Book Image

Quantum Computing with Silq Programming

By : Srinjoy Ganguly, Thomas Cambier
Book Image

Quantum Computing with Silq Programming

By: Srinjoy Ganguly, Thomas Cambier

Overview of this book

Quantum computing is a growing field, with many research projects focusing on programming quantum computers in the most efficient way possible. One of the biggest challenges faced with existing languages is that they work on low-level circuit model details and are not able to represent quantum programs accurately. Developed by researchers at ETH Zurich after analyzing languages including Q# and Qiskit, Silq is a high-level programming language that can be viewed as the C++ of quantum computers! Quantum Computing with Silq Programming helps you explore Silq and its intuitive and simple syntax to enable you to describe complex tasks with less code. This book will help you get to grips with the constructs of the Silq and show you how to write quantum programs with it. You’ll learn how to use Silq to program quantum algorithms to solve existing and complex tasks. Using quantum algorithms, you’ll also gain practical experience in useful applications such as quantum error correction, cryptography, and quantum machine learning. Finally, you’ll discover how to optimize the programming of quantum computers with the simple Silq. By the end of this Silq book, you’ll have mastered the features of Silq and be able to build efficient quantum applications independently.
Table of Contents (19 chapters)
Section 1: Essential Background and Introduction to Quantum Computing
Section 2: Challenges in Quantum Programming and Silq Programming
Section 3: Quantum Algorithms Using Silq Programming
Section 4: Applications of Quantum Computing


Over the course of this chapter, we have seen two famous problems: Deutsch-Jozsa and Bernstein-Vazirani, designed to demonstrate that quantum algorithms can use the properties of quantum computing, such as the superposition of states or quantum interference, to gain an advantage over their classical counterparts.

After studying how to solve the problems theoretically with quantum techniques and looking at what the speedup was compared to the classical solution, we then practically implemented the algorithms in Silq and tested them on some examples.

We familiarized ourselves with Silq programming by implementing basic quantum algorithms using concepts such as the uniform superposition of states for a given number of qubits, which will be used in the next sections when designing more complex algorithms. It was also useful to showcase safe uncomputation, which is one of the key features of the Silq language.

In the next chapter, we will build on what we learned in this...