Rings of Saturn (ℝ¹→ℝ⁵ Projection)

Blockchain-to-5D Spiral Embedding for Trustworthy Machine Learning

Rings of Saturn is a reference implementation of the Spiral–HDAG–Coupling architecture.
It combines a verifiable ledger, a tensor-based Hyperdimensional DAG (HDAG),
and Time Information Crystals (TICs) to provide a spiralicious new kind of memory layer for Machine Learning.
With integrated Zero-Knowledge ML (ZKML), the system enables trustworthy, auditable, and privacy-preserving AI pipelines.

Installation

Clone the repository

git clone https://github.com/example/rings-of-saturn.git
cd rings-of-saturn

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

pip install --upgrade pip
pip install -r requirements.txt

Note: For GPU-based workloads, a separate PyTorch installation may be required.
Please refer to the official PyTorch installation guide

Quick Example

The following snippet demonstrates how to persist a sensor event in the Ledger and then compute a resonance score in the HDAG.

import torch
from ledger import Ledger
from hdag.hdag import HDAG
ledger = Ledger()
ledger.add_transaction({"sensor": "lumen", "value": 1337})
block = ledger.create_block()
assert ledger.validate_chain()

hdag = HDAG()
hdag.add_node("sensor", torch.tensor([1.0, 0.5, 0.1]))
hdag.add_node("feature", torch.tensor([0.8, 0.55, 0.05]))
hdag.add_edge("sensor", "feature", 0.9)

print("Resonance:", hdag.resonance(hdag.nodes["sensor"], hdag.nodes["feature"]))

For more details on the architecture, APIs, and example workflows, please refer to the project documentation.

License

This project is licensed under the Apache-2.0 License.