3. First QEC Simulation

This guide will walk you through your first quantum error correction (QEC) experiment using OpenQStack.

You’ll run a full encode → error → syndrome → recovery → decode cycle using the 3-qubit bit-flip code.

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Step 1: Run the Demo

Navigate to the examples/ directory and run the demo script:

cd examples
python openq_blink.py

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Step 2: Understand What’s Happening

The script performs a full QEC cycle:

1. Encoding
   The logical qubit (e.g., |ψ⟩ = |0⟩) is encoded into a 3-qubit state.

2. Error Injection
   A random bit-flip error (X gate) is applied to one of the physical qubits.

3. Syndrome Measurement
   A parity check is performed to detect the error.

4. Recovery
   Based on the syndrome, the most likely correction is applied.

5. Decoding
   The recovered 3-qubit state is decoded back to a single-qubit logical state.

You will see:

• Intermediate states printed to the terminal
• Syndrome bits displayed (e.g., "010")
• The final recovered logical qubit state
• A probability plot (if matplotlib is installed)

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Step 3: Project Structure

openqstack/
├── openqstack/          # Core logic: codes, noise, visualization
│   ├── qec.py
│   ├── visualize.py
│   └── __init__.py
│
├── examples/            # Demo scripts and walkthroughs
│   └── openq_blink.py
│
├── tests/               # Unit tests
│   └── test_bitflip.py
│
├── requirements.txt     # Python dependencies
├── setup.py             # Installable module
└── README.md            # Project overview

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Step 4: Try More

Once the basic demo is working, try:

• Changing the logical input state:

  psi = [1/np.sqrt(2), 1/np.sqrt(2)]
  

• Using a depolarizing noise model:

  from openqstack.qec import DepolarizingChannel
  channel = DepolarizingChannel(p=0.1, n_qubits=3)
  noisy_state = channel(encoded)
  

• Visualizing results:

  from openqstack.visualize import plot_bloch
  plot_bloch(decoded)
  

• Writing your own recovery logic or adding a custom error

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Step 5: Troubleshooting

If something goes wrong:

• Make sure you're using Python 3.8+

• Install missing packages:

  pip install -r requirements.txt
  

• If plots don’t show:

  pip install matplotlib
  

• Run tests to confirm functionality:

  pytest tests/
  

• Verify package visibility:

  python -m openqstack
  

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Questions?

OpenQStack is an open-source initiative supporting quantum education.

• Found a bug? Open an issue.
• Teaching with OpenQStack? Let us know.
• Want to contribute? Fork the repo or start a discussion.

We welcome collaboration from students, educators, and researchers.