The purpose of this project is to explain quantum information theory using both theory and Python application to a beginner who has little to no experience with the field. Very little pre-requisites are required and I am very confident that any ambitious highschooler can complete this text. The initial form of this series will be in a set of Jupyter notebooks that will eventually be turned into an e-book/video series. Note that if you have any worries, questions, or have spotted any mistakes, you can contact me at any time on [email protected]
For the Python implementations, the following modules will be necessary:
- Numpy (for linear algebra and math in general)
- Qiskit (a multi-purpose quantum computing framework that will be used for all QC stuff)
- SymPy (includes tools that will be used for stuff like matrix visualization)
- QPy (a basic numerical quantum mechanics solver I made). It comes with the repository
The first three chapters of this text has been used for a Quantum Computing school my colleagues and I ran over the summer (see the TEQS repo). Apart from re-writing Chapter 4 and making it focused on The 4 reduced postulates of QM, I have no interest in working further on this for the foreseeable future.