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

Grover's search for multiple solutions using Silq programming

Until now, we have looked into Grover's search for finding only one solution, which we termed as the marked element. But Grover's algorithm can also be used to find multiple solutions, which means multiple marked elements. The number of iterations in the case of multiple solutions is around , where M is the number of marked elements. Let's now start with the extensive mathematical treatment for the case of multiple solutions in the next section.

Mathematical treatment of Grover's search for multiple solutions

Consider that the number of marked elements is M such that ; so, therefore, we start with state , which is the superposition of all the M marked elements.

We also have our original state prepared, which is . Now, the original state can be written in terms of N and M as coefficients by a bit of mathematical manipulation, as follows:

To simplify the preceding...