TriadicFrameworks
Overview

Drift Analyzer

Core Engine for Drift Detection, Drift Classification, and Collapse Prediction (FFT 2026 Edition)#

Metadata#

module: Drift Analyzer
parent_module: FFT Analyzer
layer: Core Frameworks — Structural Spine
version: 2026.1
status: Active, Canonical
drift_categories:
  - operator drift
  - dimensional drift
  - regime drift
  - coherence drift
  - paradox-induced drift
  - collapse drift
session_context:
  drift_sensitivity: extremely_high
  coherence_sensitivity: high
  dimensional_sensitivity: high
  regime_sensitivity: high
cross_module_propagation:
  imports:
    - Coherence Analyzer
    - Dimensional Analyzer
    - Regime Analyzer
    - Operator Engine
    - Paradox Engine
  exports:
    - drift signatures
    - drift vectors
    - collapse diagnostics
    - drift maps

Purpose#

The Drift Analyzer detects unintended directional deviation within a framework.
Drift is the earliest and most reliable indicator of:

  • weakening coherence
  • dimensional instability
  • paradox accumulation
  • operator imbalance
  • regime regression
  • collapse risk

The Drift Analyzer is the early‑warning system of Framework Field Theory.

Drift Model (D0–D7)#

D0 — Null Drift#

No drift detected; stable.

D1 — Operator Drift#

Operator imbalance or inconsistency.

D2 — Dimensional Drift#

Dimensional instability or regression pressure.

D3 — Regime Drift#

Regime‑layer instability or contradiction.

D4 — Coherence Drift#

Weakening harmonic structure or resonance.

D5 — Paradox Drift#

Paradox vectors forming or intensifying.

D6 — Collapse Drift#

Collapse vectors active; downward pressure.

D7 — Field Drift#

Field‑level instability; highest severity.

What the Drift Analyzer Measures#

1. Drift Category#

Identifies the dominant drift type:

  • operator
  • dimensional
  • regime
  • coherence
  • paradox
  • collapse

2. Drift Vectors#

Maps:

  • direction (e.g., C2 → C1, D3 → D2)
  • magnitude (low/moderate/high)
  • trigger (operator, paradox, coherence, regime)

3. Drift Magnitude#

Quantifies drift severity:

  • none
  • low
  • moderate
  • high

4. Drift Sources#

Identifies root causes:

  • operator imbalance
  • paradox overload
  • dimensional stress
  • coherence instability
  • regime contradiction

5. Collapse Risk#

Evaluates whether drift is approaching collapse thresholds.

Analyzer Workflow#

Step 1 — Detect Drift#

Identify drift category (D0–D7).

Step 2 — Map Drift Vectors#

Determine:

  • direction
  • magnitude
  • trigger

Step 3 — Identify Drift Sources#

Analyze:

  • operator pattern
  • coherence envelope
  • dimensional envelope
  • paradox load
  • regime state

Step 4 — Evaluate Collapse Risk#

Determine:

  • soft boundary
  • hard boundary
  • critical boundary

Step 5 — Generate Drift Signature#

Includes:

  • drift category
  • drift vectors
  • drift magnitude
  • collapse risk
  • notes

Drift Engine Structure#

The Drift Analyzer uses the FFT Drift Engine, composed of:

  • Detect Drift — identify drift category and magnitude
  • Map Drift — generate drift vectors and drift maps
  • Analyze Drift — identify drift sources and triggers
  • Predict Collapse — evaluate collapse boundaries and risk

This engine integrates with the Coherence, Dimensional, Regime, and Operator analyzers.

Example (Abbreviated)#

Framework: Narrative Analysis Model
Drift Signature:
  category: D2 (Dimensional Drift)
  vector: D3 → D2 (partial collapse)
  magnitude: moderate
  trigger: operator inconsistency
  collapse_risk: moderate
notes: paradox exposure and operator imbalance weaken dimensional stability

- [Drift Types](/docs/Framework_Field_Theory/Analyzer/Drift/Drift_Types)
- [Drift Vectors](/docs/Framework_Field_Theory/Analyzer/Drift/Drift_Vectors)
- [Collapse Dynamics](/docs/Framework_Field_Theory/Analyzer/Drift/Collapse_Dynamics)
- [Collapse Diagnostics](/docs/Framework_Field_Theory/Analyzer/Drift/Collapse_Diagnostics)
- [Examples](/docs/Framework_Field_Theory/Analyzer/Drift/Examples)
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