Drift Analyzer

Module path: Framework_Field_Theory/Analyzer/Drift/ Parent module: FFT Analyzer Layer: Core Frameworks — Structural Spine

Metadata#

module: FFT Drift Analyzer
parent_module: FFT Analyzer
layer: Core Frameworks — Structural Spine
version: 2026.2
status: Active, Canonical
analyzer_type:
  - drift detection
  - drift classification
  - drift mapping
  - paradox-induced drift analysis
 
session_context:
  drift_sensitivity: very_high
  regime_sensitivity: high
  dimensional_envelope: D0–D7
  coherence_requirements:
    - operator grammar must be explicit
    - drift vectors must be declared
    - paradox exposure must be identified
 
cross_module_propagation:
  imports:
    - FFT operator families
    - FFT dimensional architecture
    - FFT coherence engines
    - SARG regime geometry
    - Mode substrate states
    - Substrate Flow invariants
  exports:
    - drift signatures
    - drift maps
    - drift case catalogues
    - paradox drift profiles

Purpose#

The FFT Drift Analyzer identifies, classifies, and maps drift within any framework, system, or conceptual structure modeled using Framework Field Theory. Drift is defined as unintended deviation from a framework's declared dimensional, operator, or coherence envelope.

Unlike the other Analyzer submodules — which diagnose a single structural layer — Drift is the cross-cutting monitor that spans all layers: operators, dimensions, regimes, and coherence. It detects change over time and flags when that change is unintended, accelerating, or paradox-driven.

This analyzer is responsible for:

• detecting drift early
• classifying drift type and velocity
• mapping drift vectors across layers
• identifying paradox-induced drift

It is the temporal watchdog of FFT.

What the Drift Analyzer Detects#

1. Drift Detection#

• Presence or absence of drift
• Drift onset and velocity
• Drift direction relative to the declared envelope

2. Drift Classification#

• Gradual drift — slow, incremental deviation
• Sudden drift — abrupt structural shift
• Oscillating drift — periodic deviation and return
• Paradox drift — deviation caused or amplified by unresolved paradox

3. Drift Mapping#

• Drift vectors across operator, dimensional, regime, and coherence layers
• Drift magnitude and trajectory
• Cross-layer drift correlation

4. Paradox-Induced Drift#

• Paradox density as a drift accelerant
• Feedback loops between drift and paradox exposure
• Paradox-driven collapse risk

Directory Structure#

Drift/
├── README.md
├── Drift_Analyzer.md
├── Drift_Cases.md
└── Paradox_Drift.md

Files#

How to Use the Drift Analyzer#

Step 1 — Declare the Framework Provide: operator pattern, dimensional envelope, regime state, coherence level, and any known drift history.

Step 2 — Detect Drift The analyzer scans for: drift presence, onset timing, velocity, and direction relative to the declared envelope.

Step 3 — Classify Drift Type Categorize the drift as: gradual, sudden, oscillating, or paradox-induced.

Step 4 — Map Drift Vectors Map drift across layers: operator drift, dimensional drift, regime drift, coherence drift. Identify cross-layer correlations.

Step 5 — Evaluate Paradox Exposure If paradox is present: assess paradox density as a drift accelerant, identify feedback loops, flag collapse risk.

Step 6 — Generate Drift Signature A drift signature includes: drift type, velocity, direction, layer distribution, paradox involvement, and projected trajectory.

Example Output#

Framework: Legacy Enterprise Architecture
Drift Signature:
  drift_detected: true
  drift_type: gradual
  velocity: moderate
  direction: D3 → D2 (dimensional contraction)
  layer_distribution:
    operator: low
    dimensional: high
    regime: moderate
    coherence: low
  paradox_involvement: none
  projected_trajectory: continued contraction without intervention
  notes: dimensional envelope shrinking; operator grammar intact; regime drift secondary to dimensional loss

Navigation#

• Drift Analyzer
• Drift Cases
• Paradox Drift

Cross-Module Integration#

Related Modules#

• FFT Analyzer — Parent Analyzer module
• Regime — Regime classification and boundary diagnostics
• Operators — Operator profiling and regime coupling
• Dimensional — Dimensional structure and transitions
• Coherence — Coherence stability and paradox exposure
• Examples — Cross-cutting worked examples

Part of TriadicFrameworks · Framework Field Theory · Analyzer