MITPQML

GitHub repository for the MITP Summer School 2023 : Machine Learning in Particle Theory Quantum Machine Learning course.

Each session we will push an exercise to the repository based on content you will learn in the lectures. In order to be successful in running the exercises please ensure that you create a virtual Python v3.10 environment and install the packages in the requirements.txt file using pip install -r requirements.txt.

Then add your Python environment to jupyter notebook. Using conda you can do this by:

1. Install ipykernel: conda install -c anaconda ipykernel
2. Add environment: python -m ipykernel install --user --name=envName

The exercises include:

1. Introduction to Quantum Computing
2. Introduction to Quantum Computing 2
3. The Grover Algorithm and Amplitude Estimation
4. Optimisation and the Variational Quantum Eigensolver
5. Variational Quantum Circuit for the Titanic dataset
6. Quadratic Unconstrained Binary Optimization
7. Quantum Approximate Optimization Algorithm