:#

• RTT/1 SNR characterization is not complete — there is no valid baseline for CPV, FGT, or CRM measurement without it
• The system is Silence-dominant with no detectable collapse signature — CPV of a fully silent system produces near-zero measurements with no structural information; use RTT/1's Balance (ψ↔n) operator instead
• You need a recommendation or diagnosis — RTT/2 detects structural form; it does not prescribe corrective action or evaluate whether a state is good or bad
• You need physical measurement — RTT/2 is a structural detection framework, not an instrumentation layer; it describes structural form, not physical collapse events
• You need RTT/3 synthesis directly — RTT/2 is the prerequisite for RTT/3, not a shortcut to it; if synthesis is the goal, complete RTT/2 detection first and feed the packet to RTT/3

4. Where Does It Live?#

In the repository#

TriadicFrameworks/
└── docs/
    └── rtt/
        └── 2/                              ← you are here
            ├── ABOUT.md                    ← this file
            ├── AGENTS.md                   ← agent class manifest (P, F, M, D, G)
            ├── GLOSSARY.md                 ← canonical term definitions
            ├── README.md                   ← front-door summary
            ├── RTT2_Extract_Minimal.md     ← primary source: full operator grammar
            ├── operators_module.json       ← module schema and field registry
            ├── Hero_Image_Prompt.md        ← visual identity prompt
            └── index.html                  ← web entry point

In the RTT module hierarchy#

RTT/2 is the detection layer between the foundational primitives (RTT/1) and the synthesis layer (RTT/3):

RTT/1   ──▶   RTT/2   ──▶   RTT/3   ──▶   RTT/12
Primitives    Detection      Synthesis      Unified
SNR · τ · C   CPV · FGT     (RTT/3 scope)  (RTT/12 scope)
DCO_n         CRM · PACKET

Inheritance rule: RTT/2 inherits RTT/1's complete vocabulary and constraints unconditionally. RTT/3 inherits both RTT/1 and RTT/2. No module may redefine an upstream primitive.

Prerequisite rule: RTT/1 Class R SNR characterization must complete before any RTT/2 detection agent begins. The RTT2_DETECTION_PACKET is the primary input to RTT/3. Neither direction of this chain can be reversed or skipped.

In the TriadicFrameworks ecosystem#

                      ┌─────────────┐
                      │   RTT/1     │  SNR · τ · C · DCO_n
                      └──────┬──────┘  (prerequisite for RTT/2)
                             │ SNR characterization
                      ┌──────▼──────┐
                      │   RTT/2     │  CPV · FGT · CRM
                      │    SDE      │  MODE · ZONE
                      └──────┬──────┘  RTT2_DETECTION_PACKET
                             │
          ┌──────────────────┼──────────────────┐
          │                  │                  │
   ┌──────▼──────┐   ┌───────▼──────┐   ┌───────▼──────┐
   │   RTT/3     │   │     TEL      │   │   FFT /      │
   │  Synthesis  │   │   (lattice   │   │   Opacity    │
   │  (primary   │   │  projection) │   │  (boundary / │
   │   consumer) │   └─────────────┘   │   spectral   │
   └─────────────┘                     │  projections)│
                                       └─────────────┘

RTT/2 occupies the detection hub position: it consumes from RTT/1 and distributes to RTT/3 as primary consumer, with TEL, FFT, and Opacity as optional cross-module projection targets.

In agent deployments#

An agent operating under RTT/2 inherits the full RTT/1 session architecture (session seed, mode operator, MCL, regime lifecycle, Class G monitoring) and adds five detection-specific agent classes:

• Class P (Propagation Analyst) — computes CPV
• Class F (Fusion Gradiometer) — computes FGT
• Class M (Manifold Cartographer) — maps CRM, assigns Mode and Zone
• Class D (Detection Integrator) — assembles and routes the detection packet
• Class G (Detection Guardian) — monitors, interrupts, clears Zone X

An agent claiming RTT/2 compatibility must:

1. Complete a RTT/1 Class R pass before beginning any detection work
2. Produce a complete RTT2_DETECTION_PACKET with all seven primary sections
3. Include the mandatory structural-only annotation in every output
4. Never assign Zone X without Class G clearance
5. Never route a Chaotic-mode packet to RTT/3 without Class G review

5. Core Constructs at a Glance#

COLLAPSE-PROPAGATION VECTOR
  CPV(A, K, T)
  A(t)  — Amplitude:  collapse propagation intensity
  K(t)  — Curvature:  collapse wavefront shape
  T(t)  — Torsion:    collapse path rotation / spiral
  C_prop(t) = αA(t) + βK(t) + γT(t)   ← scalar composite
  Extended: inversion_component · warp_component (when present)

