metadata
license: mit
task_categories:
- other
language:
- en
- mr
tags:
- coordinates
- geometry
- vedic
- multiverse
- hypersphere
- orthogonal
- rotation-matrices
- neural-geometry
- 3d
- 8d
- 16d
- 32d
- 64d
pretty_name: Multiverse Field Coordinates
size_categories:
- 100M<n<1B
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/ ├── layer_01/ │ ├── coords_3d.csv │ ├── coords_8d.csv │ ├── coords_16d.csv │ ├── coords_32d.csv │ └── coords_64d.csv ├── layer_02/ │ └── ... (same) ... └── layer_07/ └── ... (same)
CSV Format
- पहिला कॉलम:
ID(1–108) - बाकी कॉलम:
0ते360(अंश) - प्रत्येक सेल: comma-separated vector
उदाहरण (3D):0.123456,-0.234567,0.890123
Mathematical Foundation
- प्रत्येक ID साठी deterministic orthogonal matrix (QR decomposition)
- कोन θ नुसार unit hypersphere वर base point
- Orthogonal matrix ने rotate
- Layer नुसार radius scaling
- 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{multiverse_field_coordinates, author = {kalpesh77}, title = {Multiverse Field Coordinates – Vedic Neural Geometry}, year = {2025}, url = {https://huggingface.co/datasets/kalpesh77/Multiverse-field-coordinates} }
License
MIT