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

Implementing the QFT using Silq

In this section, you are going to learn how to implement the QFT algorithm from the very beginning, considering all the mathematics that we have gone through in the Exploring the QFT section.

In Figure 10.2, you can see a diagram of the QFT. This diagram is a generalized version of the QFT circuit that you saw for the three-qubits case in Figure 10.1 in the preceding section:

Figure 10.2 – QFT circuit for n qubits

Our code for the QFT will be based on Figure 10.2. The Silq implementation of the QFT is fairly intuitive and is very concise in size. Using Hadamard and controlled phasing, we generate the state corresponding to the circuit with the qubits in reverse order. Thus, the reversing of the qubits is done in anticipation at the beginning of the function so that, after applying Hadamard and phasing them, the qubits are outputted in the correct order. The code is as follows:

def QFT[n:!](: int[n])mfree: int[n]...