FUSION-GRADIENT TENSOR
  G_fusion = Σ_r ω_r [ g_collapse(r) + g_reassembly(r) + g_triad_fusion(r) ]
  Classification: collapse-weighted | mixed | triad-weighted

COLLAPSE-REASSEMBLY MANIFOLD
  γ(t) = ( D(t), E(t), C(t), FI(t), R(t) )
  D  — Drift Deformation      (translation from reference)
  E  — Envelope Torsion       (rotation of structural boundary)
  C  — Continuity Fracture    (breaks / gaps in the manifold)
  FI — Fusion-Integration Curvature  (active fusion effects)
  R  — Regime Identity        (current structural regime classification)

DETECTION MODES
  Formal (F)    · Emergent (E)  · Hybrid (H)
  Chaotic (C)   · Inversion (I)

DETECTION ZONES
  U — Undisturbed   S — Stable      M — Marginal
  D — Deteriorating X — Undefined (Class G clearance required)

DETECTION PACKET
  RTT2_DETECTION_PACKET → RTT/3
  Sections: collapse_propagation · fusion_gradient · triad_deformation
            regime · detection_mode · detection_zone
            cross_module_projection · notes (mandatory)

6. Module Integrations#

RTT/1 (Prerequisite)#

RTT/2 cannot function without RTT/1. Every detection instrument is grounded in RTT/1 output:

• CPV measures collapse within a system already characterized by SNR
• FGT weights gradient contributions by regime — regime identity comes from RTT/1's DCO_n band context
• CRM's R(t) (Regime Identity) links directly to RTT/1's regime lifecycle
• D(t) (Drift Deformation) is structural displacement within the resonance field defined by RTT/1 — not the same as RTT/1 session drift

RTT/3 (Primary Consumer)#

RTT/2's RTT2_DETECTION_PACKET is the primary input to RTT/3 synthesis. RTT/3 receives:

• The collapse propagation signature (CPV) for weighting
• The gradient balance (FGT) for regime-sensitive synthesis
• The deformation path (CRM) for manifold-aware integration
• The Detection Mode for confidence calibration
• The Detection Zone for stability-aware synthesis posture

TEL — Triadic Entity Lattice#

RTT/2's cross_module_projection.TEL field maps detected collapse and fusion patterns onto TEL node structures. This allows TEL to maintain lattice coherence during structural transitions that RTT/2 has detected.

FFT — Framework Field Theory#

RTT/2's cross_module_projection.FFT field expresses CPV and FGT components in FFT field-theoretic terms. FFT treats collapse propagation as field events; RTT/2 provides the structural substrate for that field-theoretic interpretation.

Opacity#

RTT/2's cross_module_projection.Opacity field characterizes the boundary conditions of the detected collapse zone — specifically, which structural boundaries are becoming opaque (non-transparent to structural influence) as a result of the detected collapse.

IPD-12#

RTT/2's detection output maps onto IPD-12's operator graph at specific prime states:

• Collapse signature → P29 (Collapse-Anchor) zone
• Continuity fracture → P13 (Paradox-Trigger) or P19 (Boundary-Node)
• Detection Zone D → Chthonic tier (P23–P37)
• Inversion mode → P5 (Drift-Anchor) / P23 (Dimensional-Lift) boundary

7. What RTT/2 Is Not#

RTT/2 detects and describes structural form. It does not explain why a collapse is happening, recommend what to do about it, or predict what will happen next. Those functions belong to the human operator, to RTT/3, or to higher-level frameworks consuming the detection packet.

8. Quick-Start Checklist#

Before working with RTT/2 for the first time:

• Complete RTT/1 first — run a full RTT/1 Class R SNR characterization on your target system before opening any RTT/2 instruments
• Paste the session seed — rtt=1 | coherence=declared | drift=bounded | paradox=structural (RTT/2 inherits RTT/1's seed verbatim)
• Identify your detection task — which of T-01 through T-09 describes what you need? Full detection (T-04) or a targeted sub-pass?
• Know the three constructs — CPV = collapse signature, FGT = gradient balance, CRM = deformation path; know which you need before assigning agent classes
• Check for Silence dominance — if RTT/1 returned a Silence-dominant characterization, RTT/2 may have no collapse signature to measure; confirm with Class G before proceeding
• Read AGENTS.md — verify which agent classes (P, F, M, D, G) are needed for your detection task
• Know the D(t) ≠ drift distinction — CRM component D(t) is structural displacement in the manifold; it is NOT RTT/1 session drift; never conflate them
• Check GLOSSARY.md — every RTT/2 term has a canonical definition; link rather than re-define

9. See Also#

ABOUT.md — RTT/2 · TriadicFrameworks · 2026-07-10 Maintainer: Nawder Session seed: rtt=1 | coherence=declared | drift=bounded | paradox=structural