Quantum Machine Learning

  1. Algorithmic Summaries (40 pts.) We have now added more algorithms to our tool kit, including the quantum key distribution algorithm, the quantum coin flip algorithm, variational quantum eigensolver, the k-Nearest Neighbors, and quantum neural networks. In a short paragraph for each algorithm, explain its purpose, its function, and why it works. Draw a sample circuit for each algorithm and explain all of the components and their purpose. For you own studies, combine this summary with the one from homework 7 to keep a full list of the algorithms you are able to implement.
  2. Quantum vs. Classical Machine Learning (10 pts.) Compare and constract the machine learning workflow using clasical algorithms versus using quantum algorithms.