HamiltonV4

Hamilton V4 Parallel (~100M Parameters)

Uploaded July 11 2026 5:45AM PST

Hamilton V4 is a high-performance continuous-time state space trajectory tracking model optimized for raw telemetry streaming manifolds. Moving away from standard tokenized transformers or legacy sequential loop mechanics, V4 implements alternating symplectic blocks (value dynamics, coupled query-key tracking, and momentum invariants) to execute state updates and manifold smoothing across entire temporal horizons concurrently.

Full explainer here - https://zenodo.org/records/21299022

🔬 Architecture

• Model Parameter Footprint: ~104.5 Million Parameters
• Input Dimension: 12-Dimensional
• Output Projection: 3-Dimensional (Manifold_X, Manifold_Y, Manifold_Z)
• Layer Stack Depth: 16 Interleaved
• Attention Configuration: 16 Attention
• Normalization Strategy: Pre-Layer Normalization
• Temporal Path Evaluator: Multi-step Continuous

⚙️ Local Workspace (Python 3.11)

To initialize the workspace locally inside your standalone H4/ environment directory:

# 1. Install required serialization and tensor backends
pip install torch safetensors numpy transformers huggingface_hub gradio

# 2. Execute local optimization loop to generate optimized parameter matrices
python train_v4.py