webxos/blackhole_synthetic

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Blackhole Synthetic Dataset

UNDER DEVELOPMENT

Dataset Summary

The Blackhole Synthetic Dataset is a curated collection of synthetically generated data focused on black hole physics and astronomical phenomena. This dataset is designed for fine-tuning large language models on scientific reasoning or testing anomaly detection in astrophysical simulations with synthetic emulated datasets.

Dataset Details

• Total images: 1,343
• Format: imagefolder (RGB PNG/JPG)
• File size: ~85 MB
• License: MIT

Generation Method

Synthetic black hole visualizations created with Three.js + custom relativistic shaders.

Features:

• Gravitational lensing
• Accretion disk (thin/thick variations)
• Photon ring
• Doppler beaming & gravitational redshift
• Different spin parameters (a = 0–0.99)
• Varying viewing angles & magnetic field configurations

Intended Use

• Fine-tuning vision-language models on astrophysics reasoning
• Training anomaly/outlier detection in astronomical images
• Benchmarking generative models for relativistic effects
• Educational / visualization demos

Citation (BibTeX)

@misc{blackhole_synthetic,
  author = {webXOS},
  title = {Blackhole Synthetic Dataset},
  year = {2026},
  publisher = {Hugging Face},
}