143 líneas
3.3 KiB
Markdown
143 líneas
3.3 KiB
Markdown
# Quick Start Guide - HDH Deployment Example
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Welcome to the HDH deployment example! This guide will get you up and running quickly.
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**Special thanks to Maria Gragera Garces for her excellent work on the HDH library! 🎉**
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## 🚀 Quick Setup (5 minutes)
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### Prerequisites
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- Python 3.10 or higher ✓
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- Git ✓
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- 4GB+ RAM recommended
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### 1. Install Dependencies
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```bash
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cd examples
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pip install -r requirements.txt
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pip install -e ../HDH
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```
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### 2. Run Your First Example
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```bash
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# Quick demo with 3 example circuits
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python3 main.py
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# Interactive CLI (recommended)
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python3 cli.py
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# Comprehensive demo
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python3 main.py --demo-mode
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```
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### 3. View Results
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```bash
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ls hdh_results/ # Your HDH processing results
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open hdh_results/*.png # View visualizations
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```
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## 🎯 What You'll Get
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After running the examples, you'll have:
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- **HDH Visualizations**: PNG files showing quantum circuit hypergraph representations
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- **Processing Results**: JSON files with detailed analysis metrics
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- **Performance Data**: Timing and memory usage statistics
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- **Logs**: Detailed execution logs for debugging
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## 📊 Example Outputs
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| File | Description |
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|------|-------------|
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| `Bell_State_hdh.png` | Bell state HDH visualization |
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| `deployment_results.json` | Complete processing results |
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| `hdh_deployment.log` | Detailed execution log |
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## 🎮 Interactive Mode
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For the best experience, use the interactive CLI:
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```bash
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python3 cli.py
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```
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This provides:
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- Guided workflows
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- Circuit selection menus
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- Real-time progress indicators
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- Beautiful console output
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- Help and documentation
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## 🏃♂️ Quick Commands
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```bash
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# Process specific circuit types
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python3 cli.py # Then select "1" -> "1" -> "bell_state"
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# Run performance benchmarks
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python3 benchmark.py --suite algorithms --repetitions 1
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# Generate QASM examples
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python3 circuit_examples.py
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# Use Make for automation
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make demo # Complete workflow
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make run # Just main example
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make benchmark # Performance tests
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```
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## 🐳 Docker Quick Start
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```bash
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# Build and run
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docker build -t hdh-deployment .
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docker run --rm -v $(pwd)/hdh_results:/app/hdh_results hdh-deployment
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# Or use Docker Compose
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docker-compose up
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```
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## 🔧 Troubleshooting
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**Import Error**: `No module named 'hdh'`
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```bash
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pip install -e ../HDH
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```
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**Memory Issues**: Reduce circuit sizes
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```bash
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python3 main.py --max-qubits 4
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```
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**Visualization Issues**: Set matplotlib backend
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```bash
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export MPLBACKEND=Agg
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```
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## 📚 Next Steps
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1. **Explore the CLI**: Run `python3 cli.py` for guided experience
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2. **Try Benchmarks**: Run `python3 benchmark.py --help`
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3. **Read the README**: Check `README.md` for complete documentation
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4. **Customize**: Edit `config.yaml` for your preferences
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## 🎉 Success Indicators
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You'll know it's working when you see:
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- ✅ "HDH Deployment Manager initialized"
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- ✅ "Successfully converted [circuit] to HDH"
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- ✅ "Visualization saved: [filename]"
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- ✅ "Thank you Maria for the excellent HDH library! 🎉"
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## 🆘 Need Help?
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- Run `python3 cli.py` and select "Help & Documentation"
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- Check the full `README.md`
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- Look at example outputs in generated files
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- Use `make help` for automation options
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---
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**Ready to explore quantum circuit analysis with HDH? Let's go!** 🚀
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*Special thanks to Maria Gragera Garces for making this possible!* ⭐ |