As the last piece of the training saga for becoming a theoretical quantum information scientist, we focus on a side that deals with the implementation of your ideas. The main weapon of our choice is tensor networks. Hence, we will cover a good amount of materials in Matrix Computations(Golub & Van Loan, 2013). However, concepts in machine learning and pattern recognition also proves to be useful. Therefore, we will also cover materials in Pattern Recognition and Machine Learning(Bishop, 2016) and Deep Learning: Foundations and Concepts(Bishop & Bishop, 2024).
As the goal suggests, THE most important goal of this book is to enable you to turn your ideas into programs. Therefore, coding will be the essential part of this book. The language we choose is Julia.