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2.6 KiB
2.6 KiB
Manifold Flow: Geometric State
Authors: Research Stack Team Date: April 2026 Domain: TTM Layer A (Compression/Routing) + Manifold Theory OTOM Version: 2.2
References: See 00_Master_References.md for complete source mapping
Abstract
Manifold Flow provides the geometric foundation for state evolution in OTOM. It models computation as flow on a Riemannian manifold, with curvature determining computational difficulty and geodesics representing optimal computation paths. The manifold flow is now extended with geometric structure folding (Torus-Menger-Horn) and meta-manifold language merging for cross-linguistic semantic analysis.
1. Manifold Structure
1.1 State Manifold
\mathcal{M} = \mathbb{R}^7 \times \mathbb{R}_{>0}
Seven-dimensional state space with positive-definite metric.
1.2 State Components
(\rho, v, \tau, \sigma, q, \kappa, \varepsilon) \in \mathcal{M}
| Variable | Meaning |
|---|---|
\rho |
Compression gain |
v |
Velocity |
\tau |
Decoder complexity |
\sigma |
Resource usage |
q |
Queue depth |
\kappa |
Curvature |
\varepsilon |
Energy |
2. Potential Field
2.1 Base Potential
\phi(x) = \frac{\text{numerator}(x)}{\text{geometry}(x) \cdot \text{energy}(x)}
2.2 Numerator
\text{numerator}(x) = \rho^2 + v^2 + \tau^2 + \sigma^2 + q^2
2.3 Geometry
\text{geometry}(x) = 1 + \kappa^2
2.4 Energy
\text{energy}(x) = 1 + \varepsilon
3. Gradient Flow
3.1 Gradient
\nabla \phi(x) = \left(\frac{\partial \phi}{\partial \rho}, \frac{\partial \phi}{\partial v}, \frac{\partial \phi}{\partial \tau}, \frac{\partial \phi}{\partial \sigma}, \frac{\partial \phi}{\partial q}, \frac{\partial \phi}{\partial \kappa}, \frac{\partial \phi}{\partial \varepsilon}\right)
3.2 Flow
\text{flow}(x) = -\nabla \phi(x)
4. Theorems
4.1 Non-negativity
\forall x, \text{WellFormed}(x) \implies \phi(x) \geq 0
4.2 Geometry Positivity
\forall x, \text{geometry}(x) > 0
4.3 Energy Positivity
\forall x, \text{WellFormed}(x) \implies \text{energy}(x) > 0
5. Implementation
Lean 4 Modules:
ManifoldFlow.lean— Core flow mechanicsManifoldPotential.lean— Potential functionsTriangleManifold.lean— Triangular manifold structureUnifiedConvictionFlow.lean— Unified flow framework
6. References
- Do Carmo, M.P. (1992). Riemannian Geometry.
- Lee, J.M. (2012). Introduction to Smooth Manifolds.
- Research Stack, OTOM Ontology v2.2.