ARCHITECTURE.md

# LOGOS Architecture: The Prime-Manifold Protocol

## 1. The Core Thesis
LOGOS is a **Manifold-Constrained Data Transport Protocol** that implements **Nested Domain Learning** at the bitstream layer. It replaces probabilistic software routing with deterministic prime topology.

## 2. Theoretical Convergence

### A. Hardware-Native "HOPE" (Nested Domains)
Google's **HOPE** architecture separates learning into hierarchical "neighborhoods" to prevent catastrophic forgetting. LOGOS implements this physically via **Matroska Shells**:
* **Inner Shells (Meta-Heat):** Low-entropy, high-persistence data anchored by Low-GPF primes (2, 3, 5). Equivalent to HOPE's "Slow Learning" layers.
* **Outer Shells (Delta-Heat):** High-entropy, high-variance data anchored by High-GPF primes. Equivalent to HOPE's "Fast Learning" layers.
* **Mechanism:** Data is not routed by a neural network; it is sorted by its **Prime Harmonic Resonance**.

### B. Intrinsic "mHC" (Manifold Constraints)
DeepSeek's **mHC** stabilizes networks by projecting connections onto a manifold. LOGOS achieves this via **Radial Prime Topology**:
* **The Constraint:** Data atoms are valid ONLY if they align with the **Mod 10 Prime Vectors (1, 3, 7, 9)**.
* **The Manifold:** The "Web" created by connecting Composites to their **Greatest Prime Factor (GPF)** forms a closed geometric surface.
* **Stability:** Signal variance ("Heat") is dissipated by traversing this web from Outer Shells to Inner Shells, structurally preventing gradient explosion.

## 3. The SPCW Engine (The Implementation)
* **Input:** Raw Data Stream (Video/Image).
* **Process:** Adaptive Quadtree Decomposition (The Baker).
* **Routing:** 
    * **Persistence (00):** Mapped to Inner Shell (Meta).
    * **Change (11):** Mapped to Outer Shell (Delta).
* **Validation:** Harmonic Checksum verifies that the Sum of Delta Heat matches the Topological Address.

## 4. Summary for System Architects
LOGOS is not just compression. It is a **Geometric Stability Engine**. It allows high-throughput AI streams to "self-organize" into nested domains of validity, reducing the thermal and computational load on the receiving hardware.

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*Bridging Google’s Software Topology (HOPE) with DeepSeek’s Mathematical Constraint (mHC) using LOGOS’s Physical Geometry.*