kalpesh77/Multiverse-field-coordinates

Multiverse-field-coordinates

Vedic Neural Geometry – Multiverse Field Dataset

एक सार्वत्रिक, शुद्ध-संख्यात्मक, बहुआयामी कॉऑर्डिनेट सिस्टीम. ओलंपिक मैदानाप्रमाणे एकच मैदान — ज्यातून वेगवेगळ्या विषयांवर कॉऑर्डिनेशन / mapping करता येते.

Core Concept

• —केंद्र (Bindu / Brahma): सर्व आयामांमध्ये केंद्रबिंदू
• —Angular Grid: 0° ते 360° (1° स्टेप)
• —ID: 1 ते 108 (108 Divisions)
• —Layers (Avaran): 7 थर
• —Dimensions: 3D, 8D, 16D, 32D, 64D
• —Math Engine: Orthogonal bases + Rotation matrices
• —Complementary: 0° आणि 180° exact opposite (जसे RGB ↔ CMY)

Dataset Structure

data/ ├── layer01/ │ ├── coords3d.csv │ ├── coords8d.csv │ ├── coords16d.csv │ ├── coords32d.csv │ └── coords64d.csv ├── layer02/ │ └── ... (same) ... └── layer07/ └── ... (same)

CSV Format

• —पहिला कॉलम: ID (1–108)
• —बाकी कॉलम: 0 ते 360 (अंश)
• —प्रत्येक सेल: comma-separated vector उदाहरण (3D): 0.123456,-0.234567,0.890123

Mathematical Foundation

1. 1.प्रत्येक ID साठी deterministic orthogonal matrix (QR decomposition)
2. 2.कोन θ नुसार unit hypersphere वर base point
3. 3.Orthogonal matrix ने rotate
4. 4.Layer नुसार radius scaling
5. 5.0° ↔ 180° = exact complementary (negative vector)

Intended Use

• —Multi-dimensional embedding / coordinate systems
• —Geometric neural networks
• —Symbolic / Vedic geometry experiments
• —Universal mapping field for different domains
• —Research on orthogonal and rotational structures

Generation

Generated using pure NumPy with:

• —Orthogonal frames via QR
• —Hyperspherical coordinates
• —Layer-wise radial scaling

Citation

@dataset{multiversefieldcoordinates, author = {kalpesh77}, title = {Multiverse Field Coordinates – Vedic Neural Geometry}, year = {2025}, url = {https://huggingface.co/datasets/kalpesh77/Multiverse-field-coordinates} }

License

MIT