Quantum Computing with Silq Programming

This is the code repository for Quantum Computing with Silq Programming, published by Packt.

Get up and running with quantum computing with the simplicity of this new high-level programming language

What is this book about?

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 covers the following exciting features: Identify the challenges that researchers face in quantum programming Understand quantum computing concepts and learn how to make quantum circuits Explore Silq programming constructs and use them to create quantum programs Use Silq to code quantum algorithms such as Grover's and Simon’s Discover the practicalities of quantum error correction with Silq Explore useful applications such as quantum machine learning in a practical way

If you feel this book is for you, get your copy today!

Instructions and Navigations

All of the code is organized into folders. For example, Chapter02.

The code will look like the following:

def geometric():!?? {
    count := 0;
    ok := true;
    while ok{
        count += 1;

Following is what you need for this book: This Silq quantum computing book is for students, researchers, and scientists looking to learn quantum computing techniques and software development. Quantum computing enthusiasts who want to explore this futuristic technology will also find this book useful. Beginner-level knowledge of any programming language as well as mathematical topics such as linear algebra, probability, complex numbers, and statistics is required.

With the following software and hardware list you can run all code files present in the book (Chapter 1-13).

Software and Hardware List

No.	Software required	OS required
1	Visual Studio with Silq plugin	Windows, Mac OS X, and Linux (Any)

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.

Get to Know the Author

Srinjoy Ganguly Srinjoy Ganguly is the founder and CEO of AdroitERA, an EdTech firm, and possesses a Master's in quantum computing technology from the Technical University of Madrid, and a Master's in artificial intelligence from the University of Southampton. He has over 4 years' experience in quantum computing and 5 years' experience in machine learning and deep learning. He currently leads the Quantum Machine Learning (QML) study space at QWorld. He has given an expert talk on QML at IEEE SPS. His research interests include QML, Quantum Image Processing, Quantum Natural Language Processing (QNLP), machine learning, and deep learning.

Thomas Cambier Thomas Cambier is a French programmer and software developer. After studying top-level mathematics, physics, and computer science at Ecole Polytechnique, France's leading engineering school, he obtained a Master's degree in computer science at ETH Zürich on a broad range of subjects going from algorithmics and cryptography to object-oriented programming. Deeply interested in the promising possibilities resulting from quantum computing, he wrote his Master's thesis on the design of quantum algorithms with Silq, a brand-new high-level quantum language created by a research group at ETH Zürich.

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