Dimensional Layers

Dimensional layers organize the Resonance Substrate Model into interacting conceptual domains. Each layer contributes unique structures and operators, and cross-layer mappings enable multi-scale behavior.

Quicklinks#

• docs README
• docs api integration examples
• docs api README
• docs api schema overview
• docs api using the schemas
• docs experiments faraday paradox experiment
• docs experiments README
• docs experiments replication checklist
• docs experiments resonance alignment tests
• docs experiments rotating conductor tests
• docs methods field equations
• docs methods operator definitions
• docs methods README
• docs methods substrate dynamics
• docs methods triadic fields
• docs onboarding model map
• docs onboarding reading guide
• docs onboarding triadic quickstart
• docs onboarding verification tests
• docs overview comparison to gr models
• docs overview glossary
• docs overview introduction
• docs overview README
• docs overview resonance primitives
• docs overview theoretical background
• docs simulations boundary conditions
• docs simulations numerical methods
• docs simulations README
• docs simulations solver_architecture
• docs simulations validation metrics
• docs simulations core README
• previous folder

1. Layer Types#

Classical Layer#

Handles scalar, vector, and spin-like fields.

Quantum Layer#

Represents coherence, decoherence, and density structures.

Semantic Layer#

Encodes symbolic or meaning-bearing units.

Distributed Layer#

Coordinates substrate nodes and communication.

2. Cross-Layer Interactions#

Layers influence one another through:

• resonance-driven coupling
• coherence-modulated activation
• semantic modulation of resonance envelopes
• distributed synchronization

These interactions enable unified multi-scale dynamics.

3. Dimensional Mapping#

Mappings include:

• coordinate transforms
• manifold embeddings
• projection operators
• layer-to-layer coupling rules

4. Purpose#

Dimensional layering provides:

• extensibility
• conceptual clarity
• multi-scale modeling capability
• integration of classical, quantum, and semantic behaviors