About the challenge

The Qiskit Quantum Hackathon 2026 is a one-day hackathon on Saturday, 14 November 2026. Teams solve three quantum computing problems of increasing difficulty in Jupyter notebooks, using Qiskit and the Qiskit Aer simulator. Everything runs on a laptop: you do not need access to quantum hardware, a cloud account or any paid service.

The three challenges

1. E91 quantum key distribution (easy). Simulate Ekert's entanglement-based key distribution protocol. Prepare Bell pairs, measure along random directions, sift a secret key, test the CHSH inequality, and catch an eavesdropper who intercepts and resends qubits. A stretch task asks whether an eavesdropper can be told apart from ordinary noise.
2. Grover's algorithm under noise (medium). Use Grover search to find a hidden key, then measure how depolarizing and bit-flip noise limit the number of useful iterations, and compare with a fair classical baseline.
3. VQE for lithium hydride (hard). Build the qubit Hamiltonian of the LiH molecule, reduce it with symmetries, design a variational circuit and optimize it on a noisy simulator within a fixed budget of gates and shots. Your method is tested at bond lengths that are not revealed in advance. This challenge decides close rankings.

Schedule (Saturday, 14 November 2026)

Get started

Set up your Python environment before the event day, so that you can start solving at 10:00 AM. 

1. Install Python 3.11 or newer from https://www.python.org/downloads/ (the packages do not support older versions). Check the version with python3 --version on Linux and macOS or py -3 --version on Windows.

2. Download requirements.txt into a new folder, for example quantum-hackathon.

3. Create a virtual environment and install the packages. Open a terminal in that folder and run:

   Linux and macOS:

   python3 -m venv .venv
   source .venv/bin/activate
   pip install --upgrade pip
   pip install -r requirements.txt
   

   Windows (PowerShell):

   py -3 -m venv .venv
   .venv\Scripts\Activate.ps1
   python -m pip install --upgrade pip
   pip install -r requirements.txt
   

   If you use conda, create an environment with conda create -n qiskit-hackathon python=3.11, activate it, and run pip install -r requirements.txt.

4. Check the installation:

   python -c "import qiskit, qiskit_aer, numpy, scipy, matplotlib; print('qiskit', qiskit.__version__, '| qiskit-aer', qiskit_aer.__version__)"
   

   The expected output is qiskit 2.6.1 | qiskit-aer 0.18.2.

5. On 14 November at 10:00 AM, download the hackathon package and unzip it. Activate your environment, open a terminal in the unzipped qiskit-quantum-hackathon folder and start JupyterLab with jupyter lab. Read README.md in the package first: it explains the rules, the hints, the scoring and the submission format.

If you cannot install Python on your laptop, you can use Google Colab instead; the README.md in the package explains how.

• Challenge 1: E91 Quantum Key Distribution (100 points)
  90 pts: automatic tests with hidden keys, angles and noise levels in a clean re-run with a fresh seed. 10 pts: judges’ review of your written answers, experiments and figures. Breakdown in Section 11 of the notebook.
• Challenge 2: Grover’s Algorithm under Noise (100 points)
  90 pts: automatic tests with hidden keys and noise levels in a clean re-run with a fresh seed. 10 pts: judges’ review of your noise analysis, classical comparison and figures. Breakdown in Section 11 of the notebook.
• Challenge 3: VQE for Lithium Hydride (100 points)
  90 pts: automatic tests at hidden bond lengths; part is scored on how close your energies are to exact values. 10 pts: judges’ review of your ansatz, results and figures. Breakdown in Section 11 of the notebook.
• Tie-breakers
  Ties broken by: 1) higher Challenge 3 score, 2) lower mean VQE energy error, 3) fewer two-qubit gates, 4) fewer VQE shots, 5) higher Challenge 2 score. Teams still tied share the rank.