RLForQuantumCircuits seeks to build on current efforts in algorithm improvement and development using a reinforcement learning approach. The algorithms we are working with are Matrix Multiplication, Fast Fourier Transform, Quantum Fourier Transform, and the Classical Simulation of Quantum Circuits. The Reinforcement learning models will look for ways to reduce the number of operations that are needed to perform these algorithms on different sizes and dimensions.
The purpose of this repository is to provide resources for others interested in the topic to learn the fundamentals that construct it and access materials to make their own contributions.