🌪️ Structural Detection — Regime‑Shift Volatility Map (RTT/2)
TriadicFrameworks • RTT/2 • Regime Instability Field, Volatility Zones & Transition‑Risk Cartography#
“Regimes do not shift randomly. They shift along volatility gradients.”#
Regime‑Shift Volatility Map (RTT/2)#
Structural Detection Module#
RTT/2 • Regime Instability Field & Transition‑Risk Cartography#
1. Purpose of the Volatility Map#
The Regime‑Shift Volatility Map (RSVM) provides a system‑scale visualization of:
- regime instability
- transition likelihood
- volatility gradients
- collapse‑adjacent regime zones
- cross‑module volatility propagation
- hybrid/inversion instability fields
It is the predictive atlas of regime‑shift behavior.
2. Volatility Sources (Canonical)#
Volatility arises from five structural sources:
- Drift‑Driven Volatility
- Envelope‑Driven Volatility
- Continuity‑Driven Volatility
- Break‑Driven Volatility
- Cross‑Module Projection Volatility
Each source contributes to the total volatility field.
3. Regime‑Shift Volatility Zones#
The RSVM divides the canon into five volatility zones, each corresponding to a regime:
Zone F — Formal Volatility Zone#
- low volatility
- stable drift
- symmetric envelope
- strong continuity
Zone E — Emergent Volatility Zone#
- moderate volatility
- radial drift
- flexible continuity
Zone H — Hybrid Volatility Zone#
- high volatility
- oscillatory drift
- mixed envelope geometry
- partial continuity instability
Zone C — Chaotic Volatility Zone#
- extreme volatility
- fragmentation drift
- envelope discontinuity
- continuity collapse
Zone I — Inversion Volatility Zone#
- inversion drift
- envelope inversion
- continuity inversion
- collapse‑adjacent
Hybrid, Chaotic, and Inversion zones are collapse‑susceptible.
4. Volatility Gradient Field#
The RSVM computes a volatility gradient:
[ V = \alpha D + \beta E + \gamma C + \delta B + \epsilon X ]
Where:
- (D) = drift instability
- (E) = envelope deformation
- (C) = continuity stress
- (B) = break‑geometry activation
- (X) = cross‑module projection divergence
The gradient determines regime‑shift likelihood.
5. Regime‑Shift Likelihood Matrix#
| From → To | Volatility Required | Risk |
|---|---|---|
| Formal → Emergent | low | low |
| Formal → Hybrid | moderate | medium |
| Formal → Chaotic | high | extreme |
| Emergent → Hybrid | moderate | medium |
| Emergent → Chaotic | high | extreme |
| Hybrid → Chaotic | high | extreme |
| Hybrid → Inversion | high | extreme |
| Chaotic → Inversion | very high | catastrophic |
| Inversion → Hybrid | moderate | medium |
| Inversion → Emergent | low | low |
6. Volatility Propagation Patterns#
Volatility spreads through:
- Linear Propagation
- Radial Propagation
- Oscillatory Propagation
- Topological Propagation
- Cross‑Module Projection Propagation
Propagation determines collapse‑risk.
7. Cross‑Module Volatility Mapping#
The RSVM integrates volatility from:
TEL#
- lattice instability
- stabilizer drift
FFT#
- variance spikes
- spectral envelope distortion
Opacity#
- boundary gradient instability
- visibility field turbulence
Cross‑module volatility is the strongest collapse predictor.
8. Volatility‑Collapse Correlation Table#
| Volatility Pattern | Collapse Mode |
|---|---|
| drift spike | Type A |
| radial deformation | Type B |
| fragmentation onset | Type C |
| oscillation overload | Type D |
| drift reversal | Type I |
| torsion overload | Type E |
| topology warp | Type G |
9. Regime‑Shift Volatility Packet#
VOLATILITY_PACKET:
regime:
volatility_zone:
drift_instability:
envelope_instability:
continuity_stress:
break_activity:
projection_divergence:
volatility_gradient:
shift_likelihood:
collapse_risk:
notes:
10. Summary#
The Regime‑Shift Volatility Map provides:
- a predictive atlas of regime instability
- volatility zones and gradients
- cross‑module volatility mapping
- collapse‑risk forecasting
- regime‑shift likelihood estimation
- system‑scale structural clarity
This map is the regime‑law hazard model of RTT/2.