Metadata-Version: 2.4
Name: entro-ghost
Version: 1.0.0
Summary: ENTRO-GHOST: Entropic Memory and Residual Pattern Discovery in Informational Voids
Author-email: Samir Baladi <gitdeeper@gmail.com>
License: MIT
Project-URL: Homepage, https://entro-ghost.netlify.app
Project-URL: GitHub, https://github.com/gitdeeper10/ENTRO-GHOST
Project-URL: GitLab, https://gitlab.com/gitdeeper10/ENTRO-GHOST
Project-URL: Bitbucket, https://bitbucket.org/gitdeeper-10/entro-ghost
Project-URL: Codeberg, https://codeberg.org/gitdeeper10/entro-ghost
Project-URL: DOI, https://doi.org/10.5281/zenodo.19504584
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: System :: Distributed Computing
Requires-Python: >=3.11
Description-Content-Type: text/markdown
License-File: LICENSE
License-File: NOTICE
License-File: AUTHORS.md
Dynamic: license-file

# 👻 ENTRO-GHOST (E-LAB-08)

## Entropic Memory and Residual Pattern Discovery in Informational Voids

[![PyPI version](https://badge.fury.io/py/entro-ghost.svg)](https://pypi.org/project/entro-ghost/)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.19504584.svg)](https://doi.org/10.5281/zenodo.19504584)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

---

## 📖 Overview

ENTRO-GHOST introduces the **Entropic Memory Framework (EMF)** that treats residual information — the thermodynamic traces left by prior computational states — as actionable signals rather than discarded noise.

### Key Contributions

| Component | Description |
|-----------|-------------|
| **Ghost Trace Γ(t)** | Exponentially-weighted integral of stability history |
| **Ghost Recovery Algorithm** | Augments control with recall force: u_GRA = u + ζ·(Ψ* - Γ) |
| **Void Pattern Detector** | Treats informational gaps as latent potential energy |
| **Holographic Stability Protocol** | Distributed memory with Byzantine fault tolerance |

### Results

- **47.3% reduction** in recovery time after catastrophic collapse
- **Unconditional stability** guarantees (Routh-Hurwitz)
- **Byzantine fault tolerance** up to ⌊(M-1)/2⌋ corrupted subsystems

---

## 🚀 Quick Install

```bash
pip install entro-ghost
```

🔬 Quick Start

```python
from entro_ghost import GhostRecoveryOptimizer

# Initialize with default parameters
gra = GhostRecoveryOptimizer(alpha=0.1, zeta=0.65)

# Update ghost trace and get control signal
psi = 0.85      # current stability
psi_star = 0.95 # target stability
u_baseline = 0.1

result = gra.control(psi, psi_star, u_baseline)
print(f"Ghost pull: {result['u_ghost']:.3f}")
print(f"Total control: {result['u_total']:.3f}")
```

---

📚 Documentation

· Website: https://entro-ghost.netlify.app
· Paper: DOI: 10.5281/zenodo.19504584
· API Docs: https://entro-ghost.readthedocs.io

---

🧬 EntropyLab Program

E-LAB Project Focus
01 ENTROPIA Theoretical foundations
02 ENTRO-AI AI inference stability
03 ENTRO-CORE Core measurement
04 ENTRO-ENGINE System coupling
05 ENTRO-EVO Adaptive weighting
06 ENTRO-NET Distributed sync
07 ENTRO-QUANTUM Probabilistic states
08 ENTRO-GHOST Entropic memory
09 (forthcoming) -
10 ENTRO-MANIFESTO Unified manifesto

---

📝 Citation

```bibtex
@software{baladi2026entroghost,
  author = {Samir Baladi},
  title = {ENTRO-GHOST: Entropic Memory and Residual Pattern Discovery},
  year = {2026},
  doi = {10.5281/zenodo.19504584},
  note = {E-LAB-08}
}
```

---

📄 License

MIT License © 2026 Samir Baladi

---

Part of the EntropyLab Research Program
"Systems that know where they have been can find their way back significantly faster than systems that do not."
