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economic-geometry

Formal Foundation v1.0 — The Geometry of Economic States

A rigorous mathematical framework for representing, analyzing, and transforming business configurations within a 64-state semantic space.


📐 Overview

Economic Geometry is a formal theory that treats economic agents, capital, and business models as geometric objects in a multidimensional state space. It provides the mathematical foundation for the SUBIT-64 ontology and enables structural analysis of business configurations.

Fundamental Theorem

Every economic entity can be uniquely represented as a vector ω in the product space:

Ω = A × V × T

where:

  • A (WHO — Agency) = {ME, WE, YOU, THEY}
  • V (WHERE — Vector) = {EAST, SOUTH, WEST, NORTH}
  • T (WHEN — Phase) = {SPRING, SUMMER, AUTUMN, WINTER}

This yields |Ω| = 64 canonical states, isomorphic to the 6-bit cube {0,1}⁶.


📁 Repository Structure

economic-geometry/
│
├── README.md                           # This file
├── LICENSE                             # MIT License
├── CITATION.cff                        # Citation metadata for academic use
│
├── axioms/                             # Foundational principles
│   ├── space-definition.md             # Ω = A × V × T: proof of completeness
│   ├── orthogonality-proof.md          # Independence of WHO, WHERE, WHEN
│   └── binary-isomorphism.md           # {0,1}⁶ mapping and Anima/Animus duality
│
├── geometry/                            # Mathematical structure
│   ├── metric-space.md                  # Hamming distance, structural friction SF(ω)
│   ├── geodesics.md                      # Optimal transformation paths
│   ├── observables.md                    # CES, risk, monetization as functionals
│   └── symmetry-group.md                  # Transformation operators T: Ω → Ω
│
├── dynamics/                             # Evolution and change
│   ├── transformation-operators.md        # Scale, Pivot, Harvest, etc.
│   ├── phase-transitions.md                # First and second-order transitions
│   ├── bifurcation-theory.md                # Critical points and instability
│   └── trajectory-prediction.md              # Forecasting business paths
│
├── atlas/                                # Complete mapping of Ω
│   ├── subit-64-catalog.md                # All 64 states with descriptions
│   ├── capital-efficiency-heatmap.md       # CES values across Ω
│   ├── structural-friction-tensor.md       # SF(ω) for all configurations
│   └── risk-profiles/                       # Detailed risk analysis per region
│       ├── quadrant-1.md
│       ├── quadrant-2.md
│       └── ...
│
├── applications/                          # Practical implementations
│   ├── business-diagnostics/                # How to identify ω for real companies
│   │   ├── methodology.md
│   │   └── case-studies/
│   │       ├── amazon-trajectory.md
│   │       ├── tesla-evolution.md
│   │       └── startup-failures.md
│   ├── portfolio-theory.md                   # Diversification as dispersion in Ω
│   ├── investment-criteria.md                 # Geometric due diligence
│   └── policy-framework.md                     # National economic cartography
│
├── extensions/                             # Advanced topics
│   ├── n-dimensional-generalization.md      # Ωₙ beyond 3 dimensions
│   ├── quantum-analogies.md                  # Superposition of business states
│   ├── fractal-hierarchy.md                   # Self-similarity across scales
│   └── category-theory-foundations.md          # Functorial approaches
│
└── implementations/                         # Computational tools
    ├── python/
    └──  README.md
        ├── omega_space.py
        ├── metrics.py
        ├── transformers.py
        └──  visualization/
            ├── lattice-3d.py
            └── trajectory-plotter.py


🎯 Key Contributions

Concept Symbol Definition
State Space Ω A × V × T, the complete economic configuration space
State Vector ω (a, v, t), a point representing a business configuration
Structural Distance d(ω₁, ω₂) Hamming distance between states
Structural Friction SF(ω) Internal inconsistency measure
Capital Efficiency CES(ω) (Fₗ × M_v × Pₜ) - SF, the principal observable
Transformation T: Ω → Ω Operators representing business evolution

🔗 Relationship with SUBIT-Omega-Analyzer

This repository provides the mathematical foundation for the SUBIT-Omega-Analyzer tool:

Repository Purpose
economic-geometry Formal theory, axioms, proofs, mathematical structure
subit-omega-analyzer Practical implementation, prompts, business diagnostics

📖 Getting Started

  1. Begin with the axioms/space-definition.md
  2. Explore the atlas/subit-64-catalog.md to understand all 64 states
  3. Study geometry/metric-space.md for the mathematical core
  4. See applications/business-diagnostics/methodology.md for practical use

🧑‍🤝‍🧑 How to Contribute

We welcome contributions from mathematicians, economists, entrepreneurs, and philosophers. See community/contributing.md for guidelines.

Current priorities:

  • Formal proofs of completeness theorems
  • Empirical validation studies
  • Python implementation of core calculus
  • Case study documentation

📄 License

MIT License


🧬 Version

v1.0 — Geometric Foundation (March 2026)

  • Axiomatic definition of Ω-space
  • Complete metric structure
  • Transformation group specification
  • Full atlas of 64 states

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A rigorous mathematical framework for representing, analyzing, and transforming business configurations within a 64-state semantic space.

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