Metadata-Version: 2.4
Name: quantum-entangled-knowledge-graphs
Version: 0.1.0
Summary: World's first open-source library for quantum-enhanced knowledge graph reasoning using entanglement principles
Home-page: https://github.com/krish567366/quantum-entangled-knowledge-graphs
Author: Krishna Bajpai
Author-email: Krishna Bajpai <bajpaikrishna715@gmail.com>
Maintainer-email: Krishna Bajpai <bajpaikrishna715@gmail.com>
License: MIT
Project-URL: Homepage, https://github.com/krish567366/quantum-entangled-knowledge-graphs
Project-URL: Documentation, https://krish567366.github.io/quantum-entangled-knowledge-graphs/
Project-URL: Repository, https://github.com/krish567366/quantum-entangled-knowledge-graphs
Project-URL: Bug Tracker, https://github.com/krish567366/quantum-entangled-knowledge-graphs/issues
Keywords: quantum computing,knowledge graphs,quantum entanglement,graph neural networks,quantum machine learning,semantic reasoning,artificial intelligence
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Software Development :: Libraries :: Python Modules
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License-File: LICENSE
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# Quantum Entangled Knowledge Graphs (QE-KGR)

[![PyPI version](https://badge.fury.io/py/quantum-entangled-knowledge-graphs.svg)](https://badge.fury.io/py/quantum-entangled-knowledge-graphs)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Documentation](https://img.shields.io/badge/docs-github_pages-blue.svg)](https://krish567366.github.io/quantum-entangled-knowledge-graphs/)

> 🚀 **World's First Open-Source Library** for quantum-enhanced knowledge graph reasoning using entanglement principles

## 🧠 What is QE-KGR?

QE-KGR (Quantum Entangled Knowledge Graph Reasoning) revolutionizes how we represent and reason over complex knowledge by applying quantum mechanics principles to graph theory. Unlike classical knowledge graphs, QE-KGR enables:

- **Quantum Superposition** of multiple relations simultaneously
- **Entanglement-based reasoning** for discovering hidden connections
- **Interference patterns** for enhanced link prediction
- **Non-classical logic** for handling uncertainty and context

## ⚛️ Core Features

### 🔗 Entangled Graph Representation

- Nodes as quantum states (density matrices/ket vectors)
- Edges as entanglement tensors with superposed relations
- Tensor network representation for efficient computation

### 🧮 Quantum Inference Engine

- Quantum walks for graph traversal
- Grover-like search for subgraph discovery
- Interference-based link prediction
- Entanglement entropy measurements

### 🔍 Quantum Query Processing

- Vector-based semantic queries
- Hilbert space projections
- Superposed query chains
- Context-aware reasoning

### 📊 Advanced Visualization

- Interactive entangled graph visualization
- Entropy heatmaps and quantum state projections
- Real-time inference path highlighting

## 🚀 Quick Start

### Installation

```bash
pip install quantum-entangled-knowledge-graphs
```

### Basic Usage

```python
import qekgr
from qekgr.graphs import EntangledGraph
from qekgr.reasoning import QuantumInference
from qekgr.query import EntangledQueryEngine

# Create an entangled knowledge graph
graph = EntangledGraph()

# Add quantum nodes and entangled edges
alice = graph.add_quantum_node("Alice", state="physicist")
bob = graph.add_quantum_node("Bob", state="researcher")
graph.add_entangled_edge(alice, bob, relations=["collaborates", "mentors"], 
                        amplitudes=[0.8, 0.6])

# Initialize quantum reasoning engine
inference_engine = QuantumInference(graph)

# Perform quantum walk-based reasoning
result = inference_engine.quantum_walk(start_node=alice, steps=10)

# Query with entanglement-based search
query_engine = EntangledQueryEngine(graph)
answers = query_engine.query("Who might Alice collaborate with in quantum research?")
```

## 🏗️ Architecture

```bash
qekgr/
├── graphs/          # Quantum graph representations
├── reasoning/       # Quantum inference algorithms  
├── query/          # Entangled query processing
└── utils/          # Visualization and utilities
```

## 📚 Applications

- **Drug Discovery**: Finding hidden molecular interaction patterns
- **Scientific Research**: Discovering interdisciplinary connections
- **Social Network Analysis**: Understanding complex relationship dynamics
- **Recommendation Systems**: Quantum-enhanced collaborative filtering
- **Knowledge Discovery**: Uncovering latent semantic bridges

## 🔬 Theoretical Foundation

QE-KGR is built on rigorous quantum mechanical principles:

- **Hilbert Space Embeddings**: Knowledge represented in complex vector spaces
- **Tensor Networks**: Efficient quantum state manipulation
- **Entanglement Entropy**: Measuring information correlation
- **Quantum Interference**: Constructive/destructive amplitude patterns

## 📖 Documentation

Comprehensive documentation is available at: [krish567366.github.io/quantum-entangled-knowledge-graphs](https://krish567366.github.io/quantum-entangled-knowledge-graphs/)

## 🤝 Contributing

We welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for details.

## 📝 License

MIT License - see [LICENSE](LICENSE) file for details.

## 👨‍💻 Author

**Krishna Bajpai**

- Email: bajpaikrishna715@gmail.com
- GitHub: [@krish567366](https://github.com/krish567366)

## 🙏 Acknowledgments

This project draws inspiration from quantum computing research and modern graph neural networks. Special thanks to the quantum computing and knowledge graph communities.

---

*"In the quantum realm, knowledge is not just connected—it's entangled."* 🌌
