SEAT — Sutton Entropy Analysis Tool

Initial public release of SEAT: A modular analysis framework for studying information retention in gravitational wave events.

SEAT performs entropy-based decomposition of LIGO strain data using Shannon, Renyi, and Tsallis models, supporting advanced features like:
• Quantum echo detection
• Mutual information analysis (H1/L1 correlation)
• Bayesian entropy model comparison
• Persistent homology (topological tracking)
• Soft hair memory estimation
• Event-level diagnostics

This tool was designed to make quantum-scale deviations in black hole mergers more accessible and measurable by the broader scientific community.

Note: Quantum echo analysis is optional due to its high computational load.

For academic/non-commercial use.
Feedback and contributions are welcome!