M Mohile wrote:It would be helpful if the authors would let us know whether mathematics, statistics is necessary in understanding quantum computing?
If yes, would like them to help us know the topics that need good understanding before we all deep dive into the world of qubits.
Hi there! The amount of math needed for QC understanding is scalable, just like the math needed for programming a regular (classical) computer.
For example, it's not really necessary to understand how transistors work (hard-core math) in order to use a computer and develop software, although you can.
Similarly, it's not necessary to get all up in the deep quantum-physics-math to start programming a QPU, although you can if you want.
In our book, it's useful to have high-school algebra and basic coding, but nothing else is required.
We introduce the concepts and provide hands-on QPU programming experience
without doing a physics deep-dive.
For those who want more than that, chapter 14 contains all sorts of mathematics, with links and references to materials where it can be explored in-depth.
For example, an explanation of Shor's factoring algorithm can be mathematically intense, but we focus (using some nice visual models) on how and why it works, rather than deriving proofs, and then provide running code samples such as
this one so you can try it out for yourself. And then if you need more deep math detail, chapter 14 has good references.
The one exception in the book is chapter 13 (Quantum Machine Learning), but most of the heavy math in that chapter is from machine learning, not QC.
Statistics: Advanced QC involves interesting correlations and Monte Carlo-style sampling, so people who do enjoy the world of hard-core statistics will have years of fascinating material to explore. :]