Metadata-Version: 2.1
Name: quantum_bb84simulator
Version: 1.1.0
Summary: A comprehensive Python library for simulating the BB84 quantum key distribution protocol.
Home-page: 
Author: Syon Balakrishnan
Author-email: balakrishnansyon@gmail.com
License: MIT
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
License-File: LICENSE.txt
Requires-Dist: qiskit>=0.37.0
Requires-Dist: matplotlib>=3.5.0
Requires-Dist: numpy>=1.21.0
Provides-Extra: dev
Requires-Dist: pytest; extra == "dev"
Requires-Dist: pytest-cov; extra == "dev"
Requires-Dist: sphinx; extra == "dev"

# BB84 Simulation Library

A comprehensive Python library for simulating the **BB84 quantum key distribution protocol**, now enhanced with **AI-based eavesdropping detection, advanced noise models, Qiskit integration, and improved visualization tools.**

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## **Features**
### **🔑 Complete BB84 Protocol**
- Qubit preparation, transmission, and measurement.
- Key sifting, error correction, and privacy amplification.

### **🔍 Advanced Eavesdropping & Security Features**
- Configurable noise models: depolarizing, amplitude damping, phase damping, and readout errors.
- **NEW:** AI-based eavesdropper detection using **Isolation Forest**.
- **NEW:** Simulated **lossy channel effects** on key transmission.

### **📊 Visualization Tools**
- Protocol workflow visualization.
- Noise impact visualization.
- Key sifting visualization.
- **NEW:** **Real-time QBER visualization** for intrusion detection.

### **💻 Quantum Execution**
- **NEW:** IBM **Qiskit Integration** for running BB84 on real quantum hardware.

### **🛠 Extensible & Modular Design**
- Modular architecture for easy integration of additional features.
- **NEW:** Caching for quantum noise models to optimize performance.

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## **Installation**

### **Prerequisites**
- Python 3.8+
- pip package manager
- Install dependencies:
  ```bash
  pip install -r requirements.txt
