QORVEX v8: The Hyperspace Kernel
🏗️ Total Architecture
Qorvex v8 is a Intelligence kernel that replaces standard attention mechanisms with a Quantum Tensor Network (MPS).
1. The Core: Hyperspace Transformer
- Attention: Uses the
HyperspaceQPU to project attention weights into a quantum state.
- Mechanism: Instead of simple dot-product attention, it calculates expectation values of a Matrix Product State (MPS), allowing for non-linear, high-dimensional structural resonance.
- Config: Target 1024d / 24L / 32H (Qorvex-class).
2. The Nervous System: Calibration-Aware Routing
- CalibrationMap: A real-time map of hardware "noise" and "dead zones."
- Router: Uses a Dijkstra-based pathfinding algorithm to route tensor contractions through the most stable hardware paths.
3. The Cognitive Layer: PUP & SLA²
- PUP: Quantifies uncertainty at every layer, preventing confident hallucinations.
- SLA²: Implements a biologically plausible depth profile (L2 peak, L4 pump) to optimize information flow.
🚶 Walkthrough
- Input $\rightarrow$ Tokenized BPE $\rightarrow$ Embedding.
- Hyperspace Block $\rightarrow$ Quantum Attention (MPS) $\rightarrow$ MLP $\rightarrow$ LayerNorm.
- Routing $\rightarrow$ The
CalibrationRouter optimizes the contraction on the fly.
- Output $\rightarrow$ PUP-weighted prediction $\rightarrow$ Final Token.
📈 Benchmarks
- Iron Gap: Quantifies the gate-cost of quantum emulation vs. native torch.
- Stability: Verified via CPU-fallback for driver-agnostic deployment.