QuantumMachineLearning

This project is divided in two parts:

1. Utilizing Neural Networks to sort signal from background processes in high energy particle collisions
2. Utilizing variational circuits, also called Quantum Neural Networks, to do the same task

This is a special curriculum project at UiO. The task to sort signal from background processes is from the Higgs boson Machine Learning challenge from 2014.

Part 1 used the Python library TensorFlow and sci-kit learn to make the Neural Network.

Part 2 used the Python library Qiskit to simulate a quantum circuit to do quantum machine learning.

The results and full project is in the pfd file. Enjoy!