Quantum Error Correction Experiments

This repository contains two Jupyter notebooks exploring quantum error correction (QEC) using Qiskit:

• repetition-code.ipynb — A simple 3-qubit repetition code, illustrating the basics of encoding, noise, and majority-vote decoding.
• 3-distance-surface-code.ipynb — A distance-3 planar surface code with both single-round and space–time decoding, including a comparison of logical failure rates.

Features

• QEC simulation with depolarising + readout noise models
• Surface code stabilizer layout and syndrome extraction
• MWPM (minimum-weight perfect matching) decoders for both 2D and 3D (space–time)
• Performance plots comparing decoding strategies

Example Results

We include 10 example plots comparing single-round decoding vs. k-round space–time decoding in the
image-results/ folder.

Across these examples:

• Space–time decoding (k rounds) consistently outperforms single-round decoding.
• Typical estimated logical failure rates:
  • k-round space–time: ~0.16–0.18
  • Single-round: ~0.18–0.20

Example:

---

Requirements

• Python 3.9+
• Qiskit
• NetworkX
• Matplotlib
• NumPy

Install with:

pip install qiskit networkx matplotlib numpy