You're reading from Quantum Computing with Silq Programming Get up and running with quantum computing with the simplicity of this new high-level programming language

Product type Paperback

Published in Apr 2021

Publisher Packt

ISBN-13 9781800569669

Length 310 pages

Edition 1st Edition

Languages

C++

Tools

Quantum Development Kit

Concepts

Programming Language

Authors (2):

Thomas Cambier

Srinjoy Ganguly

View More author details

Table of Contents (19) Chapters

Preface

1. Section 1: Essential Background and Introduction to Quantum Computing

2. Chapter 1: Essential Mathematics and Algorithmic Thinking FREE CHAPTER

3. Chapter 2: Quantum Bits, Quantum Measurements, and Quantum Logic Gates

4. Chapter 3: Multiple Quantum Bits, Entanglement, and Quantum Circuits

5. Chapter 4: Physical Realization of a Quantum Computer

6. Section 2: Challenges in Quantum Programming and Silq Programming

7. Chapter 5: Challenges in Quantum Computer Programming

8. Chapter 6: Silq Programming Basics and Features

9. Chapter 7: Programming Multiple-Qubit Quantum Circuits with Silq

10. Section 3: Quantum Algorithms Using Silq Programming

11. Chapter 8: Quantum Algorithms I – Deutsch-Jozsa and Bernstein-Vazirani

12. Chapter 9: Quantum Algorithms II – Grover's Search Algorithm and Simon's Algorithm

13. Chapter 10: Quantum Algorithms III – Quantum Fourier Transform and Phase Estimation

14. Section 4: Applications of Quantum Computing

15. Chapter 11: Quantum Error Correction

16. Chapter 12: Quantum Cryptography – Quantum Key Distribution

17. Chapter 13: Quantum Machine Learning

18. Other Books You May Enjoy

Quantum annealing-based quantum computers

Quantum annealing is a technique used to find the global minimum or optimal solution to a problem that can have a large number of solutions. Essentially it is used for optimization problems such as the Traveling Salesman Problem (TSP), which seeks to find the shortest path for a traveling salesman to visit every city on the route only once and then return back to their starting city. The TSP sounds very simple in description but is a very hard problem to solve because as the number of cities increase, thousands, millions, or even billions of paths emerge as well, which makes this a combinatorial optimization problem. For this kind of problem, quantum computers are the best because the TSP cannot be solved even by today's fastest computers.

D-Wave, a Canadian company, uses the quantum annealing technology to solve combinatorial optimization problems and their computers have been purchased by Google, Microsoft, and NASA for research...